ver2.5

OpenAITools/CrinicalTrialTools.py

@@ -309,3 +309,115 @@ class GraderAgent:
         result = GraderAgent.invoke({"document": AgentJudgment_output})
         AgentGrade = result.score
         return AgentGrade
+
+import re
+
+class LLMTranslator:
+    def __init__(self, llm):
+        self.llm = llm
+        self.structured_llm_modifier = self.llm.with_structured_output(ModifyQuestion)
+
+        self.system_prompt = """あなたは、優秀な翻訳者です。\n
+                                日本語を英語に翻訳して下さい。\n
+                             """
+        self.system_prompt2 = """あなたは、優秀な翻訳者です。\n
+                                日本語を英語に以下のフォーマットに従って翻訳して下さい。\n
+                                MainQuestion:
+                                Known gene mutation:
+                                Measurable tumour:
+                                Biopsiable tumour:
+                             """
+
+        self.modify_prompt = ChatPromptTemplate.from_messages(
+            [
+                ("system", self.system_prompt),
+                ("human", "ユーザーの質問: {question}"),
+            ]
+        )
+
+        self.modify_prompt2 = ChatPromptTemplate.from_messages(
+            [
+                ("system", self.system_prompt2),
+                ("human", "ユーザーの質問: {question}"),
+            ]
+        )
+
+    def is_english(self, text: str) -> bool:
+        """
+        簡易的にテキストが英語かどうかを判定する関数
+        :param text: 判定するテキスト
+        :return: 英語の場合True、日本語の場合False
+        """
+        # 英語のアルファベットが多く含まれているかを確認
+        return bool(re.match(r'^[A-Za-z0-9\s.,?!]+$', text))
+
+    def translate(self, question: str) -> str:
+        """
+        質問を翻訳するメソッド。英語の質問はそのまま返す。
+        :param question: 質問文
+        :return: 翻訳済みの質問文、または元の質問文（英語の場合）
+        """
+        # 質問が英語の場合、そのまま返す
+        if self.is_english(question):
+            return question
+        
+        # 日本語の質問は翻訳プロセスにかける
+        question_modifier = self.modify_prompt | self.structured_llm_modifier
+        result = question_modifier.invoke({"question": question})
+        modify_question = result.modified_question
+        return modify_question
+    
+    def translateQuestion(self, question: str) -> str:
+        """
+        フォーマット付きで質問を翻訳するメソッド。
+        :param question: 質問文
+        :return: フォーマットに従った翻訳済みの質問
+        """
+        question_modifier = self.modify_prompt2 | self.structured_llm_modifier
+        result = question_modifier.invoke({"question": question})
+        modify_question = result.modified_question
+        return modify_question
+
+def generate_ex_question(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable):
+    # GeneMutationが空の場合はUnknownに設定
+    gene_mutation_text = GeneMutation if GeneMutation else "Unknown"
+    
+    # MeseableとBiopsiableの値をYes, No, Unknownに変換
+    meseable_text = (
+        "Yes" if Meseable == "有り" else "No" if Meseable == "無し" else "Unknown"
+    )
+    biopsiable_text = (
+        "Yes" if Biopsiable == "有り" else "No" if Biopsiable == "無し" else "Unknown"
+    )
+    
+    # 質問文の生成
+    ex_question = f"""{age}歳{sex}の{tumor_type}患者さんはこの治験に参加することができますか？
+判明している遺伝子変異: {gene_mutation_text}
+Meseable tumor: {meseable_text}
+Biopsiable tumor: {biopsiable_text}
+です。
+"""
+    return ex_question
+
+def generate_ex_question_English(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable):
+    # GeneMutationが空の場合は"Unknown"に設定
+    gene_mutation_text = GeneMutation if GeneMutation else "Unknown"
+    
+    # sexの値を male または female に変換
+    sex_text = "male" if sex == "男性" else "female" if sex == "女性" else "Unknown"
+    
+    # MeseableとBiopsiableの値を "Yes", "No", "Unknown" に変換
+    meseable_text = (
+        "Yes" if Meseable == "有り" else "No" if Meseable == "無し" else "Unknown"
+    )
+    biopsiable_text = (
+        "Yes" if Biopsiable == "有り" else "No" if Biopsiable == "無し" else "Unknown"
+    )
+    
+    # 英語での質問文を生成
+    ex_question = f"""Can a {age}-year-old {sex_text} patient with {tumor_type} participate in this clinical trial?
+Known gene mutation: {gene_mutation_text}
+Measurable tumor: {meseable_text}
+Biopsiable tumor: {biopsiable_text}
+"""
+    return ex_question

PATHtoOriginaltool.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -17,7 +17,7 @@
        " '/Users/satoc/Dropbox/programing/python/gradio']"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -40,7 +40,7 @@
        "'/Users/satoc/Dropbox/programing/python/gradio'"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -60,13 +60,14 @@
        "'/Users/satoc/Dropbox/programing/python/gradio/original_tools.pth'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "fileName = paths[-1] + '/' +'original_tools.pth'\n",
+    "#fileName = \"/Users/satoc/Dropbox/programing/python/ClinicalTrialV2\" + '/' +'original_tools.pth'\n",
     "fileName"
    ]
   },
@@ -79,7 +80,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -88,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -97,7 +98,7 @@
        "'/Users/satoc/Dropbox/programing/python/ClinicalTrialV2'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -108,7 +109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -125,14 +126,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['/Users/satoc/miniforge3/envs/gradio/lib/python312.zip', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12/lib-dynload', '', '/Users/satoc/.local/lib/python3.12/site-packages', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12/site-packages', '/Users/satoc/Dropbox/programing/python/gradio']\n",
+      "['/Users/satoc/miniforge3/envs/gradio/lib/python312.zip', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12/lib-dynload', '', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12/site-packages', '/Users/satoc/Dropbox/programing/python/gradio']\n",
       "/Users/satoc/Dropbox/programing/python/gradio/original_tools.pth\n",
       "/Users/satoc/Dropbox/programing/python/ClinicalTrialV2\n"
      ]
@@ -153,7 +154,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -162,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -176,6 +177,47 @@
    "outputs": [],
    "source": []
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      ".pthファイルを作成するパス: /Users/satoc/miniforge3/envs/gradio/lib/python3.12/site-packages/original_tools.pth\n",
+      "現在の作業ディレクトリ: /Users/satoc/Dropbox/programing/python/ClinicalTrialV2\n",
+      "モジュール検索パス:\n",
+      "['/Users/satoc/miniforge3/envs/gradio/lib/python312.zip', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12/lib-dynload', '', '/Users/satoc/.local/lib/python3.12/site-packages', '/Users/satoc/miniforge3/envs/gradio/lib/python3.12/site-packages', '/Users/satoc/Dropbox/programing/python/gradio']\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "import os\n",
+    "import site\n",
+    "\n",
+    "# site-packagesのディレクトリを取得\n",
+    "site_packages_path = site.getsitepackages()[0]  # 複数ある場合、通常は最初のものを使用\n",
+    "\n",
+    "# .pthファイルのパスをsite-packagesに設定\n",
+    "fileName = os.path.join(site_packages_path, 'original_tools.pth')\n",
+    "print(f\".pthファイルを作成するパス: {fileName}\")\n",
+    "\n",
+    "# 現在の作業ディレクトリを取得\n",
+    "cwd = os.getcwd()\n",
+    "print(f\"現在の作業ディレクトリ: {cwd}\")\n",
+    "\n",
+    "# .pthファイルを作成し、現在の作業ディレクトリのパスを書き込む\n",
+    "with open(fileName, mode='w') as f:\n",
+    "    f.write(cwd)\n",
+    "\n",
+    "# 確認のためにsys.pathを再表示\n",
+    "print(\"モジュール検索パス:\")\n",
+    "print(sys.path)\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

app.py

@@ -1,48 +1,55 @@
 import gradio as gr
 import pandas as pd
-from OpenAITools.FetchTools import fetch_clinical_trials, fetch_clinical_trials_jp
+from OpenAITools.FetchTools import fetch_clinical_trials
 from langchain_openai import ChatOpenAI
 from langchain_groq import ChatGroq
-from OpenAITools.CrinicalTrialTools import QuestionModifierEnglish, TumorNameExtractor, SimpleClinicalTrialAgent, GraderAgent
+from OpenAITools.CrinicalTrialTools import SimpleClinicalTrialAgent, GraderAgent, LLMTranslator, generate_ex_question_English
 
 # モデルとエージェントの初期化
 groq = ChatGroq(model_name="llama3-70b-8192", temperature=0)
-modifier = QuestionModifierEnglish(groq)
-extractor = TumorNameExtractor(groq)
+translator = LLMTranslator(groq)
 CriteriaCheckAgent = SimpleClinicalTrialAgent(groq)
 grader_agent = GraderAgent(groq)
 
 # データフレームを生成する関数
-def generate_dataframe_from_question(ex_question):
-    modified_question = modifier.modify_question(ex_question)
-    tumor_name = extractor.extract_tumor_name(ex_question)
-    df = fetch_clinical_trials(tumor_name)
+def generate_dataframe(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable):
+    # 日本語の腫瘍タイプを英語に翻訳
+    TumorName = translator.translate(tumor_type)
+
+    # 質問文を生成
+    ex_question = generate_ex_question_English(age, sex, TumorName, GeneMutation, Meseable, Biopsiable)
+    
+    # 臨床試験データの取得
+    df = fetch_clinical_trials(TumorName)
     df['AgentJudgment'] = None
     df['AgentGrade'] = None
-
+    
+    # 臨床試験の適格性の評価
     NCTIDs = list(df['NCTID'])
     progress = gr.Progress(track_tqdm=True)
-    
     for i, nct_id in enumerate(NCTIDs):
         target_criteria = df.loc[df['NCTID'] == nct_id, 'Eligibility Criteria'].values[0]
-        agent_judgment = CriteriaCheckAgent.evaluate_eligibility(target_criteria, modified_question)
+        agent_judgment = CriteriaCheckAgent.evaluate_eligibility(target_criteria, ex_question)
         agent_grade = grader_agent.evaluate_eligibility(agent_judgment)
+        
+        # データフレームの更新
         df.loc[df['NCTID'] == nct_id, 'AgentJudgment'] = agent_judgment
         df.loc[df['NCTID'] == nct_id, 'AgentGrade'] = agent_grade
         progress((i + 1) / len(NCTIDs))
     
+    # 列を指定した順に並び替え
     columns_order = ['NCTID', 'AgentGrade', 'Title', 'AgentJudgment', 'Japanes Locations', 
                      'Primary Completion Date', 'Cancer', 'Summary', 'Eligibility Criteria']
     df = df[columns_order]
+        
+    return df, df  # フィルタ用と表示用にデータフレームを返す
 
-    return df, df
-
-# AgentGradeが特定の値（yes, no, unclear）の行だけを選択する関数
+# 特定のAgentGrade（yes, no, unclear）に基づいて行をフィルタリングする関数
 def filter_rows_by_grade(original_df, grade):
     df_filtered = original_df[original_df['AgentGrade'] == grade]
     return df_filtered, df_filtered
 
-# フィルタ結果をCSVとして保存しダウンロードする関数
+# CSVとして保存しダウンロードする関数
 def download_filtered_csv(df):
     file_path = "filtered_data.csv"
     df.to_csv(file_path, index=False)
@@ -56,27 +63,44 @@ def download_full_csv(df):
 
 # Gradioインターフェースの作成
 with gr.Blocks() as demo:
-    gr.Markdown("## 質問を入力して、患者さんが参加可能な臨床治験の情報を収集。参加可能か否かを判断根拠も含めて提示します。結果はcsvとしてダウンロード可能です")
-    question_input = gr.Textbox(label="質問を入力してください", placeholder="例: 65歳男性でBRCA遺伝子の変異がある前立腺癌患者さんが参加できる臨床治験を教えて下さい。")
+    gr.Markdown("## 臨床試験適格性評価インターフェース")
+
+    # 各種入力フィールド
+    age_input = gr.Textbox(label="Age", placeholder="例: 65")
+    sex_input = gr.Dropdown(choices=["男性", "女性"], label="Sex")
+    tumor_type_input = gr.Textbox(label="Tumor Type", placeholder="例: gastric cancer, 日本でも良いですが英語の方が精度が高いです。")
+    gene_mutation_input = gr.Textbox(label="Gene Mutation", placeholder="例: HER2")
+    measurable_input = gr.Dropdown(choices=["有り", "無し", "不明"], label="Measurable Tumor")
+    biopsiable_input = gr.Dropdown(choices=["有り", "無し", "不明"], label="Biopsiable Tumor")
+
+    # データフレーム表示エリア
     dataframe_output = gr.DataFrame()
     original_df = gr.State()
     filtered_df = gr.State()
 
-    generate_button = gr.Button("日本で行われている患者さんの癌腫の臨床治験を全て取得する")
-    yes_button = gr.Button("AI Agentが患者さんが参加可能であると判断した臨床治験のみを表示")
-    no_button = gr.Button("AI Agentが患者さんが参加不可であると判断した臨床治験のみを表示")
-    unclear_button = gr.Button("AI Agentが���えられた情報だけでは判断不可能とした臨床治験のみを表示")
-    download_filtered_button = gr.Button("フィルタ結果をCSVとしてダウンロード")
-    download_full_button = gr.Button("全体結果をCSVとしてダウンロード")
-    download_filtered_output = gr.File(label="フィルタ結果のCSVダウンロード")
-    download_full_output = gr.File(label="全体結果のCSVダウンロード")
+    # データフレーム生成ボタン
+    generate_button = gr.Button("Generate Clinical Trials Data")
+
+    # フィルタリングボタン
+    yes_button = gr.Button("Show Eligible Trials")
+    no_button = gr.Button("Show Ineligible Trials")
+    unclear_button = gr.Button("Show Unclear Trials")
+    
+    # ダウンロードボタン
+    download_filtered_button = gr.Button("Download Filtered Data")
+    download_filtered_output = gr.File(label="Download Filtered Data")
+
+    download_full_button = gr.Button("Download Full Data")
+    download_full_output = gr.File(label="Download Full Data")
 
-    generate_button.click(fn=generate_dataframe_from_question, inputs=question_input, outputs=[dataframe_output, original_df])
+
+    # ボタン動作の設定
+    generate_button.click(fn=generate_dataframe, inputs=[age_input, sex_input, tumor_type_input, gene_mutation_input, measurable_input, biopsiable_input], outputs=[dataframe_output, original_df])
     yes_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State("yes")], outputs=[dataframe_output, filtered_df])
     no_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State("no")], outputs=[dataframe_output, filtered_df])
     unclear_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State("unclear")], outputs=[dataframe_output, filtered_df])
     download_filtered_button.click(fn=download_filtered_csv, inputs=filtered_df, outputs=download_filtered_output)
     download_full_button.click(fn=download_full_csv, inputs=original_df, outputs=download_full_output)
-
+    
 if __name__ == "__main__":
     demo.launch()

appOld.py

@@ -0,0 +1,82 @@
+import gradio as gr
+import pandas as pd
+from OpenAITools.FetchTools import fetch_clinical_trials, fetch_clinical_trials_jp
+from langchain_openai import ChatOpenAI
+from langchain_groq import ChatGroq
+from OpenAITools.CrinicalTrialTools import QuestionModifierEnglish, TumorNameExtractor, SimpleClinicalTrialAgent, GraderAgent
+
+# モデルとエージェントの初期化
+groq = ChatGroq(model_name="llama3-70b-8192", temperature=0)
+modifier = QuestionModifierEnglish(groq)
+extractor = TumorNameExtractor(groq)
+CriteriaCheckAgent = SimpleClinicalTrialAgent(groq)
+grader_agent = GraderAgent(groq)
+
+# データフレームを生成する関数
+def generate_dataframe_from_question(ex_question):
+    modified_question = modifier.modify_question(ex_question)
+    tumor_name = extractor.extract_tumor_name(ex_question)
+    df = fetch_clinical_trials(tumor_name)
+    df['AgentJudgment'] = None
+    df['AgentGrade'] = None
+
+    NCTIDs = list(df['NCTID'])
+    progress = gr.Progress(track_tqdm=True)
+    
+    for i, nct_id in enumerate(NCTIDs):
+        target_criteria = df.loc[df['NCTID'] == nct_id, 'Eligibility Criteria'].values[0]
+        agent_judgment = CriteriaCheckAgent.evaluate_eligibility(target_criteria, modified_question)
+        agent_grade = grader_agent.evaluate_eligibility(agent_judgment)
+        df.loc[df['NCTID'] == nct_id, 'AgentJudgment'] = agent_judgment
+        df.loc[df['NCTID'] == nct_id, 'AgentGrade'] = agent_grade
+        progress((i + 1) / len(NCTIDs))
+    
+    columns_order = ['NCTID', 'AgentGrade', 'Title', 'AgentJudgment', 'Japanes Locations', 
+                     'Primary Completion Date', 'Cancer', 'Summary', 'Eligibility Criteria']
+    df = df[columns_order]
+
+    return df, df
+
+# AgentGradeが特定の値（yes, no, unclear）の行だけを選択する関数
+def filter_rows_by_grade(original_df, grade):
+    df_filtered = original_df[original_df['AgentGrade'] == grade]
+    return df_filtered, df_filtered
+
+# フィルタ結果をCSVとして保存しダウンロードする関数
+def download_filtered_csv(df):
+    file_path = "filtered_data.csv"
+    df.to_csv(file_path, index=False)
+    return file_path
+
+# 全体結果をCSVとして保存しダウンロードする関数
+def download_full_csv(df):
+    file_path = "full_data.csv"
+    df.to_csv(file_path, index=False)
+    return file_path
+
+# Gradioインターフェースの作成
+with gr.Blocks() as demo:
+    gr.Markdown("## 質問を入力して、患者さんが参加可能な臨床治験の情報を収集。参加可能か否かを判断根拠も含めて提示します。結果はcsvとしてダウンロード可能です")
+    question_input = gr.Textbox(label="質問を入力してください", placeholder="例: 65歳男性でBRCA遺伝子の変異がある前立腺癌患者さんが参加できる臨床治験を教えて下さい。")
+    dataframe_output = gr.DataFrame()
+    original_df = gr.State()
+    filtered_df = gr.State()
+
+    generate_button = gr.Button("日本で行われている患者さんの癌腫の臨床治験を全て取得する")
+    yes_button = gr.Button("AI Agentが患者さんが参加可能であると判断した臨床治験のみを表示")
+    no_button = gr.Button("AI Agentが患者さんが参加不可であると判断した臨床治験のみを表示")
+    unclear_button = gr.Button("AI Agentが与えられた情報だけでは判断不可能とした臨床治験のみを表示")
+    download_filtered_button = gr.Button("フィルタ結果をCSVとしてダウンロード")
+    download_full_button = gr.Button("全体結果をCSVとしてダウンロード")
+    download_filtered_output = gr.File(label="フィルタ結果のCSVダウンロード")
+    download_full_output = gr.File(label="全体結果のCSVダウンロード")
+
+    generate_button.click(fn=generate_dataframe_from_question, inputs=question_input, outputs=[dataframe_output, original_df])
+    yes_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State("yes")], outputs=[dataframe_output, filtered_df])
+    no_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State("no")], outputs=[dataframe_output, filtered_df])
+    unclear_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State("unclear")], outputs=[dataframe_output, filtered_df])
+    download_filtered_button.click(fn=download_filtered_csv, inputs=filtered_df, outputs=download_filtered_output)
+    download_full_button.click(fn=download_full_csv, inputs=original_df, outputs=download_full_output)
+
+if __name__ == "__main__":
+    demo.launch()

dev/ClinicalTrialApp.ipynb

@@ -2,14 +2,27 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/var/folders/yw/qz00x75d7kb98f7vm8dkhkvw0000gn/T/ipykernel_63095/2786558369.py:6: LangChainDeprecationWarning: As of langchain-core 0.3.0, LangChain uses pydantic v2 internally. The langchain_core.pydantic_v1 module was a compatibility shim for pydantic v1, and should no longer be used. Please update the code to import from Pydantic directly.\n",
+      "\n",
+      "For example, replace imports like: `from langchain_core.pydantic_v1 import BaseModel`\n",
+      "with: `from pydantic import BaseModel`\n",
+      "or the v1 compatibility namespace if you are working in a code base that has not been fully upgraded to pydantic 2 yet. \tfrom pydantic.v1 import BaseModel\n",
+      "\n",
+      "  from OpenAITools.CrinicalTrialTools import QuestionModifierEnglish, TumorNameExtractor, SimpleClinicalTrialAgent, GraderAgent\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "* Running on local URL:  http://127.0.0.1:7862\n",
+      "* Running on local URL:  http://127.0.0.1:7861\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -17,7 +30,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7862/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7861/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -30,9 +43,16 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 3,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=glioma SEARCH[Location](AREA[LocationCountry]Japan AND AREA[LocationStatus]Recruiting)&pageSize=100\n"
+     ]
     }
    ],
    "source": [

dev/ClinicalTrialApp2.ipynb

@@ -0,0 +1,184 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "* Running on local URL:  http://127.0.0.1:7866\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7866/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=glioma SEARCH[Location](AREA[LocationCountry]Japan AND AREA[LocationStatus]Recruiting)&pageSize=100\n"
+     ]
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "import pandas as pd\n",
+    "from OpenAITools.FetchTools import fetch_clinical_trials\n",
+    "from langchain_openai import ChatOpenAI\n",
+    "from langchain_groq import ChatGroq\n",
+    "from OpenAITools.CrinicalTrialTools import SimpleClinicalTrialAgent, GraderAgent, LLMTranslator, generate_ex_question_English\n",
+    "\n",
+    "# モデルとエージェントの初期化\n",
+    "groq = ChatGroq(model_name=\"llama3-70b-8192\", temperature=0)\n",
+    "translator = LLMTranslator(groq)\n",
+    "CriteriaCheckAgent = SimpleClinicalTrialAgent(groq)\n",
+    "grader_agent = GraderAgent(groq)\n",
+    "\n",
+    "# データフレームを生成する関数\n",
+    "def generate_dataframe(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable):\n",
+    "    # 日本語の腫瘍タイプを英語に翻訳\n",
+    "    TumorName = translator.translate(tumor_type)\n",
+    "\n",
+    "    # 質問文を生成\n",
+    "    ex_question = generate_ex_question_English(age, sex, TumorName, GeneMutation, Meseable, Biopsiable)\n",
+    "    \n",
+    "    # 臨床試験データの取得\n",
+    "    df = fetch_clinical_trials(TumorName)\n",
+    "    df['AgentJudgment'] = None\n",
+    "    df['AgentGrade'] = None\n",
+    "    \n",
+    "    # 臨床試験の適格性の評価\n",
+    "    NCTIDs = list(df['NCTID'])\n",
+    "    progress = gr.Progress(track_tqdm=True)\n",
+    "    for i, nct_id in enumerate(NCTIDs):\n",
+    "        target_criteria = df.loc[df['NCTID'] == nct_id, 'Eligibility Criteria'].values[0]\n",
+    "        agent_judgment = CriteriaCheckAgent.evaluate_eligibility(target_criteria, ex_question)\n",
+    "        agent_grade = grader_agent.evaluate_eligibility(agent_judgment)\n",
+    "        \n",
+    "        # データフレームの更新\n",
+    "        df.loc[df['NCTID'] == nct_id, 'AgentJudgment'] = agent_judgment\n",
+    "        df.loc[df['NCTID'] == nct_id, 'AgentGrade'] = agent_grade\n",
+    "        progress((i + 1) / len(NCTIDs))\n",
+    "    \n",
+    "    # 列を指定した順に並び替え\n",
+    "    columns_order = ['NCTID', 'AgentGrade', 'Title', 'AgentJudgment', 'Japanes Locations', \n",
+    "                     'Primary Completion Date', 'Cancer', 'Summary', 'Eligibility Criteria']\n",
+    "    df = df[columns_order]\n",
+    "        \n",
+    "    return df, df  # フィルタ用と表示用にデータフレームを返す\n",
+    "\n",
+    "# 特定のAgentGrade（yes, no, unclear）に基づいて行をフィルタリングする関数\n",
+    "def filter_rows_by_grade(original_df, grade):\n",
+    "    df_filtered = original_df[original_df['AgentGrade'] == grade]\n",
+    "    return df_filtered, df_filtered\n",
+    "\n",
+    "# CSVとして保存しダウンロードする関数\n",
+    "def download_filtered_csv(df):\n",
+    "    file_path = \"filtered_data.csv\"\n",
+    "    df.to_csv(file_path, index=False)\n",
+    "    return file_path\n",
+    "\n",
+    "# 全体結果をCSVとして保存しダウンロードする関数\n",
+    "def download_full_csv(df):\n",
+    "    file_path = \"full_data.csv\"\n",
+    "    df.to_csv(file_path, index=False)\n",
+    "    return file_path\n",
+    "\n",
+    "# Gradioインターフェースの作成\n",
+    "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(\"## 臨床試験適格性評価インターフェース\")\n",
+    "\n",
+    "    # 各種入力フィールド\n",
+    "    age_input = gr.Textbox(label=\"Age\", placeholder=\"例: 65\")\n",
+    "    sex_input = gr.Dropdown(choices=[\"男性\", \"女性\"], label=\"Sex\")\n",
+    "    tumor_type_input = gr.Textbox(label=\"Tumor Type\", placeholder=\"例: gastric cancer, 日本でも良いですが英語の方が精度が高いです。\")\n",
+    "    gene_mutation_input = gr.Textbox(label=\"Gene Mutation\", placeholder=\"例: HER2\")\n",
+    "    measurable_input = gr.Dropdown(choices=[\"有り\", \"無し\", \"不明\"], label=\"Measurable Tumor\")\n",
+    "    biopsiable_input = gr.Dropdown(choices=[\"有り\", \"無し\", \"不明\"], label=\"Biopsiable Tumor\")\n",
+    "\n",
+    "    # データフレーム表示エリア\n",
+    "    dataframe_output = gr.DataFrame()\n",
+    "    original_df = gr.State()\n",
+    "    filtered_df = gr.State()\n",
+    "\n",
+    "    # データフレーム生成ボタン\n",
+    "    generate_button = gr.Button(\"Generate Clinical Trials Data\")\n",
+    "\n",
+    "    # フィルタリングボタン\n",
+    "    yes_button = gr.Button(\"Show Eligible Trials\")\n",
+    "    no_button = gr.Button(\"Show Ineligible Trials\")\n",
+    "    unclear_button = gr.Button(\"Show Unclear Trials\")\n",
+    "    \n",
+    "    # ダウンロードボタン\n",
+    "    download_filtered_button = gr.Button(\"Download Filtered Data\")\n",
+    "    download_filtered_output = gr.File(label=\"Download Filtered Data\")\n",
+    "\n",
+    "    download_full_button = gr.Button(\"Download Full Data\")\n",
+    "    download_full_output = gr.File(label=\"Download Full Data\")\n",
+    "\n",
+    "\n",
+    "    # ボタン動作の設定\n",
+    "    generate_button.click(fn=generate_dataframe, inputs=[age_input, sex_input, tumor_type_input, gene_mutation_input, measurable_input, biopsiable_input], outputs=[dataframe_output, original_df])\n",
+    "    yes_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State(\"yes\")], outputs=[dataframe_output, filtered_df])\n",
+    "    no_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State(\"no\")], outputs=[dataframe_output, filtered_df])\n",
+    "    unclear_button.click(fn=filter_rows_by_grade, inputs=[original_df, gr.State(\"unclear\")], outputs=[dataframe_output, filtered_df])\n",
+    "    download_filtered_button.click(fn=download_filtered_csv, inputs=filtered_df, outputs=download_filtered_output)\n",
+    "    download_full_button.click(fn=download_full_csv, inputs=original_df, outputs=download_full_output)\n",
+    "\n",
+    "\n",
+    "# インターフェースの起動\n",
+    "demo.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "gradio",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

dev/GraphAppDev6.ipynb

@@ -0,0 +1,1068 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/satoc/miniforge3/envs/gradio/lib/python3.12/site-packages/IPython/core/interactiveshell.py:3577: LangChainDeprecationWarning: As of langchain-core 0.3.0, LangChain uses pydantic v2 internally. The langchain_core.pydantic_v1 module was a compatibility shim for pydantic v1, and should no longer be used. Please update the code to import from Pydantic directly.\n",
+      "\n",
+      "For example, replace imports like: `from langchain_core.pydantic_v1 import BaseModel`\n",
+      "with: `from pydantic import BaseModel`\n",
+      "or the v1 compatibility namespace if you are working in a code base that has not been fully upgraded to pydantic 2 yet. \tfrom pydantic.v1 import BaseModel\n",
+      "\n",
+      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain_community.agent_toolkits import create_sql_agent\n",
+    "from langchain_openai import ChatOpenAI\n",
+    "from langchain_groq import ChatGroq\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
+    "import pandas as pd\n",
+    "from pydantic import BaseModel, Field\n",
+    "\n",
+    "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
+    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.embeddings import HuggingFaceEmbeddings\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "\n",
+    "\n",
+    "gpt = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n",
+    "#agent_gpt_executor = create_sql_agent(gpt, db=db, agent_type=\"tool-calling\", verbose=True)\n",
+    "\n",
+    "## make database\n",
+    "from langchain_community.utilities import SQLDatabase\n",
+    "from sqlalchemy import create_engine\n",
+    "\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema import SystemMessage\n",
+    "from langchain_core.prompts import MessagesPlaceholder\n",
+    "#agent_groq_executor = create_sql_agent(llm, db=db, agent_type=\"tool-calling\", verbose=True)\n",
+    "\n",
+    "from OpenAITools.FetchTools import fetch_clinical_trials, fetch_clinical_trials_jp\n",
+    "from OpenAITools.CrinicalTrialTools import QuestionModifierEnglish, TumorNameExtractor, SimpleClinicalTrialAgent,GraderAgent,LLMTranslator\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Define LLMS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gpt = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n",
+    "#agent_gpt_executor = create_sql_agent(gpt, db=db, agent_type=\"tool-calling\", verbose=True)\n",
+    "groq = ChatGroq(model_name=\"llama3-70b-8192\", temperature=0)\n",
+    "#agent_groq_executor = create_sql_agent(groq, db=db, agent_type=\"tool-calling\", verbose=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "age = \"65\"\n",
+    "sex =\"男性\"\n",
+    "tumor_type =\"胃癌\"\n",
+    "#tumor_type = \"gastric cancer\"\n",
+    "GeneMutation =\"HER2\"\n",
+    "Meseable = \"有り\"\n",
+    "Biopsiable = \"有り\"\n",
+    "NCTID = 'NCT06441994'\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_ex_question(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable):\n",
+    "    # GeneMutationが空の場合はUnknownに設定\n",
+    "    gene_mutation_text = GeneMutation if GeneMutation else \"Unknown\"\n",
+    "    \n",
+    "    # MeseableとBiopsiableの値をYes, No, Unknownに変換\n",
+    "    meseable_text = (\n",
+    "        \"Yes\" if Meseable == \"有り\" else \"No\" if Meseable == \"無し\" else \"Unknown\"\n",
+    "    )\n",
+    "    biopsiable_text = (\n",
+    "        \"Yes\" if Biopsiable == \"有り\" else \"No\" if Biopsiable == \"無し\" else \"Unknown\"\n",
+    "    )\n",
+    "    \n",
+    "    # 質問文の生成\n",
+    "    ex_question = f\"\"\"{age}歳{sex}の{tumor_type}患者さんはこの治験に参加することができますか？\n",
+    "判明している遺伝子変異: {gene_mutation_text}\n",
+    "Meseable tumor: {meseable_text}\n",
+    "Biopsiable tumor: {biopsiable_text}\n",
+    "です。\n",
+    "\"\"\"\n",
+    "    return ex_question"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_ex_question_English(age, sex, tumor_type, GeneMutation, Meseable, Biopsiable):\n",
+    "    # GeneMutationが空の場合は\"Unknown\"に設定\n",
+    "    gene_mutation_text = GeneMutation if GeneMutation else \"Unknown\"\n",
+    "    \n",
+    "    # sexの値を male または female に変換\n",
+    "    sex_text = \"male\" if sex == \"男性\" else \"female\" if sex == \"女性\" else \"Unknown\"\n",
+    "    \n",
+    "    # MeseableとBiopsiableの値を \"Yes\", \"No\", \"Unknown\" に変換\n",
+    "    meseable_text = (\n",
+    "        \"Yes\" if Meseable == \"有り\" else \"No\" if Meseable == \"無し\" else \"Unknown\"\n",
+    "    )\n",
+    "    biopsiable_text = (\n",
+    "        \"Yes\" if Biopsiable == \"有り\" else \"No\" if Biopsiable == \"無し\" else \"Unknown\"\n",
+    "    )\n",
+    "    \n",
+    "    # 英語での質問文を生成\n",
+    "    ex_question = f\"\"\"Can a {age}-year-old {sex_text} patient with {tumor_type} participate in this clinical trial?\n",
+    "Known gene mutation: {gene_mutation_text}\n",
+    "Measurable tumor: {meseable_text}\n",
+    "Biopsiable tumor: {biopsiable_text}\n",
+    "\"\"\"\n",
+    "    return ex_question\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Stomach cancer\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Define extractor\n",
+    "Translator = LLMTranslator(groq)\n",
+    "TumorName = Translator.translate(tumor_type)\n",
+    "print(TumorName)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "TumorName = \"gastric cancer\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Can a 65-year-old male patient with gastric cancer participate in this clinical trial?\\nKnown gene mutation: HER2\\nMeasurable tumor: Yes\\nBiopsiable tumor: Yes\\n'"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ex_question = generate_ex_question_English(age, sex, TumorName, GeneMutation, Meseable, Biopsiable)\n",
+    "ex_question"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "ex_question = \"\"\"\"65歳男性の胃癌患者さんはこの治験に参加することができますか？\n",
+    "判明している遺伝子変異:HER2\n",
+    "Meseable tumor:Yes\n",
+    "biopsiable tumor: Yes\n",
+    "です。\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#ex_question = \"65歳男性でが参加できる臨床治験を教えて下さい。\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#ex_question = \"65歳男性でBRCA遺伝子の変異がある前立患者さんが参加できる臨床治験を教えて下さい。\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "modifierEnglish = QuestionModifierEnglish(groq)\n",
+    "modifierEnglish.modify_question(ex_question)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fetching data from: https://clinicaltrials.gov/api/v2/studies?query.titles=gastric cancer SEARCH[Location](AREA[LocationCountry]Japan AND AREA[LocationStatus]Recruiting)&pageSize=100\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Make db\n",
+    "df = fetch_clinical_trials(TumorName)\n",
+    "# 新しい列を追加\n",
+    "df['AgentJudgment'] = None\n",
+    "df['AgentGrade'] = None\n",
+    "#df = df.iloc[:5, :]\n",
+    "NCTIDs = list(df['NCTID' ])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>NCTID</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>Primary Completion Date</th>\n",
+       "      <th>Cancer</th>\n",
+       "      <th>Summary</th>\n",
+       "      <th>Japanes Locations</th>\n",
+       "      <th>Eligibility Criteria</th>\n",
+       "      <th>AgentJudgment</th>\n",
+       "      <th>AgentGrade</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NCT03505320</td>\n",
+       "      <td>A Study of Zolbetuximab (IMAB362) in Adults Wi...</td>\n",
+       "      <td>2025-04-30</td>\n",
+       "      <td>Pharmacokinetics of Zolbetuximab, Gastric Canc...</td>\n",
+       "      <td>Zolbetuximab is being studied as a treatment f...</td>\n",
+       "      <td>Chiba, Tokyo</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Female subject eligib...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NCT05002127</td>\n",
+       "      <td>A Study of Evorpacept (ALX148) in Patients wit...</td>\n",
+       "      <td>2026-07</td>\n",
+       "      <td>Gastric Cancer, Gastroesophageal Junction Aden...</td>\n",
+       "      <td>A Phase 2/3 Study of Evorpacept (ALX148) in Co...</td>\n",
+       "      <td>Chiba, Fukuoka, Gifu, Kumamoto, Kyoto, Nagasak...</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* HER2-overexpressing a...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NCT05365581</td>\n",
+       "      <td>A Study of ASP2138 Given by Itself or Given Wi...</td>\n",
+       "      <td>2026-10-31</td>\n",
+       "      <td>Gastric Adenocarcinoma, Gastroesophageal Junct...</td>\n",
+       "      <td>Claudin 18.2 protein, or CLDN18.2 is a protein...</td>\n",
+       "      <td>Kashiwa, Nagoya, Osakasayama, Suita, Yokohama, ku</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Participant is consid...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NCT05111626</td>\n",
+       "      <td>Bemarituzumab Plus Chemotherapy and Nivolumab ...</td>\n",
+       "      <td>2026-09-26</td>\n",
+       "      <td>Gastric Cancer, Gastroesophageal Junction Aden...</td>\n",
+       "      <td>The main objective of Part 1 is to evaluate th...</td>\n",
+       "      <td>Sapporo, gun, ku, shi</td>\n",
+       "      <td>Inclusion Criteria Part 1 and Part 2:\\n\\n* Adu...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NCT06324357</td>\n",
+       "      <td>Beamion BCGC-1: A Study to Find a Suitable Dos...</td>\n",
+       "      <td>2027-02-22</td>\n",
+       "      <td>Metastatic Breast Cancer, Metastatic Gastric A...</td>\n",
+       "      <td>This study is open to adults aged 18 years and...</td>\n",
+       "      <td>ku, shi</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Signed and dated writ...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NCT06056024</td>\n",
+       "      <td>A Study to Test How Well Different Doses of BI...</td>\n",
+       "      <td>2027-05-26</td>\n",
+       "      <td>Solid Tumor, KRAS Mutation</td>\n",
+       "      <td>This study is open to adults with advanced can...</td>\n",
+       "      <td>Kashiwa, ku</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Patients with pathol...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NCT04379596</td>\n",
+       "      <td>Ph1b/2 Study of the Safety and Efficacy of T-D...</td>\n",
+       "      <td>2026-07-30</td>\n",
+       "      <td>Gastric Cancer</td>\n",
+       "      <td>DESTINY-Gastric03 will investigate the safety,...</td>\n",
+       "      <td>Kashiwa, gun, ku, shi</td>\n",
+       "      <td>Inclusion criteria:\\n\\n1. Male and female part...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NCT00197470</td>\n",
+       "      <td>Cytokine Gene Polymorphisms in Gastric Diseases</td>\n",
+       "      <td>Unknown Date</td>\n",
+       "      <td>Gastric Ulcer, Duodenal Ulcer, Gastric Cancer</td>\n",
+       "      <td>Recently, cytokine polymorphisms are considere...</td>\n",
+       "      <td>Hamamatsu</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n-\\n\\nExclusion Criteria...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NCT05205343</td>\n",
+       "      <td>Trans-Pacific Multicenter Collaborative Study ...</td>\n",
+       "      <td>2026-05-31</td>\n",
+       "      <td>Gastrostomy, Gastric, GastroEsophageal Cancer</td>\n",
+       "      <td>To compare the symptoms of patients who have a...</td>\n",
+       "      <td>Tokyo</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Able to speak and re...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NCT06490055</td>\n",
+       "      <td>Predicting the Efficacy in Advanced Gastric Ca...</td>\n",
+       "      <td>2025-12-31</td>\n",
+       "      <td>Gastric Cancer, Chemotherapy Effect, Paclitaxe...</td>\n",
+       "      <td>With advances in chemotherapy for gastric canc...</td>\n",
+       "      <td>Kurashiki</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. unresectable or recu...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>NCT06490159</td>\n",
+       "      <td>Predicting Peripheral Neuropathy of Paclitaxel...</td>\n",
+       "      <td>2025-12-31</td>\n",
+       "      <td>Gastric Cancer, Chemotherapy-induced Periphera...</td>\n",
+       "      <td>Although advances in chemotherapy have improve...</td>\n",
+       "      <td>Kurashiki</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. unresectable or recu...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>NCT05438459</td>\n",
+       "      <td>GAIA-102 Intraperitoneal Administration in Pat...</td>\n",
+       "      <td>2026-12-31</td>\n",
+       "      <td>Gastric Cancer, Pancreatic Cancer</td>\n",
+       "      <td>Phase I Part :\\n\\nConfirm the safety of GAIA-1...</td>\n",
+       "      <td>shi</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Unresectable, advanc...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>NCT04745988</td>\n",
+       "      <td>An Open Label Phase 2 Study to Evaluate the Sa...</td>\n",
+       "      <td>2025-08</td>\n",
+       "      <td>Gastric Cancer</td>\n",
+       "      <td>This study is an open label phase 2 study to e...</td>\n",
+       "      <td>Kashiwa</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Have gastric and gas...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>NCT06038578</td>\n",
+       "      <td>A Study of TRK-950 When Used in Combination Wi...</td>\n",
+       "      <td>2025-08-31</td>\n",
+       "      <td>Gastric Adenocarcinoma, Gastric Cancer, Gastro...</td>\n",
+       "      <td>This study will assess the efficacy, safety, o...</td>\n",
+       "      <td>Chuo Ku, Kashiwa, Ku</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Histologically or cyt...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>NCT05322577</td>\n",
+       "      <td>A Study Evaluating Bemarituzumab in Combinatio...</td>\n",
+       "      <td>2026-03-17</td>\n",
+       "      <td>Gastric Cancer, Gastroesophageal Junction Cancer</td>\n",
+       "      <td>The main objectives of this study are to evalu...</td>\n",
+       "      <td>Shi, gun, ku, shi</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Adults with unresecta...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>NCT05152147</td>\n",
+       "      <td>A Study of Zanidatamab in Combination With Che...</td>\n",
+       "      <td>2024-12-31</td>\n",
+       "      <td>Gastric Neoplasms, Gastroesophageal Adenocarci...</td>\n",
+       "      <td>This study is being done to find out if zanida...</td>\n",
+       "      <td>Cho, Chuo Ku, Hirakata, Ina, Ku, Matsuyama, Na...</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Histologically confir...</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          NCTID                                              Title  \\\n",
+       "0   NCT03505320  A Study of Zolbetuximab (IMAB362) in Adults Wi...   \n",
+       "1   NCT05002127  A Study of Evorpacept (ALX148) in Patients wit...   \n",
+       "2   NCT05365581  A Study of ASP2138 Given by Itself or Given Wi...   \n",
+       "3   NCT05111626  Bemarituzumab Plus Chemotherapy and Nivolumab ...   \n",
+       "4   NCT06324357  Beamion BCGC-1: A Study to Find a Suitable Dos...   \n",
+       "5   NCT06056024  A Study to Test How Well Different Doses of BI...   \n",
+       "6   NCT04379596  Ph1b/2 Study of the Safety and Efficacy of T-D...   \n",
+       "7   NCT00197470    Cytokine Gene Polymorphisms in Gastric Diseases   \n",
+       "8   NCT05205343  Trans-Pacific Multicenter Collaborative Study ...   \n",
+       "9   NCT06490055  Predicting the Efficacy in Advanced Gastric Ca...   \n",
+       "10  NCT06490159  Predicting Peripheral Neuropathy of Paclitaxel...   \n",
+       "11  NCT05438459  GAIA-102 Intraperitoneal Administration in Pat...   \n",
+       "12  NCT04745988  An Open Label Phase 2 Study to Evaluate the Sa...   \n",
+       "13  NCT06038578  A Study of TRK-950 When Used in Combination Wi...   \n",
+       "14  NCT05322577  A Study Evaluating Bemarituzumab in Combinatio...   \n",
+       "15  NCT05152147  A Study of Zanidatamab in Combination With Che...   \n",
+       "\n",
+       "   Primary Completion Date                                             Cancer  \\\n",
+       "0               2025-04-30  Pharmacokinetics of Zolbetuximab, Gastric Canc...   \n",
+       "1                  2026-07  Gastric Cancer, Gastroesophageal Junction Aden...   \n",
+       "2               2026-10-31  Gastric Adenocarcinoma, Gastroesophageal Junct...   \n",
+       "3               2026-09-26  Gastric Cancer, Gastroesophageal Junction Aden...   \n",
+       "4               2027-02-22  Metastatic Breast Cancer, Metastatic Gastric A...   \n",
+       "5               2027-05-26                         Solid Tumor, KRAS Mutation   \n",
+       "6               2026-07-30                                     Gastric Cancer   \n",
+       "7             Unknown Date      Gastric Ulcer, Duodenal Ulcer, Gastric Cancer   \n",
+       "8               2026-05-31      Gastrostomy, Gastric, GastroEsophageal Cancer   \n",
+       "9               2025-12-31  Gastric Cancer, Chemotherapy Effect, Paclitaxe...   \n",
+       "10              2025-12-31  Gastric Cancer, Chemotherapy-induced Periphera...   \n",
+       "11              2026-12-31                  Gastric Cancer, Pancreatic Cancer   \n",
+       "12                 2025-08                                     Gastric Cancer   \n",
+       "13              2025-08-31  Gastric Adenocarcinoma, Gastric Cancer, Gastro...   \n",
+       "14              2026-03-17   Gastric Cancer, Gastroesophageal Junction Cancer   \n",
+       "15              2024-12-31  Gastric Neoplasms, Gastroesophageal Adenocarci...   \n",
+       "\n",
+       "                                              Summary  \\\n",
+       "0   Zolbetuximab is being studied as a treatment f...   \n",
+       "1   A Phase 2/3 Study of Evorpacept (ALX148) in Co...   \n",
+       "2   Claudin 18.2 protein, or CLDN18.2 is a protein...   \n",
+       "3   The main objective of Part 1 is to evaluate th...   \n",
+       "4   This study is open to adults aged 18 years and...   \n",
+       "5   This study is open to adults with advanced can...   \n",
+       "6   DESTINY-Gastric03 will investigate the safety,...   \n",
+       "7   Recently, cytokine polymorphisms are considere...   \n",
+       "8   To compare the symptoms of patients who have a...   \n",
+       "9   With advances in chemotherapy for gastric canc...   \n",
+       "10  Although advances in chemotherapy have improve...   \n",
+       "11  Phase I Part :\\n\\nConfirm the safety of GAIA-1...   \n",
+       "12  This study is an open label phase 2 study to e...   \n",
+       "13  This study will assess the efficacy, safety, o...   \n",
+       "14  The main objectives of this study are to evalu...   \n",
+       "15  This study is being done to find out if zanida...   \n",
+       "\n",
+       "                                    Japanes Locations  \\\n",
+       "0                                        Chiba, Tokyo   \n",
+       "1   Chiba, Fukuoka, Gifu, Kumamoto, Kyoto, Nagasak...   \n",
+       "2   Kashiwa, Nagoya, Osakasayama, Suita, Yokohama, ku   \n",
+       "3                               Sapporo, gun, ku, shi   \n",
+       "4                                             ku, shi   \n",
+       "5                                         Kashiwa, ku   \n",
+       "6                               Kashiwa, gun, ku, shi   \n",
+       "7                                           Hamamatsu   \n",
+       "8                                               Tokyo   \n",
+       "9                                           Kurashiki   \n",
+       "10                                          Kurashiki   \n",
+       "11                                                shi   \n",
+       "12                                            Kashiwa   \n",
+       "13                               Chuo Ku, Kashiwa, Ku   \n",
+       "14                                  Shi, gun, ku, shi   \n",
+       "15  Cho, Chuo Ku, Hirakata, Ina, Ku, Matsuyama, Na...   \n",
+       "\n",
+       "                                 Eligibility Criteria AgentJudgment AgentGrade  \n",
+       "0   Inclusion Criteria:\\n\\n* Female subject eligib...          None       None  \n",
+       "1   Inclusion Criteria:\\n\\n* HER2-overexpressing a...          None       None  \n",
+       "2   Inclusion Criteria:\\n\\n* Participant is consid...          None       None  \n",
+       "3   Inclusion Criteria Part 1 and Part 2:\\n\\n* Adu...          None       None  \n",
+       "4   Inclusion Criteria:\\n\\n* Signed and dated writ...          None       None  \n",
+       "5   Inclusion Criteria:\\n\\n1. Patients with pathol...          None       None  \n",
+       "6   Inclusion criteria:\\n\\n1. Male and female part...          None       None  \n",
+       "7   Inclusion Criteria:\\n\\n-\\n\\nExclusion Criteria...          None       None  \n",
+       "8   Inclusion Criteria:\\n\\n1. Able to speak and re...          None       None  \n",
+       "9   Inclusion Criteria:\\n\\n1. unresectable or recu...          None       None  \n",
+       "10  Inclusion Criteria:\\n\\n1. unresectable or recu...          None       None  \n",
+       "11  Inclusion Criteria:\\n\\n1. Unresectable, advanc...          None       None  \n",
+       "12  Inclusion Criteria:\\n\\n1. Have gastric and gas...          None       None  \n",
+       "13  Inclusion Criteria:\\n\\n* Histologically or cyt...          None       None  \n",
+       "14  Inclusion Criteria:\\n\\n* Adults with unresecta...          None       None  \n",
+       "15  Inclusion Criteria:\\n\\n* Histologically confir...          None       None  "
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "#Define agents\n",
+    "#modifier = QuestionModifierEnglish(groq)\n",
+    "CriteriaCheckAgent = SimpleClinicalTrialAgent(groq)\n",
+    "grader_agent = GraderAgent(groq)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The patient is not eligible for this clinical trial because the inclusion criteria specify that female subjects are eligible, and the patient is a 65-year-old male.\n",
+      "no\n",
+      "The patient is eligible for this clinical trial based on the provided information, as he has a measurable and biopsiable tumor with a known HER2 gene mutation, which meets the inclusion criteria. However, I do not know if he has progressed on or after a prior HER2-directed agent and fluoropyrimidine- or platinum-containing chemotherapy, which is also required for inclusion.\n",
+      "unclear\n",
+      "The patient is eligible for this clinical trial based on the provided criteria. The patient meets the inclusion criteria, including having a measurable tumor, being at least 18 years old, and having a predicted life expectancy of at least 12 weeks. The patient also has histologically confirmed gastric/gastroesophageal junction (GEJ) adenocarcinoma, which is one of the specified disease types for this trial. Additionally, the patient has a HER2-positive tumor, which is not an exclusion criterion for this trial.\n",
+      "yes\n",
+      "The patient is eligible for this clinical trial based on the provided criteria, as they meet the inclusion criteria for age, measurable tumor, and biopsiable tumor. However, the patient's HER2 status is known to be positive, which is an exclusion criterion. Therefore, the patient is not eligible for this clinical trial.\n",
+      "no\n",
+      "The patient is not eligible for this clinical trial because the trial is for metastatic breast cancer (mBC) or metastatic gastric adenocarcinoma, gastroesophageal junction adenocarcinoma, or esophageal adenocarcinoma (mGEAC), and the patient has gastric cancer, which is not specified as an eligible type of cancer.\n",
+      "no\n",
+      "The patient is not eligible for this clinical trial because the trial requires a KRAS wild type (wt) amplification or a KRAS G12V mutation, but the patient has a HER2 gene mutation.\n",
+      "no\n",
+      "The patient is eligible for this clinical trial based on the provided criteria, as they meet the inclusion criteria (age, disease characteristics, measurable tumor, and HER2-positive status) and do not have any of the exclusion criteria mentioned.\n",
+      "yes\n",
+      "I do not know if the patient is eligible for this clinical trial because the criteria do not mention age or specific types of cancer, and there is no information about H. pylori status in the patient.\n",
+      "unclear\n",
+      "The patient is eligible for this clinical trial based on the provided criteria, as he has a biopsy-confirmed diagnosis of gastric cancer, is 65 years old (meeting the age criterion), and there is no mention of any exclusion criteria being met.\n",
+      "yes\n",
+      "The patient is eligible for this clinical trial based on the provided information, as he meets the inclusion criteria (age, measurable tumor, biopsiable tumor, and gastric cancer diagnosis) and does not appear to meet any of the exclusion criteria.\n",
+      "yes\n",
+      "The patient is eligible for this clinical trial based on the provided criteria, as they meet the inclusion criteria (age, measurable tumor, biopsiable tumor, and gastric cancer diagnosis) and do not have any of the listed exclusion criteria.\n",
+      "yes\n",
+      "Based on the provided criteria, the 65-year-old male patient with gastric cancer and a known HER2 gene mutation appears to be eligible for this clinical trial, as he meets the inclusion criteria (e.g., unresectable advanced gastric cancer, measurable tumor, biopsiable tumor, etc.) and does not have any obvious exclusion criteria mentioned. However, I would need to review the patient's full medical history and current condition to confirm eligibility.\n",
+      "unclear\n",
+      "The patient is eligible for this clinical trial based on the provided criteria, as they meet the inclusion criteria (gastric cancer, measurable tumor, biopsiable tumor, age ≥ 20, etc.) and do not have any of the exclusion criteria mentioned.\n",
+      "yes\n",
+      "The patient is not eligible for this clinical trial because the patient has a known HER2 gene mutation, and the exclusion criteria specify that patients with HER2 positive gastric or GEJ adenocarcinoma are not eligible.\n",
+      "no\n",
+      "The patient is not eligible for this clinical trial because they have a known HER2 gene mutation, which is an exclusion criterion.\n",
+      "no\n",
+      "Based on the provided information, the 65-year-old male patient with gastric cancer and a known HER2 gene mutation appears to be eligible for this clinical trial, as he meets the inclusion criteria of having measurable tumor and biopsiable tumor, and there is no mention of any exclusion criteria that would disqualify him.\n",
+      "yes\n"
+     ]
+    }
+   ],
+   "source": [
+    "for nct_id in NCTIDs:\n",
+    "    TargetCriteria = df.loc[df['NCTID'] == nct_id, 'Eligibility Criteria'].values[0]\n",
+    "    AgentJudgment = CriteriaCheckAgent.evaluate_eligibility(TargetCriteria, ex_question)\n",
+    "    print(AgentJudgment)\n",
+    "\n",
+    "    AgentGrade = grader_agent.evaluate_eligibility(AgentJudgment)\n",
+    "    print(AgentGrade)\n",
+    "    # NCTIDに一致する行を見つけて更新\n",
+    "    df.loc[df['NCTID'] == nct_id, 'AgentJudgment'] = AgentJudgment\n",
+    "    df.loc[df['NCTID'] == nct_id, 'AgentGrade'] = AgentGrade\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>NCTID</th>\n",
+       "      <th>Title</th>\n",
+       "      <th>Primary Completion Date</th>\n",
+       "      <th>Cancer</th>\n",
+       "      <th>Summary</th>\n",
+       "      <th>Japanes Locations</th>\n",
+       "      <th>Eligibility Criteria</th>\n",
+       "      <th>AgentJudgment</th>\n",
+       "      <th>AgentGrade</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NCT03505320</td>\n",
+       "      <td>A Study of Zolbetuximab (IMAB362) in Adults Wi...</td>\n",
+       "      <td>2025-04-30</td>\n",
+       "      <td>Pharmacokinetics of Zolbetuximab, Gastric Canc...</td>\n",
+       "      <td>Zolbetuximab is being studied as a treatment f...</td>\n",
+       "      <td>Chiba, Tokyo</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Female subject eligib...</td>\n",
+       "      <td>The patient is not eligible for this clinical ...</td>\n",
+       "      <td>no</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NCT05002127</td>\n",
+       "      <td>A Study of Evorpacept (ALX148) in Patients wit...</td>\n",
+       "      <td>2026-07</td>\n",
+       "      <td>Gastric Cancer, Gastroesophageal Junction Aden...</td>\n",
+       "      <td>A Phase 2/3 Study of Evorpacept (ALX148) in Co...</td>\n",
+       "      <td>Chiba, Fukuoka, Gifu, Kumamoto, Kyoto, Nagasak...</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* HER2-overexpressing a...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>unclear</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NCT05365581</td>\n",
+       "      <td>A Study of ASP2138 Given by Itself or Given Wi...</td>\n",
+       "      <td>2026-10-31</td>\n",
+       "      <td>Gastric Adenocarcinoma, Gastroesophageal Junct...</td>\n",
+       "      <td>Claudin 18.2 protein, or CLDN18.2 is a protein...</td>\n",
+       "      <td>Kashiwa, Nagoya, Osakasayama, Suita, Yokohama, ku</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Participant is consid...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>NCT05111626</td>\n",
+       "      <td>Bemarituzumab Plus Chemotherapy and Nivolumab ...</td>\n",
+       "      <td>2026-09-26</td>\n",
+       "      <td>Gastric Cancer, Gastroesophageal Junction Aden...</td>\n",
+       "      <td>The main objective of Part 1 is to evaluate th...</td>\n",
+       "      <td>Sapporo, gun, ku, shi</td>\n",
+       "      <td>Inclusion Criteria Part 1 and Part 2:\\n\\n* Adu...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>no</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>NCT06324357</td>\n",
+       "      <td>Beamion BCGC-1: A Study to Find a Suitable Dos...</td>\n",
+       "      <td>2027-02-22</td>\n",
+       "      <td>Metastatic Breast Cancer, Metastatic Gastric A...</td>\n",
+       "      <td>This study is open to adults aged 18 years and...</td>\n",
+       "      <td>ku, shi</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Signed and dated writ...</td>\n",
+       "      <td>The patient is not eligible for this clinical ...</td>\n",
+       "      <td>no</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>NCT06056024</td>\n",
+       "      <td>A Study to Test How Well Different Doses of BI...</td>\n",
+       "      <td>2027-05-26</td>\n",
+       "      <td>Solid Tumor, KRAS Mutation</td>\n",
+       "      <td>This study is open to adults with advanced can...</td>\n",
+       "      <td>Kashiwa, ku</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Patients with pathol...</td>\n",
+       "      <td>The patient is not eligible for this clinical ...</td>\n",
+       "      <td>no</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>NCT04379596</td>\n",
+       "      <td>Ph1b/2 Study of the Safety and Efficacy of T-D...</td>\n",
+       "      <td>2026-07-30</td>\n",
+       "      <td>Gastric Cancer</td>\n",
+       "      <td>DESTINY-Gastric03 will investigate the safety,...</td>\n",
+       "      <td>Kashiwa, gun, ku, shi</td>\n",
+       "      <td>Inclusion criteria:\\n\\n1. Male and female part...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>NCT00197470</td>\n",
+       "      <td>Cytokine Gene Polymorphisms in Gastric Diseases</td>\n",
+       "      <td>Unknown Date</td>\n",
+       "      <td>Gastric Ulcer, Duodenal Ulcer, Gastric Cancer</td>\n",
+       "      <td>Recently, cytokine polymorphisms are considere...</td>\n",
+       "      <td>Hamamatsu</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n-\\n\\nExclusion Criteria...</td>\n",
+       "      <td>I do not know if the patient is eligible for t...</td>\n",
+       "      <td>unclear</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>NCT05205343</td>\n",
+       "      <td>Trans-Pacific Multicenter Collaborative Study ...</td>\n",
+       "      <td>2026-05-31</td>\n",
+       "      <td>Gastrostomy, Gastric, GastroEsophageal Cancer</td>\n",
+       "      <td>To compare the symptoms of patients who have a...</td>\n",
+       "      <td>Tokyo</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Able to speak and re...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>NCT06490055</td>\n",
+       "      <td>Predicting the Efficacy in Advanced Gastric Ca...</td>\n",
+       "      <td>2025-12-31</td>\n",
+       "      <td>Gastric Cancer, Chemotherapy Effect, Paclitaxe...</td>\n",
+       "      <td>With advances in chemotherapy for gastric canc...</td>\n",
+       "      <td>Kurashiki</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. unresectable or recu...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>NCT06490159</td>\n",
+       "      <td>Predicting Peripheral Neuropathy of Paclitaxel...</td>\n",
+       "      <td>2025-12-31</td>\n",
+       "      <td>Gastric Cancer, Chemotherapy-induced Periphera...</td>\n",
+       "      <td>Although advances in chemotherapy have improve...</td>\n",
+       "      <td>Kurashiki</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. unresectable or recu...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>NCT05438459</td>\n",
+       "      <td>GAIA-102 Intraperitoneal Administration in Pat...</td>\n",
+       "      <td>2026-12-31</td>\n",
+       "      <td>Gastric Cancer, Pancreatic Cancer</td>\n",
+       "      <td>Phase I Part :\\n\\nConfirm the safety of GAIA-1...</td>\n",
+       "      <td>shi</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Unresectable, advanc...</td>\n",
+       "      <td>Based on the provided criteria, the 65-year-ol...</td>\n",
+       "      <td>unclear</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>NCT04745988</td>\n",
+       "      <td>An Open Label Phase 2 Study to Evaluate the Sa...</td>\n",
+       "      <td>2025-08</td>\n",
+       "      <td>Gastric Cancer</td>\n",
+       "      <td>This study is an open label phase 2 study to e...</td>\n",
+       "      <td>Kashiwa</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n1. Have gastric and gas...</td>\n",
+       "      <td>The patient is eligible for this clinical tria...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>NCT06038578</td>\n",
+       "      <td>A Study of TRK-950 When Used in Combination Wi...</td>\n",
+       "      <td>2025-08-31</td>\n",
+       "      <td>Gastric Adenocarcinoma, Gastric Cancer, Gastro...</td>\n",
+       "      <td>This study will assess the efficacy, safety, o...</td>\n",
+       "      <td>Chuo Ku, Kashiwa, Ku</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Histologically or cyt...</td>\n",
+       "      <td>The patient is not eligible for this clinical ...</td>\n",
+       "      <td>no</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>NCT05322577</td>\n",
+       "      <td>A Study Evaluating Bemarituzumab in Combinatio...</td>\n",
+       "      <td>2026-03-17</td>\n",
+       "      <td>Gastric Cancer, Gastroesophageal Junction Cancer</td>\n",
+       "      <td>The main objectives of this study are to evalu...</td>\n",
+       "      <td>Shi, gun, ku, shi</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Adults with unresecta...</td>\n",
+       "      <td>The patient is not eligible for this clinical ...</td>\n",
+       "      <td>no</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>NCT05152147</td>\n",
+       "      <td>A Study of Zanidatamab in Combination With Che...</td>\n",
+       "      <td>2024-12-31</td>\n",
+       "      <td>Gastric Neoplasms, Gastroesophageal Adenocarci...</td>\n",
+       "      <td>This study is being done to find out if zanida...</td>\n",
+       "      <td>Cho, Chuo Ku, Hirakata, Ina, Ku, Matsuyama, Na...</td>\n",
+       "      <td>Inclusion Criteria:\\n\\n* Histologically confir...</td>\n",
+       "      <td>Based on the provided information, the 65-year...</td>\n",
+       "      <td>yes</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          NCTID                                              Title  \\\n",
+       "0   NCT03505320  A Study of Zolbetuximab (IMAB362) in Adults Wi...   \n",
+       "1   NCT05002127  A Study of Evorpacept (ALX148) in Patients wit...   \n",
+       "2   NCT05365581  A Study of ASP2138 Given by Itself or Given Wi...   \n",
+       "3   NCT05111626  Bemarituzumab Plus Chemotherapy and Nivolumab ...   \n",
+       "4   NCT06324357  Beamion BCGC-1: A Study to Find a Suitable Dos...   \n",
+       "5   NCT06056024  A Study to Test How Well Different Doses of BI...   \n",
+       "6   NCT04379596  Ph1b/2 Study of the Safety and Efficacy of T-D...   \n",
+       "7   NCT00197470    Cytokine Gene Polymorphisms in Gastric Diseases   \n",
+       "8   NCT05205343  Trans-Pacific Multicenter Collaborative Study ...   \n",
+       "9   NCT06490055  Predicting the Efficacy in Advanced Gastric Ca...   \n",
+       "10  NCT06490159  Predicting Peripheral Neuropathy of Paclitaxel...   \n",
+       "11  NCT05438459  GAIA-102 Intraperitoneal Administration in Pat...   \n",
+       "12  NCT04745988  An Open Label Phase 2 Study to Evaluate the Sa...   \n",
+       "13  NCT06038578  A Study of TRK-950 When Used in Combination Wi...   \n",
+       "14  NCT05322577  A Study Evaluating Bemarituzumab in Combinatio...   \n",
+       "15  NCT05152147  A Study of Zanidatamab in Combination With Che...   \n",
+       "\n",
+       "   Primary Completion Date                                             Cancer  \\\n",
+       "0               2025-04-30  Pharmacokinetics of Zolbetuximab, Gastric Canc...   \n",
+       "1                  2026-07  Gastric Cancer, Gastroesophageal Junction Aden...   \n",
+       "2               2026-10-31  Gastric Adenocarcinoma, Gastroesophageal Junct...   \n",
+       "3               2026-09-26  Gastric Cancer, Gastroesophageal Junction Aden...   \n",
+       "4               2027-02-22  Metastatic Breast Cancer, Metastatic Gastric A...   \n",
+       "5               2027-05-26                         Solid Tumor, KRAS Mutation   \n",
+       "6               2026-07-30                                     Gastric Cancer   \n",
+       "7             Unknown Date      Gastric Ulcer, Duodenal Ulcer, Gastric Cancer   \n",
+       "8               2026-05-31      Gastrostomy, Gastric, GastroEsophageal Cancer   \n",
+       "9               2025-12-31  Gastric Cancer, Chemotherapy Effect, Paclitaxe...   \n",
+       "10              2025-12-31  Gastric Cancer, Chemotherapy-induced Periphera...   \n",
+       "11              2026-12-31                  Gastric Cancer, Pancreatic Cancer   \n",
+       "12                 2025-08                                     Gastric Cancer   \n",
+       "13              2025-08-31  Gastric Adenocarcinoma, Gastric Cancer, Gastro...   \n",
+       "14              2026-03-17   Gastric Cancer, Gastroesophageal Junction Cancer   \n",
+       "15              2024-12-31  Gastric Neoplasms, Gastroesophageal Adenocarci...   \n",
+       "\n",
+       "                                              Summary  \\\n",
+       "0   Zolbetuximab is being studied as a treatment f...   \n",
+       "1   A Phase 2/3 Study of Evorpacept (ALX148) in Co...   \n",
+       "2   Claudin 18.2 protein, or CLDN18.2 is a protein...   \n",
+       "3   The main objective of Part 1 is to evaluate th...   \n",
+       "4   This study is open to adults aged 18 years and...   \n",
+       "5   This study is open to adults with advanced can...   \n",
+       "6   DESTINY-Gastric03 will investigate the safety,...   \n",
+       "7   Recently, cytokine polymorphisms are considere...   \n",
+       "8   To compare the symptoms of patients who have a...   \n",
+       "9   With advances in chemotherapy for gastric canc...   \n",
+       "10  Although advances in chemotherapy have improve...   \n",
+       "11  Phase I Part :\\n\\nConfirm the safety of GAIA-1...   \n",
+       "12  This study is an open label phase 2 study to e...   \n",
+       "13  This study will assess the efficacy, safety, o...   \n",
+       "14  The main objectives of this study are to evalu...   \n",
+       "15  This study is being done to find out if zanida...   \n",
+       "\n",
+       "                                    Japanes Locations  \\\n",
+       "0                                        Chiba, Tokyo   \n",
+       "1   Chiba, Fukuoka, Gifu, Kumamoto, Kyoto, Nagasak...   \n",
+       "2   Kashiwa, Nagoya, Osakasayama, Suita, Yokohama, ku   \n",
+       "3                               Sapporo, gun, ku, shi   \n",
+       "4                                             ku, shi   \n",
+       "5                                         Kashiwa, ku   \n",
+       "6                               Kashiwa, gun, ku, shi   \n",
+       "7                                           Hamamatsu   \n",
+       "8                                               Tokyo   \n",
+       "9                                           Kurashiki   \n",
+       "10                                          Kurashiki   \n",
+       "11                                                shi   \n",
+       "12                                            Kashiwa   \n",
+       "13                               Chuo Ku, Kashiwa, Ku   \n",
+       "14                                  Shi, gun, ku, shi   \n",
+       "15  Cho, Chuo Ku, Hirakata, Ina, Ku, Matsuyama, Na...   \n",
+       "\n",
+       "                                 Eligibility Criteria  \\\n",
+       "0   Inclusion Criteria:\\n\\n* Female subject eligib...   \n",
+       "1   Inclusion Criteria:\\n\\n* HER2-overexpressing a...   \n",
+       "2   Inclusion Criteria:\\n\\n* Participant is consid...   \n",
+       "3   Inclusion Criteria Part 1 and Part 2:\\n\\n* Adu...   \n",
+       "4   Inclusion Criteria:\\n\\n* Signed and dated writ...   \n",
+       "5   Inclusion Criteria:\\n\\n1. Patients with pathol...   \n",
+       "6   Inclusion criteria:\\n\\n1. Male and female part...   \n",
+       "7   Inclusion Criteria:\\n\\n-\\n\\nExclusion Criteria...   \n",
+       "8   Inclusion Criteria:\\n\\n1. Able to speak and re...   \n",
+       "9   Inclusion Criteria:\\n\\n1. unresectable or recu...   \n",
+       "10  Inclusion Criteria:\\n\\n1. unresectable or recu...   \n",
+       "11  Inclusion Criteria:\\n\\n1. Unresectable, advanc...   \n",
+       "12  Inclusion Criteria:\\n\\n1. Have gastric and gas...   \n",
+       "13  Inclusion Criteria:\\n\\n* Histologically or cyt...   \n",
+       "14  Inclusion Criteria:\\n\\n* Adults with unresecta...   \n",
+       "15  Inclusion Criteria:\\n\\n* Histologically confir...   \n",
+       "\n",
+       "                                        AgentJudgment AgentGrade  \n",
+       "0   The patient is not eligible for this clinical ...         no  \n",
+       "1   The patient is eligible for this clinical tria...    unclear  \n",
+       "2   The patient is eligible for this clinical tria...        yes  \n",
+       "3   The patient is eligible for this clinical tria...         no  \n",
+       "4   The patient is not eligible for this clinical ...         no  \n",
+       "5   The patient is not eligible for this clinical ...         no  \n",
+       "6   The patient is eligible for this clinical tria...        yes  \n",
+       "7   I do not know if the patient is eligible for t...    unclear  \n",
+       "8   The patient is eligible for this clinical tria...        yes  \n",
+       "9   The patient is eligible for this clinical tria...        yes  \n",
+       "10  The patient is eligible for this clinical tria...        yes  \n",
+       "11  Based on the provided criteria, the 65-year-ol...    unclear  \n",
+       "12  The patient is eligible for this clinical tria...        yes  \n",
+       "13  The patient is not eligible for this clinical ...         no  \n",
+       "14  The patient is not eligible for this clinical ...         no  \n",
+       "15  Based on the provided information, the 65-year...        yes  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.to_csv('./65yerProstateCancer.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "gradio",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

dev/GraphAppDev7.ipynb

@@ -0,0 +1,124 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/satoc/miniforge3/envs/gradio/lib/python3.12/site-packages/IPython/core/interactiveshell.py:3577: LangChainDeprecationWarning: As of langchain-core 0.3.0, LangChain uses pydantic v2 internally. The langchain_core.pydantic_v1 module was a compatibility shim for pydantic v1, and should no longer be used. Please update the code to import from Pydantic directly.\n",
+      "\n",
+      "For example, replace imports like: `from langchain_core.pydantic_v1 import BaseModel`\n",
+      "with: `from pydantic import BaseModel`\n",
+      "or the v1 compatibility namespace if you are working in a code base that has not been fully upgraded to pydantic 2 yet. \tfrom pydantic.v1 import BaseModel\n",
+      "\n",
+      "  exec(code_obj, self.user_global_ns, self.user_ns)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain_community.agent_toolkits import create_sql_agent\n",
+    "from langchain_openai import ChatOpenAI\n",
+    "from langchain_groq import ChatGroq\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
+    "import pandas as pd\n",
+    "from pydantic import BaseModel, Field\n",
+    "\n",
+    "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
+    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.embeddings import HuggingFaceEmbeddings\n",
+    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "\n",
+    "\n",
+    "gpt = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n",
+    "#agent_gpt_executor = create_sql_agent(gpt, db=db, agent_type=\"tool-calling\", verbose=True)\n",
+    "\n",
+    "## make database\n",
+    "from langchain_community.utilities import SQLDatabase\n",
+    "from sqlalchemy import create_engine\n",
+    "\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema import SystemMessage\n",
+    "from langchain_core.prompts import MessagesPlaceholder\n",
+    "#agent_groq_executor = create_sql_agent(llm, db=db, agent_type=\"tool-calling\", verbose=True)\n",
+    "\n",
+    "from OpenAITools.FetchTools import fetch_clinical_trials, fetch_clinical_trials_jp\n",
+    "from OpenAITools.CrinicalTrialTools import QuestionModifierEnglish, TumorNameExtractor, SimpleClinicalTrialAgent,GraderAgent,LLMTranslator\n",
+    "\n",
+    "groq = ChatGroq(model_name=\"llama3-70b-8192\", temperature=0)\n",
+    "#agent_groq_executor = create_sql_agent(groq, db=db, agent_type=\"tool-calling\", verbose=True)\n",
+    "\n",
+    "age = \"65\"\n",
+    "sex =\"男性\"\n",
+    "tumor_type =\"胃癌\"\n",
+    "#tumor_type = \"gastric cancer\"\n",
+    "GeneMutation =\"HER2\"\n",
+    "Meseable = \"有り\"\n",
+    "Biopsiable = \"有り\"\n",
+    "NCTID = 'NCT06441994'\n",
+    "\n",
+    "#Define extractor\n",
+    "Translator = LLMTranslator(groq)\n",
+    "TumorName = Translator.translate(tumor_type)\n",
+    "\n",
+    "#Make db\n",
+    "df = fetch_clinical_trials(TumorName)\n",
+    "# 新しい列を追加\n",
+    "df['AgentJudgment'] = None\n",
+    "df['AgentGrade'] = None\n",
+    "#df = df.iloc[:5, :]\n",
+    "NCTIDs = list(df['NCTID' ])\n",
+    "\n",
+    "#Define agents\n",
+    "#modifier = QuestionModifierEnglish(groq)\n",
+    "CriteriaCheckAgent = SimpleClinicalTrialAgent(groq)\n",
+    "grader_agent = GraderAgent(groq)\n",
+    "\n",
+    "\n",
+    "for nct_id in NCTIDs:\n",
+    "    TargetCriteria = df.loc[df['NCTID'] == nct_id, 'Eligibility Criteria'].values[0]\n",
+    "    AgentJudgment = CriteriaCheckAgent.evaluate_eligibility(TargetCriteria, ex_question)\n",
+    "    print(AgentJudgment)\n",
+    "\n",
+    "    AgentGrade = grader_agent.evaluate_eligibility(AgentJudgment)\n",
+    "    print(AgentGrade)\n",
+    "    # NCTIDに一致する行を見つけて更新\n",
+    "    df.loc[df['NCTID'] == nct_id, 'AgentJudgment'] = AgentJudgment\n",
+    "    df.loc[df['NCTID'] == nct_id, 'AgentGrade'] = AgentGrade"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "gradio",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

dev/filtered_data.csv

@@ -1,59 +1,46 @@
 NCTID,AgentGrade,Title,AgentJudgment,Japanes Locations,Primary Completion Date,Cancer,Summary,Eligibility Criteria
-NCT03423628,yes,A Study to Assess the Safety and Tolerability of AZD1390 Given With Radiation Therapy in Patients With Brain Cancer,"Based on the provided criteria, the 30-year-old male patient with glioblastoma is eligible for this clinical trial, specifically for Arm A or Arm C, as he meets the inclusion criteria for histologically proven diagnosis of GBM and Karnofsky Performance Score of ≥60.","ku, shi",2026-04-22,"Recurrent Glioblastoma Multiforme, Primary Glioblastoma Multiforme, Brain Neoplasms, Malignant, Leptomeningeal Disease (LMD)","This study will test an investigational drug called AZD1390 in combination with radiation therapy for the treatment of brain tumors. This is the first time AZD1390 is being given to patients. This study will test safety, tolerability and PK (how the drug is absorbed, distributed and eliminated) of ascending doses of AZD1390 in combination with distinct regimens of radiation therapy","Inclusion Criteria:
+NCT05580562,unclear,ONC201 in H3 K27M-mutant Diffuse Glioma Following Radiotherapy (the ACTION Study),"Based on the provided criteria, the 40-year-old male patient with glioma and a known H3 K27M gene mutation, measurable and biopsiable tumor, may be eligible for this clinical trial. However, I do not know if the patient has received frontline radiotherapy, has a Karnofsky Performance Status or Lansky Performance Status ≥ 70, and meets the other inclusion and exclusion criteria. Further evaluation is needed to determine the patient's eligibility.","Chuo City, Osaka",2026-08,"H3 K27M, Glioma","This is a randomized, double-blind, placebo-controlled, parallel-group, international, Phase 3 study in patients with newly diagnosed H3 K27M-mutant diffuse glioma to assess whether treatment with ONC201 following frontline radiotherapy will extend overall survival and progression-free survival in this population. Eligible participants will have histologically diagnosed H3 K27M-mutant diffuse glioma and have completed standard frontline radiotherapy.","Inclusion Criteria:
 
-* Provision of formalin-fixed paraffin embedded tissue sample from primary or metastatic disease
-* Karnofsky Performance Score of ≥60.
-* Additional Inclusion Criteria Specific for Arm A and Japan:
+1. Able to understand the study procedures and agree to participate in the study by providing written informed consent (by participant or legally authorized representative), and assent when applicable.
+2. Body weight ≥ 10 kg at time of randomization.
+3. Histologically diagnosed H3 K27M-mutant diffuse glioma (new diagnosis). Detection of a missense K27M mutation in any histone H3-encoding gene detected by testing of tumor tissue (immunohistochemistry \[IHC\] or next-generation sequencing \[NGS\] in a Clinical Laboratory Improvement Amendments \[CLIA\]-certified or equivalent laboratory). \[Site to provide (as available): ≥ 10 unstained formalin-fixed paraffin-embedded (FFPE) slides from tumor tissue.\]
+4. At least one, high-quality, contrast-enhanced MRI of the brain obtained prior to starting radiotherapy for submission to sponsor's imaging vendor for central read. For participants who had a surgical resection, this scan must be post-resection; for participants who did not have a resection, this scan may be pre- or post-biopsy.
+5. At least one, high-quality, contrast-enhanced MRI of the brain obtained 2 to 6 weeks after completion of frontline radiotherapy. If unable to obtain contrast-enhanced imaging due to lack of venous access after multiple attempts, a patient may still be eligible after collection of a nonenhanced MRI of the brain. \[Site to also provide all available MRIs completed prior to initiating treatment with study intervention.\]
+6. Received frontline radiotherapy
 
-  * Histologically proven diagnosis of GBM. Patients who have had RT for low-grade glioma (LGG) or grade 3 glioma and have subsequently relapsed to histologically confirmed GBM can be considered
-  * A radiological diagnosis of recurrent/relapsed or progressive disease according to RANO criteria.
-  * Completion of first-line radiation at least 6 months prior to Cycle 1 Day 1.
-  * Patients with tumor-induced seizures must be well controlled on a stable anti-epileptic treatment
-  * Willing to receive anti-epileptic prophylaxis for the duration of study drug administration.
-* Additional Inclusion Criteria Specific for Arm B:
-
-\*\*Arm B has now closed to recruitment\*\*
-
-* Histologically proven diagnosis of solid tumor malignancy and Magnetic Resonance (MR) imaging documenting brain lesions.
-* Not eligible for Stereotactic Radiosurgery (SRS) treatment of brain tumor.
-* Patient has not received any previous brain RT to the area that is to be irradiated. Prior PBRT may be allowed if there is not significant overlap between the prior and new radiation fields.
-* Non-CNS malignant disease must be sufficiently controlled so that patients can be without additional systemic therapy for the required washout period before starting therapy until 5 days after the end of RT. Required washout period before starting the first dose of AZD1390 (Cycle 1) is 28 days for immune checkpoint inhibitors and 7 days for all other agents
-* Not received radiation to the lung fields within the past 8 weeks.
-* No history of seizures related to the brain metastases or LMD.
-* Receiving PBRT (rather than WBRT) during Cycle 1 as standard of care for brain metastases
-
-  • Additional Inclusion Criteria Specific for Arm C:
-* Histologically proven primary diagnosis of GBM with unmethylated O6-methylguanine-DNA methyltransferase (MGMT). Grade 4 astrocytoma or histology with molecular features of GBM can be considered.
-* Determination of MGMT promoter status by methylation-specific polymerase chain reaction (PCR) or pyrosequencing per local institutional guidelines is required to assess eligibility for this Arm.
-* Patients will have to undergo mutational testing for Isocitrate dehydrogenase 1 (IDH1) on a tumor specimen before entering study. Patients are eligible for Arm C regardless of their IDH1 mutational status.
-* No history of uncontrolled seizures after surgery for primary GBM (despite adequate antiepileptic therapy) or with need for concurrent administration of more than 2 antiepileptic drugs.
-* Willing to receive anti-epileptic prophylaxis for the duration of study drug administration
-
-Additional Inclusion criteria for Food Effect Assessment (Arm A) (Not applicable for Japan part):
-
-* For the fed assessment portion: fast overnight (for at least 10 hours) prior to consuming a high-fat meal consisting of approximately 800 to 1000 calories, with around 54% of the calories coming from fat.
-* For the fasted assessment portion: fast overnight (for at least 10 hours prior to dosing) and until 4 hours after dosing.
-
-\*Note: the optional food effect assessment is currently not open to enrolment\*
+   1. Initiated radiotherapy within 12 weeks from the initial diagnosis of H3 K27M-mutant diffuse glioma.
+   2. Completed radiotherapy within 2 to 6 weeks prior to randomization
+   3. Completed standard fractionated radiotherapy (eg. 54 to 60 Gy in 28 to 33 fractions given over approximately 6 weeks or hypofractionated radiotherapy (eg. 40 Gy in 15 fractions given over approximately 3 weeks).
+7. Karnofsky Performance Status or Lansky Performance Status ≥ 70 at time of randomization.
+8. Stable or decreasing dose of corticosteroids and anti-seizure medications for 7 days prior to randomization, if applicable. Stable steroid dose is defined as ≤ 2 mg/day increase (based on dexamethasone dose or equivalent dose of an alternative steroid).
 
 Exclusion Criteria:
 
-* Administration of chemotherapy or any investigational drug in the 28 days or carmustine (CCNU) or lomustine (BCNU) in the 6 weeks prior to receiving the first dose of treatment in Arms A and C. Administration of checkpoint inhibitors within 28 days prior to first dose of treatment and any other agent within 7 days of beginning study treatment in Arm B. Hormonal therapies are allowed during study treatment for patients in Arm B.
-* History of severe brain-injury or stroke.
-* Patient not eligible for sequential MRI evaluations are not eligible for this study.
-* History of epileptic disorder or any seizure history unrelated to tumor
-* Treatment with Strong inhibitors or inducers of CYP3A4 within 2 weeks prior to receiving study drug
-* Concurrent therapy with other seizurogenic medications.
-* Past medical history of interstitial lung disease (ILD), drug-induced ILD, radiation pneumonitis which required steroid treatment, or any evidence of clinically active ILD.
-* Concurrent severe and/or uncontrolled medical condition (e.g., severe COPD).
-* Prior treatment with pneumotoxic drugs, e.g. busulfan, bleomycin, within the past year. If prior therapy in lifetime, then excluded if history of pulmonary toxicities from administration. Patients who have received treatment with nitrosoureas (e.g., carmustine, lomustine) in the year before study entry without experiencing lung toxicity are allowed on study.
-* History or presence of myopathy or raised creatine kinase (CK) \>5 x upper limit of normal (ULN) on 2 occasions at screening.
-* Cardiac dysfunction defined as: Myocardial infarction within six months of study entry, NYHA (New York Heart Association) Class II/III/IV heart failure, unstable angina, unstable cardiac arrhythmias
-* Evidence of severe pulmonary infections, as judged by the investigator (For Japan part only this includes active infection including tuberculosis, chronic active or uncontrolled Hep B or Hep C)
-* With the exception of alopecia, any unresolved toxicities from prior therapy greater than National Cancer Institute Common Terminology Criteria for Adverse Events (NCI CTCAE 4.03) Grade 1 at the time of starting study treatment and patients with chronic Grade 2 unresolved toxicities may be eligible Additional exclusion criteria for Arm A and Japan Part
-* Has previously received ATM inhibitor with concurrent RT
-
-Additional Exclusion criteria for Food Effect Assessment (Arm A) (Not applicable for the Japan Part):
-
-* Diabetes Type I, Type II, or steroid-induced diabetes.
-* Undergoing systemic steroid treatment \*Note: the optional food effect assessment is currently not open to enrolment\*"
+1. Primary spinal tumor.
+2. Diffuse intrinsic pontine glioma (DIPG), defined as tumors with a pontine epicenter and diffuse involvement of the pons.
+3. Evidence of leptomeningeal spread of disease or cerebrospinal fluid dissemination.
+4. Any known concurrent malignancy.
+5. New lesion(s) outside of the radiation field.
+6. Received whole-brain radiotherapy.
+7. Received proton therapy for glioma.
+8. Use of any of the following treatments within the specified time periods prior to randomization:
+
+   1. ONC201 or ONC206 at any time.
+   2. Systemic bevacizumab (includes biosimilars) at any time since the initial diagnosis of H3 K27M-mutant diffuse glioma.
+   3. Temozolomide within past 3 weeks.
+   4. Tumor treating fields at any time.
+   5. DRD2 antagonist within past 2 weeks.
+   6. Any investigational therapy within past 4 weeks.
+   7. Strong CYP3A4 inhibitors within 3 days.
+   8. Strong CYP3A4 inducers (includes enzyme-inducing antiepileptic drugs) within 2 weeks.
+9. Laboratory test results meeting any of the following parameters within 2 weeks prior to randomization:
+
+   1. Absolute neutrophil count \< 1.0 × 109/L or platelets \< 75 × 109/L.
+   2. Total bilirubin \> 1.5 × upper limit of normal (ULN) (participants with Gilbert's syndrome may be included with total bilirubin \> 1.5 × ULN if direct bilirubin is ≤ 1.5 × ULN).
+   3. Aspartate aminotransferase (AST) or alanine aminotransferase (ALT) \> 2.5 × ULN.
+   4. Creatinine clearance ≤ 60 mL/min as calculated by the Cockcroft Gault equation (or estimated glomerular filtration rate \< 60 mL/min/1.73 m2).
+10. QTc \> 480 msec (based on mean from triplicate electrocardiograms) during screening.
+11. Known hypersensitivity to any excipients used in the study intervention formulation.
+12. Pregnant, breastfeeding, or planning to become pregnant while receiving study intervention or within 3 months after the last dose. Participants of childbearing potential must have a negative serum pregnancy test within 72 hours prior to receiving the first dose of study intervention.
+13. Uncontrolled intercurrent illness including, but not limited to, ongoing or active infection requiring systemic therapy or psychiatric illness/social situations that would limit compliance with study requirements.
+14. Any other condition (eg, medical, psychiatric, or social) that, in the opinion of the investigator, may interfere with participant safety or the ability to complete the study according to the protocol."

dev/full_data.csv

@@ -0,0 +1,154 @@
+NCTID,AgentGrade,Title,AgentJudgment,Japanes Locations,Primary Completion Date,Cancer,Summary,Eligibility Criteria
+NCT05580562,unclear,ONC201 in H3 K27M-mutant Diffuse Glioma Following Radiotherapy (the ACTION Study),"Based on the provided criteria, the 40-year-old male patient with glioma and a known H3 K27M gene mutation, measurable and biopsiable tumor, may be eligible for this clinical trial. However, I do not know if the patient has received frontline radiotherapy, has a Karnofsky Performance Status or Lansky Performance Status ≥ 70, and meets the other inclusion and exclusion criteria. Further evaluation is needed to determine the patient's eligibility.","Chuo City, Osaka",2026-08,"H3 K27M, Glioma","This is a randomized, double-blind, placebo-controlled, parallel-group, international, Phase 3 study in patients with newly diagnosed H3 K27M-mutant diffuse glioma to assess whether treatment with ONC201 following frontline radiotherapy will extend overall survival and progression-free survival in this population. Eligible participants will have histologically diagnosed H3 K27M-mutant diffuse glioma and have completed standard frontline radiotherapy.","Inclusion Criteria:
+
+1. Able to understand the study procedures and agree to participate in the study by providing written informed consent (by participant or legally authorized representative), and assent when applicable.
+2. Body weight ≥ 10 kg at time of randomization.
+3. Histologically diagnosed H3 K27M-mutant diffuse glioma (new diagnosis). Detection of a missense K27M mutation in any histone H3-encoding gene detected by testing of tumor tissue (immunohistochemistry \[IHC\] or next-generation sequencing \[NGS\] in a Clinical Laboratory Improvement Amendments \[CLIA\]-certified or equivalent laboratory). \[Site to provide (as available): ≥ 10 unstained formalin-fixed paraffin-embedded (FFPE) slides from tumor tissue.\]
+4. At least one, high-quality, contrast-enhanced MRI of the brain obtained prior to starting radiotherapy for submission to sponsor's imaging vendor for central read. For participants who had a surgical resection, this scan must be post-resection; for participants who did not have a resection, this scan may be pre- or post-biopsy.
+5. At least one, high-quality, contrast-enhanced MRI of the brain obtained 2 to 6 weeks after completion of frontline radiotherapy. If unable to obtain contrast-enhanced imaging due to lack of venous access after multiple attempts, a patient may still be eligible after collection of a nonenhanced MRI of the brain. \[Site to also provide all available MRIs completed prior to initiating treatment with study intervention.\]
+6. Received frontline radiotherapy
+
+   1. Initiated radiotherapy within 12 weeks from the initial diagnosis of H3 K27M-mutant diffuse glioma.
+   2. Completed radiotherapy within 2 to 6 weeks prior to randomization
+   3. Completed standard fractionated radiotherapy (eg. 54 to 60 Gy in 28 to 33 fractions given over approximately 6 weeks or hypofractionated radiotherapy (eg. 40 Gy in 15 fractions given over approximately 3 weeks).
+7. Karnofsky Performance Status or Lansky Performance Status ≥ 70 at time of randomization.
+8. Stable or decreasing dose of corticosteroids and anti-seizure medications for 7 days prior to randomization, if applicable. Stable steroid dose is defined as ≤ 2 mg/day increase (based on dexamethasone dose or equivalent dose of an alternative steroid).
+
+Exclusion Criteria:
+
+1. Primary spinal tumor.
+2. Diffuse intrinsic pontine glioma (DIPG), defined as tumors with a pontine epicenter and diffuse involvement of the pons.
+3. Evidence of leptomeningeal spread of disease or cerebrospinal fluid dissemination.
+4. Any known concurrent malignancy.
+5. New lesion(s) outside of the radiation field.
+6. Received whole-brain radiotherapy.
+7. Received proton therapy for glioma.
+8. Use of any of the following treatments within the specified time periods prior to randomization:
+
+   1. ONC201 or ONC206 at any time.
+   2. Systemic bevacizumab (includes biosimilars) at any time since the initial diagnosis of H3 K27M-mutant diffuse glioma.
+   3. Temozolomide within past 3 weeks.
+   4. Tumor treating fields at any time.
+   5. DRD2 antagonist within past 2 weeks.
+   6. Any investigational therapy within past 4 weeks.
+   7. Strong CYP3A4 inhibitors within 3 days.
+   8. Strong CYP3A4 inducers (includes enzyme-inducing antiepileptic drugs) within 2 weeks.
+9. Laboratory test results meeting any of the following parameters within 2 weeks prior to randomization:
+
+   1. Absolute neutrophil count \< 1.0 × 109/L or platelets \< 75 × 109/L.
+   2. Total bilirubin \> 1.5 × upper limit of normal (ULN) (participants with Gilbert's syndrome may be included with total bilirubin \> 1.5 × ULN if direct bilirubin is ≤ 1.5 × ULN).
+   3. Aspartate aminotransferase (AST) or alanine aminotransferase (ALT) \> 2.5 × ULN.
+   4. Creatinine clearance ≤ 60 mL/min as calculated by the Cockcroft Gault equation (or estimated glomerular filtration rate \< 60 mL/min/1.73 m2).
+10. QTc \> 480 msec (based on mean from triplicate electrocardiograms) during screening.
+11. Known hypersensitivity to any excipients used in the study intervention formulation.
+12. Pregnant, breastfeeding, or planning to become pregnant while receiving study intervention or within 3 months after the last dose. Participants of childbearing potential must have a negative serum pregnancy test within 72 hours prior to receiving the first dose of study intervention.
+13. Uncontrolled intercurrent illness including, but not limited to, ongoing or active infection requiring systemic therapy or psychiatric illness/social situations that would limit compliance with study requirements.
+14. Any other condition (eg, medical, psychiatric, or social) that, in the opinion of the investigator, may interfere with participant safety or the ability to complete the study according to the protocol."
+NCT05503264,no,"A Study To Evaluate The Efficacy, Safety, Pharmacokinetics, And Pharmacodynamics Of Satralizumab In Patients With Anti-N-Methyl-D-Aspartic Acid Receptor (NMDAR) Or Anti-Leucine-Rich Glioma-Inactivated 1 (LGI1) Encephalitis","The patient is not eligible for this clinical trial because the patient has a glioma, which is a type of malignancy, and the exclusion criteria state that patients with a history of carcinoma or malignancy are not eligible, unless deemed cured by adequate treatment with no evidence of recurrence for ≥5 years before screening.","Aichi, Chiba, Fukuoka, Gifu, Hokkaido, Hyogo, Hyogoken, Kagoshima, Kanagawa, Miyagi, Osaka, Saitama, Tokyo, sayama",2026-06-23,"NMDAR Autoimmune Encephalitis, LGI1 Autoimmune Encephalitis","The purpose of this study is to assess the efficacy, safety, pharmacokinetics, and pharmacodynamics of satralizumab in participants with anti-N-methyl-D-aspartic acid receptor (NMDAR) and anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis.","Inclusion Criteria:
+
+* Reasonable exclusion of tumor or malignancy before baseline visit (randomization)
+* Onset of autoimmune encephalitis (AIE) symptoms \<=9 months before randomization
+* Meet the definition of ""New Onset"" or ""Incomplete Responder"" AIE
+* For women of childbearing potential: agreement to remain abstinent (refrain from heterosexual intercourse) or use adequate contraception during the treatment period and for at least 3 months after the final dose of satralizumab or placebo
+* For participants enrolled in the extended China enrollment phase at National Medical Products Administration (NMPA)-recognized sites: participants who are current residents of mainland China, Hong Kong, or Taiwan, and of Chinese ancestry
+
+N-methyl-D-aspartic acid receptor (NMDAR) AIE Cohort
+
+* Age \>=12 years
+* Diagnosis of probable or definite NMDAR encephalitis
+
+Leucine-rich glioma-inactivated 1 (LGI1) AIE Cohort
+
+* Age \>=18 years
+* Diagnosis of LGI1 encephalitis
+
+Exclusion Criteria:
+
+* Any untreated teratoma or thymoma at baseline visit (randomization)
+* History of carcinoma or malignancy, unless deemed cured by adequate treatment with no evidence of recurrence for \>=5 years before screening
+* For patients with NMDAR AIE, history of negative anti-NMDAR antibody in cerebrospinal fluid (CSF) using a cell-based assay within 9 months of symptom onset
+* Historically known positivity to an intracellular antigen with high cancer association or GAD-65
+* Historically known positivity to any cell surface neuronal antibodies other than NMDAR and LGI1
+* Confirmed paraneoplastic encephalitis
+* Confirmed central or peripheral nervous system demyelinating disease
+* Alternative causes of associated symptoms
+* History of herpes simplex virus encephalitis in the previous 24 weeks
+* Any previous/concurrent treatment with IL-6 inhibitory therapy (e.g., tocilizumab), alemtuzumab, total body irradiation, or bone marrow transplantation
+* Any previous treatment with anti-CD19 antibody, complement inhibitors, neonatal Fc receptor antagonists, anti-B-lymphocyte stimulator monoclonal antibody
+* Any previous treatment with T-cell depleting therapies, cladribine, or mitoxantrone
+* Treatment with oral cyclophosphamide within 1 year prior to baseline Treatment with any investigational drug (including bortezomib) within 24 weeks prior to screening
+* Concurrent use of more than one IST as background therapy
+* Contraindication to all of the following rescue treatments: rituximab, IVIG, high-dose corticosteroids, or intravenous (IV) cyclophosphamide
+* Any surgical procedure, except laparoscopic surgery or minor surgeries within 4 weeks prior to baseline, excluding surgery for thymoma or teratoma removal
+* Planned surgical procedure during the study
+* Evidence of progressive multifocal leukoencephalopathy
+* Evidence of serious uncontrolled concomitant diseases that may preclude patient participation
+* Congenital or acquired immunodeficiency, including HIV infection
+* Active or presence of recurrent bacterial, viral, fungal, mycobacterial infection, or other infection
+* Infection requiring hospitalization or treatment with IV anti-infective agents within 4 weeks prior to baseline visit
+* Positive hepatitis B (HBV) and hepatitis C (HCV) test at screening
+* Evidence of latent or active tuberculosis (TB)
+* History of drug or alcohol abuse within 1 year prior to baseline
+* History of diverticulitis or concurrent severe gastrointestinal (GI) disorders that, in the investigator's opinion, may lead to increased risk of complications such as GI perforation
+* Receipt of live or live-attenuated vaccine within 6 weeks prior to baseline visit
+* History of blood donation (1 unit or more), plasma donation or platelet donation within 90 days prior to screening
+* History of severe allergic reaction to a biologic agent
+* Active suicidal ideation within 6 months prior to screening, or history of suicide attempt within 3 years prior to screening
+* Any serious medical condition or abnormality in clinical laboratory tests that, in the investigator's judgment, precludes safe participation in and completion of the study
+* Pregnant or breastfeeding, or intending to become pregnant during the study or within 3 months after the final dose of study drug
+* Laboratory abnormalities at Screening"
+NCT06159478,no,Binimetinib in Patients With BRAF Fusion-positive Low-grade Glioma or Pancreatic Cancer (Perfume),"The patient is not eligible for this clinical trial because the patient has a glioma with a known gene mutation of H3 K27M, but the trial requires a BRAF fusion or rearrangement.","Fukuoka, Kashiwa, Kyoto City, Sapporo, Sendai, ku",2027-02-28,"Low-grade Glioma, Pancreatic Cancer","This study is an open-label, parallel, 2-cohort, multicenter, investigator-initiated Phase 2 trial to evaluate the efficacy and safety of binimetinib in patients with advanced or recurrent low-grade glioma or pancreatic cancer harboring BRAF fusion/rearrangement.","Inclusion Criteria:
+
+Inclusion criteria for both cohort A and B
+
+1. BRAF fusion or rearrangement is detected by reimbursed NGS-based cancer gene panel tests, cancer gene panel tests performed under advanced medical treatment, or clinical study (including liquid biopsy).
+2. Unresectable or recurrent
+3. No symptomatic brain metastasis, carcinomatous meningitis or spinal metastasis requiring surgical intervention or radiotherapy
+4. No cardiac effusion, pleural effusion, or ascites requiring treatment
+5. Not received anti-cancer drug within 14 days before registration, nor received other study drug (molecular targeting drug, immune therapy) within 21 days before registration
+6. Not received operation under general anesthesia within 28 days before registration
+7. Not received radiation therapy (including gamma knife, cyber knife) within 14 days before registration
+8. Left ventricular ejection fraction \>= 50% by echocardiography or MUGA (multigated acquisition scan) within 28 days before registration
+9. Having all laboratory tests performed within 14 days before registration and the values are within the following range. Patients should not receive administration of G-CSF and/or blood transfusion within 14 days before the blood collection (1) Absolute neutrophil count \>= 1.500/mm3 (2) Platelet count \>= 10.0 X 10(4))/mm3 (3) Hemoglobin \>= 8.0 g/dL (4) Total bilirubin \<= 1.5 g/dL (5) Aspartate aminotransferase (AST) \<= 100 U/L (6) Alanine aminotransferase (ALT) \<= 100 U/L (7) Serum creatinine \<= 1.5 mg/dL
+10. Patients who are able to swallow orally administered medication.
+11. Consent to at least 30 days of contraception and limited egg donation (including egg retrieval for future egg transfer) after last administration of study drug for child-bearing status women. Consent to 90 days of contraception and limited sperm donation after last administration of study drug for men.
+12. Written informed consent (When registering patient under 18, a signed consent form must be obtained from both the patient and the parent or legal guardian.)
+
+    Cohort A
+13. Histopathologically diagnosed as low-grade glioma, based on WHO classification of 2007, 2016 and 2021. The grade is WHO grade 1 or 2.
+14. Age at the time of registration is 12 years or older (When registering a patient under 18, a signed consent form must be obtained from both the patient and the parent or legal guardian), and patients who are 12-17 years old have to be 40 kg or over in body weight. There is no limitation in body weight for patients who are 18 years or older.
+15. Lansky Performance Status (LPS) \>= 70 for patients 12-15 years old Karnofsky Performance Status (KPS) \>= 70 for patients 16 years or older
+16. Having measurable disease within 28 days before registration
+17. Patients suffice the following. (1) Having adequate initial treatment depending on the primary central nervous tumor including surgery if recommended treatment is available. (2) Neurologically stable.
+
+(3) Multiple lesion or dissemination is not detected with MRI at the registration.
+
+18) Not increased steroid for low-grade glioma within 14 days before registration and the dosage of steroid in equivalent to 50 mg prednisolone or less.
+
+Cohort B 19) Histopathologically diagnosed as pancreatic cancer (histologically not specified).
+
+20) Having progression after at least one regimen of chemotherapy excluding adjuvant therapy.
+
+21) Age at the time of registration is 18 years or older. 22) Performance Status (ECOG) is 0 or 1 23) Having measurable disease within 28 days before registration detected by enhanced CT (Head, chest, abdominal, pelvic: under 5 mm in slice)
+
+Exclusion Criteria:
+
+1. Active double primary cancer (but not \[1\]-\[3\]): \[1\] completely resected following cancers: basal cell carcinoma, stage I squamous cell carcinoma, carcinoma in situ, intramucosal carcinoma, superficial bladder cancer, \[2\] gastrointestinal cancer curatively resected with ESD or EMR, and \[3\] other cancers with no recurrence for more than 5 years.
+2. Patients with symptomatic congestive heart failure of NYHA class II-IV or arrythmia (over grade 2) occurring in less than 6 months before registration.
+3. Patients with myocardial infarction or unstable angina occurring in less than 6 months before registration.
+4. Patients with corrected QT interval (QTcF) \> 480 ms in ECG performed within 14 days before enrollment.
+5. Patients with infections requiring systemic treatment.
+6. Patients with uncontrolled hypertension (systolic blood pressure: over 150 mmHg or diastolic blood pressure: over 100 mmHg).
+7. Patients with history or findings of retinal vein occlusion (RVO) or having RVO risk factor (unstable glaucoma, ocular hypertension, hyperviscosity syndrome, hypercoagulability syndrome, etc.)
+8. Patients with history or complication of retinal degenerative disease other than RVO (central serous chorioretinopathy, retinal detachment, age-related macular degeneration, etc.)
+9. Patients with uncontrolled diabetes mellitis.
+10. Patients with venous thrombus (transient ischemic attack, stroke, massive deep vein thrombosis, pulmonary embolism, etc.) occurring in less than 3 months
+11. Patients who have neuromuscular disease with CK elevation (inflammatory myopathy, muscular dystrophy, amyotrophic lateral sclerosis, spinal muscular atrophy, etc.).
+12. Prior treatment with MEK inhibitors.
+13. Previous severe hypersensitive reaction to ingredient including binimetinib.
+14. Patients who are positive for either HIV antibody, HBs antigen, or HCV-RNA.
+15. Negative for HBs antigen, positive for HBs antibody or HBc antibody, and positive for HBV-DNA assay. (If it is less than or equal to the detection sensitivity, patients are not excluded)
+16. Patients with concomitant diseases that affect gastrointestinal function.
+17. Women who are pregnant, breastfeeding and need to continue breastfeeding in the future, and women who may be pregnant.
+18. Patients with psychiatric diseases or psychological symptoms interfering with participation in the trial.
+19. Patients who are deemed inappropriate for participation in the trial by the principal investigator or sub-investigator."