| { | |
| "ADMET_Caco2_Wang": { | |
| "task_type": "regression", | |
| "task_name": "Drug Permeability", | |
| "description": "predict drug permeability, measured in cm/s, using the Caco-2 cell line as an in vitro model to simulate human intestinal tissue permeability", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#caco-2-cell-effective-permeability-wang-et-al", | |
| "num_molecules": 906 | |
| }, | |
| "ADMET_Bioavailability_Ma": { | |
| "task_type": "classification", | |
| "task_name": "Drug Oral Bioavailability", | |
| "description": "predict oral bioavailability with binary labels, indicating the rate and extent a drug becomes available at its site of action", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#bioavailability-ma-et-al", | |
| "num_molecules": 640 | |
| }, | |
| "ADMET_Lipophilicity_AstraZeneca": { | |
| "task_type": "regression", | |
| "task_name": "Drug Lipophilicity", | |
| "description": "predict lipophilicity with continuous labels, measured as a log-ratio, indicating a drug's ability to dissolve in lipid environments", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#lipophilicity-astrazeneca", | |
| "num_molecules": 4200 | |
| }, | |
| "ADMET_Solubility_AqSolDB": { | |
| "task_type": "regression", | |
| "task_name": "Drug Aqueous Solubility", | |
| "description": "predict aqueous solubility with continuous labels, measured in log mol/L, indicating a drug's ability to dissolve in water", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#solubility-aqsoldb", | |
| "num_molecules": 9982 | |
| }, | |
| "ADMET_HIA_Hou": { | |
| "task_type": "classification", | |
| "task_name": "Drug Human Intestinal Absorption", | |
| "description": "predict human intestinal absorption (HIA) with binary labels, indicating a drug's ability to be absorbed into the bloodstream", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#hia-human-intestinal-absorption-hou-et-al", | |
| "num_molecules": 578 | |
| }, | |
| "ADMET_Pgp_Broccatelli": { | |
| "task_type": "classification", | |
| "task_name": "P-glycoprotein Inhibition", | |
| "description": "predict P-glycoprotein (Pgp) inhibition with binary labels, indicating a drug's potential to alter bioavailability and overcome multidrug resistance", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#pgp-p-glycoprotein-inhibition-broccatelli-et-al", | |
| "num_molecules": 1212 | |
| }, | |
| "ADMET_BBB_Martins": { | |
| "task_type": "classification", | |
| "task_name": "Blood-Brain Barrier Permeability", | |
| "description": "predict blood-brain barrier permeability with binary labels, indicating a drug's ability to penetrate the barrier to reach the brain", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#bbb-blood-brain-barrier-martins-et-al", | |
| "num_molecules": 1915 | |
| }, | |
| "ADMET_PPBR_AZ": { | |
| "task_type": "regression", | |
| "task_name": "Plasma Protein Binding Rate", | |
| "description": "predict plasma protein binding rate with continuous labels, indicating the percentage of a drug bound to plasma proteins in the blood", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#ppbr-plasma-protein-binding-rate-astrazeneca", | |
| "num_molecules": 1797 | |
| }, | |
| "ADMET_VDss_Lombardo": { | |
| "task_type": "regression", | |
| "task_name": "Volume of Distribution at Steady State", | |
| "description": "predict the volume of distribution at steady state (VDss), indicating drug concentration in tissues versus blood", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#vdss-volumn-of-distribution-at-steady-state-lombardo-et-al", | |
| "num_molecules": 1130 | |
| }, | |
| "ADMET_CYP2C9_Veith": { | |
| "task_type": "classification", | |
| "task_name": "CYP2C9 Inhibition", | |
| "description": "predict CYP2C9 inhibition with binary labels, indicating the drug's ability to inhibit the CYP2C9 enzyme involved in metabolism", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#cyp-p450-2c9-inhibition-veith-et-al", | |
| "num_molecules": 12092 | |
| }, | |
| "ADMET_CYP2D6_Veith": { | |
| "task_type": "classification", | |
| "task_name": "CYP2D6 Inhibition", | |
| "description": "predict CYP2D6 inhibition with binary labels, indicating the drug's potential to inhibit the CYP2D6 enzyme involved in metabolism", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#cyp-p450-2d6-inhibition-veith-et-al", | |
| "num_molecules": 13130 | |
| }, | |
| "ADMET_CYP3A4_Veith": { | |
| "task_type": "classification", | |
| "task_name": "CPY3A4 Inhibition", | |
| "description": "predict CPY3A4 inhibition with binary labels, indicating the drug's ability to inhibit the CPY3A4 enzyme involved in metabolism", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#cyp-p450-3a4-inhibition-veith-et-al", | |
| "num_molecules": 12328 | |
| }, | |
| "ADMET_CYP2C9_Substrate_CarbonMangels": { | |
| "task_type": "classification", | |
| "task_name": "CYP2C9 Substrate", | |
| "description": "predict whether a drug is a substrate of the CYP2C9 enzyme with binary labels, indicating its potential to be metabolized", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#cyp2c9-substrate-carbon-mangels-et-al", | |
| "num_molecules": 666 | |
| }, | |
| "ADMET_CYP2D6_Substrate_CarbonMangels": { | |
| "task_type": "classification", | |
| "task_name": "CYP2D6 Substrate", | |
| "description": "predict whether a drug is a substrate of the CYP2D6 enzyme with binary labels, indicating its potential to be metabolized", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#cyp2d6-substrate-carbon-mangels-et-al", | |
| "num_molecules": 664 | |
| }, | |
| "ADMET_CYP3A4_Substrate_CarbonMangels": { | |
| "task_type": "classification", | |
| "task_name": "CYP3A4 Substrate", | |
| "description": "predict whether a drug is a substrate of the CYP3A4 enzyme with binary labels, indicating its potential to be metabolized", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#cyp3a4-substrate-carbon-mangels-et-al", | |
| "num_molecules": 667 | |
| }, | |
| "ADMET_Half_Life_Obach": { | |
| "task_type": "regression", | |
| "task_name": "Drug Half-Life Duration", | |
| "description": "predict the half-life duration of a drug, measured in hours, indicating the time for its concentration to reduce by half", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#half-life-obach-et-al", | |
| "num_molecules": 667 | |
| }, | |
| "ADMET_Clearance_Hepatocyte_AZ": { | |
| "task_type": "regression", | |
| "task_name": "Drug Clearance from Hepatocyte Experiments", | |
| "description": "predict drug clearance, measured in \u03bcL/min/10^6 cells, from hepatocyte experiments, indicating the rate at which the drug is removed from body", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#clearance-astrazeneca", | |
| "num_molecules": 1020 | |
| }, | |
| "ADMET_Clearance_Microsome_AZ": { | |
| "task_type": "regression", | |
| "task_name": "Drug Clearance from Microsome Experiments", | |
| "description": "predict drug clearance, measured in mL/min/g, from microsome experiments, indicating the rate at which the drug is removed from body", | |
| "url": "https://tdcommons.ai/single_pred_tasks/adme#clearance-astrazeneca", | |
| "num_molecules": 1102 | |
| }, | |
| "ADMET_LD50_Zhu": { | |
| "task_type": "regression", | |
| "task_name": "Drug Acute Toxicity", | |
| "description": "predict the acute toxicity of a drug, measured as the dose leading to lethal effects in log(kg/mol)", | |
| "url": "https://tdcommons.ai/single_pred_tasks/tox#acute-toxicity-ld50", | |
| "num_molecules": 7385 | |
| }, | |
| "ADMET_hERG": { | |
| "task_type": "classification", | |
| "task_name": "hERG Channel Blockage", | |
| "description": "predict whether a drug blocks the hERG channel, which is crucial for heart rhythm, potentially leading to adverse effects", | |
| "url": "https://tdcommons.ai/single_pred_tasks/tox#herg-blockers", | |
| "num_molecules": 648 | |
| }, | |
| "ADMET_AMES": { | |
| "task_type": "classification", | |
| "task_name": "Drug Mutagenicity", | |
| "description": "predict whether a drug is mutagenic with binary labels, indicating its ability to induce genetic alterations", | |
| "url": "https://tdcommons.ai/single_pred_tasks/tox#ames-mutagenicity", | |
| "num_molecules": 7255 | |
| }, | |
| "ADMET_DILI": { | |
| "task_type": "classification", | |
| "task_name": "Drug-Induced Liver Injury", | |
| "description": "predict whether a drug can cause liver injury with binary labels, indicating its potential for hepatotoxicity", | |
| "url": "https://tdcommons.ai/single_pred_tasks/tox#dili-drug-induced-liver-injury", | |
| "num_molecules": 475 | |
| } | |
| } |