{"id":"W4414476131","doi":"10.1002/psp4.70115","title":"An Open‐Source Framework for Virtual Bioequivalence Modeling and Clinical Trial Design","year":2025,"lang":"en","type":"article","venue":"CPT Pharmacometrics & Systems Pharmacology","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Waterloo","funders":"Food and Drug Administration; U.S. Food and Drug Administration; U.S. Department of Health and Human Services","keywords":"Bioequivalence; Physiologically based pharmacokinetic modelling; In silico; IVIVC; Toolbox; Rework; Inference; In vivo; Benchmark (surveying); Repurposing","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":[0.02014739,0.002008156,0.001868949,0.002117304,0.0005883712,0.003892302,0.004965943,0.00263365,0.03774304],"category_scores_gemma":[0.04312739,0.001995329,0.003643459,0.001560352,0.001334428,0.002019156,0.004792123,0.004230476,0.01398896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001375396,"about_ca_system_score_gemma":0.00573688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003110349,"about_ca_topic_score_gemma":0.003923008,"domain_scores_codex":[0.9942253,0.003026974,0.000565991,0.0005236248,0.001450343,0.0002078585],"domain_scores_gemma":[0.9772893,0.0169871,0.001143549,0.002245301,0.0017028,0.0006318419],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007303872,0.000338736,0.002068263,0.003600414,0.001695453,0.0008727183,0.0004404147,0.2639725,0.004539643,0.2320723,0.1278929,0.3617763],"study_design_scores_gemma":[0.0007896444,0.0001991078,0.0005645713,0.0007388655,0.000291204,0.0004213674,0.00004679025,0.4751106,0.003021424,0.2548348,0.2638666,0.0001150051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003045714,0.0004889182,0.9696581,0.0004604992,0.0001363743,0.0002970944,0.002014923,0.02447798,0.002161592],"genre_scores_gemma":[0.01949946,0.001456131,0.9583592,0.0008810653,0.0001752103,0.003212647,0.00536151,0.007949862,0.00310496],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03774304,"threshold_uncertainty_score":0.126263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7654397942060153,"score_gpt":0.6792413634340045,"score_spread":0.08619843077201073,"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."}}