{"id":"W4386099973","doi":"10.1038/s41586-023-06388-8","title":"From target discovery to clinical drug development with human genetics","year":2023,"lang":"en","type":"review","venue":"Nature","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":203,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill Genome Centre; Jewish General Hospital; McGill University","funders":"","keywords":"Drug development; Biobank; Drug discovery; Disease; Orphan drug; Clinical trial; Medicine; Genomics; Precision medicine; Human genetics; Medical genetics; Computational biology; Bioinformatics; Biology; Drug; Genetics; Genome; Pharmacology; Gene; Internal medicine","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":[0.001385134,0.001559848,0.002126874,0.002442425,0.0002808422,0.00156625,0.001404396,0.001756414,0.005089848],"category_scores_gemma":[0.001669841,0.0003796002,0.0005848531,0.002615718,0.001019061,0.001682564,0.00129766,0.003733275,0.002867366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001328298,"about_ca_system_score_gemma":0.00161759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001232193,"about_ca_topic_score_gemma":0.00292056,"domain_scores_codex":[0.9996499,0.000083132,0.00003315047,0.0000534568,0.0001395621,0.00004085383],"domain_scores_gemma":[0.9993008,0.0004256293,0.00006047779,0.00002349826,0.0001127723,0.00007667884],"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":[0.0001370038,0.00007525703,0.00009753391,0.0115359,0.0001226242,0.0002042308,0.00003042205,0.0007132702,0.001082885,0.00924485,0.1144207,0.8623352],"study_design_scores_gemma":[0.0000507302,0.00006735263,0.000239249,0.002415283,0.0001050714,0.0005088234,0.00002090961,0.000143059,0.0001977196,0.004676506,0.9915609,0.00001442244],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004095617,0.9970701,0.0003379007,0.0006011301,0.0006131213,0.000005312299,0.00002306493,0.00001657298,0.001291765],"genre_scores_gemma":[0.000395056,0.997224,0.0003160246,0.0006820415,0.0005422445,0.000009620532,0.00003800479,0.000003138995,0.0007898863],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005089848,"threshold_uncertainty_score":0.01702726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02833882160609055,"score_gpt":0.3671400709732062,"score_spread":0.3388012493671157,"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."}}