{"id":"W3018455288","doi":"10.1016/j.clinthera.2020.03.006","title":"Use of Real-world Data for New Drug Applications and Line Extensions","year":2020,"lang":"en","type":"review","venue":"Clinical Therapeutics","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Sanofi","keywords":"Medicine; Orphan drug; Timeline; Drug; Agency (philosophy); Regulatory science; Food and drug administration; Drug approval; Tolerability; Regulatory agency; MEDLINE; Pharmacology; Family medicine; Data science; Adverse effect; Bioinformatics; Computer science; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008755557,0.0004559788,0.002080544,0.000133789,0.0002029792,0.00002944964,0.0008721782,0.0004448027,0.00006455365],"category_scores_gemma":[0.0002221551,0.0003910122,0.0005410395,0.0005368155,0.0005457042,0.0001592543,0.0004555767,0.001732236,0.00005686081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000339501,"about_ca_system_score_gemma":0.0007527355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000186172,"about_ca_topic_score_gemma":0.00003974829,"domain_scores_codex":[0.9965003,0.000544426,0.001610334,0.0008520415,0.0001253643,0.0003675141],"domain_scores_gemma":[0.9881037,0.009181015,0.0009836343,0.001081748,0.000130422,0.0005194418],"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":[0.00007962861,0.0003467581,0.00004451326,0.001365889,0.001196925,0.000004190036,0.00001829588,0.000005871252,0.000006357128,0.000983712,0.02160622,0.9743416],"study_design_scores_gemma":[0.0006350165,0.00006244535,0.000007104792,0.0004107394,0.00720804,0.000007067938,0.000009765002,0.001348384,0.000006997433,0.0002806874,0.989674,0.0003497664],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000007530057,0.9879832,0.001211887,0.001484593,0.000987835,0.002618038,0.005360155,0.0001246973,0.000222026],"genre_scores_gemma":[0.00001226659,0.9880803,0.002761752,0.003054762,0.001822317,0.0001543702,0.001461648,0.00008760822,0.002565017],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9739919,"threshold_uncertainty_score":0.9998542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7882468021714223,"score_gpt":0.643252198100617,"score_spread":0.1449946040708053,"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."}}