{"id":"W3000135183","doi":"10.3390/pharmaceutics12010074","title":"A Mechanistic Physiologically-Based Biopharmaceutics Modeling (PBBM) Approach to Assess the In Vivo Performance of an Orally Administered Drug Product: From IVIVC to IVIVP","year":2020,"lang":"en","type":"article","venue":"Pharmaceutics","topic":"Drug Solubulity and Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Food and Drug Administration; Hamilton Health Sciences Foundation; Fonds Wetenschappelijk Onderzoek; American Association of Pharmaceutical Scientists","keywords":"IVIVC; Physiologically based pharmacokinetic modelling; Pharmacokinetics; In vivo; Biopharmaceutics; Pharmacology; Bioequivalence; Computer science; Drug; Dissolution testing; Biochemical engineering; Chemistry; Medicine; Biopharmaceutics Classification System; In vitro; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000578525,0.0007168623,0.0005531571,0.0003715178,0.0002621951,0.0009282915,0.0009293806,0.001016379,0.00129826],"category_scores_gemma":[0.0007406037,0.0003843984,0.001001562,0.0002548565,0.0003697669,0.0006921844,0.0005175213,0.001075016,0.0005691566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006277756,"about_ca_system_score_gemma":0.001008731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002739507,"about_ca_topic_score_gemma":0.001108985,"domain_scores_codex":[0.999755,0.00006729566,0.00001596738,0.00004619564,0.00009679592,0.00001882012],"domain_scores_gemma":[0.9997407,0.0001025115,0.00005436962,0.00002787515,0.00006056537,0.00001401673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001048042,0.0001991078,0.002283525,0.0004036615,0.00008374294,0.0001691815,0.0001073598,0.896859,0.06240413,0.01045473,0.001254655,0.02567605],"study_design_scores_gemma":[0.00001437554,0.000293139,0.0006984348,0.00003927669,0.00004400921,0.0001297684,0.00002432087,0.9770951,0.01284181,0.002574035,0.006220945,0.00002469941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1227885,0.002411964,0.8545229,0.001496243,0.0001400587,0.0004842111,0.001030499,0.000890007,0.01623568],"genre_scores_gemma":[0.8350214,0.004121152,0.1506563,0.000527725,0.00007300716,0.0008078656,0.0009687307,0.0001944121,0.007629561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002739507,"threshold_uncertainty_score":0.00544709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3551299014290869,"score_gpt":0.4343325597526548,"score_spread":0.07920265832356788,"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."}}