{"id":"W3001449808","doi":"10.1002/cpt.1795","title":"Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?","year":2020,"lang":"en","type":"review","venue":"Clinical Pharmacology & Therapeutics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Center for Advancing Translational Sciences; National Cancer Institute; National Institutes of Health","keywords":"Context (archaeology); Drug discovery; Clinical pharmacology; Identification (biology); Clinical trial; Clinical Practice; Generative grammar; Drug; Pharmacology; Medicine; Data science; Artificial intelligence; Computer science; Bioinformatics; Internal medicine; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002973251,0.0007734708,0.001157336,0.002365979,0.0003698016,0.002211265,0.001152613,0.002768837,0.005803926],"category_scores_gemma":[0.004521406,0.000319689,0.0006933411,0.002370571,0.001883416,0.004232106,0.001036772,0.004985485,0.003802848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001809024,"about_ca_system_score_gemma":0.00314587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001820398,"about_ca_topic_score_gemma":0.00260591,"domain_scores_codex":[0.9993442,0.0002571149,0.0000469894,0.00008917012,0.0002095465,0.0000530003],"domain_scores_gemma":[0.9968023,0.002330591,0.0001370412,0.00009295418,0.000500211,0.0001368275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006128474,0.00008319612,0.000150761,0.008859134,0.00009341778,0.0000690132,0.00008153221,0.000673147,0.0003669348,0.06456468,0.05478685,0.8702101],"study_design_scores_gemma":[0.00002808845,0.0000751906,0.0004615285,0.006326295,0.00005401916,0.0003319297,0.00007213165,0.0003065026,0.0001525579,0.03456968,0.9575945,0.00002750249],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005785807,0.9925466,0.0003115601,0.004337568,0.0006405673,0.000003838521,0.00001335135,0.000008276984,0.00208051],"genre_scores_gemma":[0.0009663303,0.9941714,0.0005042253,0.002699995,0.0009124377,0.000009199707,0.00001808446,0.00000414146,0.0007141171],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005803926,"threshold_uncertainty_score":0.01941603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3585694479664162,"score_gpt":0.5906098123856323,"score_spread":0.2320403644192161,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}