{"id":"W4380362186","doi":"10.1016/b978-0-12-817134-9.00015-5","title":"Integrated pharmacokinetic/pharmacodynamic/efficacy analysis in oncology: importance of pharmacodynamic/efficacy relationships","year":2023,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Melanoma and MAPK Pathways","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pharmacodynamics; Pharmacokinetics; Context (archaeology); Pharmacology; Medicine; Biomarker; Oncology; Drug; Clinical efficacy; Efficacy; Computational biology; 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":[0.002743803,0.001055464,0.001552969,0.0008053688,0.0001368695,0.00292875,0.0006076974,0.0009517001,0.007410123],"category_scores_gemma":[0.004670377,0.0004976891,0.001112952,0.0007560628,0.0004833733,0.001521759,0.0005634626,0.002495142,0.002551005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008191691,"about_ca_system_score_gemma":0.0008915897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007719123,"about_ca_topic_score_gemma":0.001371175,"domain_scores_codex":[0.9992024,0.0003654203,0.00003962173,0.00009954794,0.0002648058,0.00002812011],"domain_scores_gemma":[0.9978724,0.001794429,0.0001140687,0.00007359826,0.0001082982,0.0000372932],"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":[0.0004221718,0.0003005747,0.00407711,0.001644712,0.000942069,0.0004658453,0.00007380723,0.05700508,0.01955435,0.0609805,0.02997726,0.8245565],"study_design_scores_gemma":[0.0001173905,0.001264707,0.01210286,0.001041913,0.001318204,0.003632348,0.0001504754,0.2966892,0.02193098,0.4528112,0.2087151,0.0002255809],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01771663,0.1858767,0.6968765,0.009875966,0.001237408,0.000230974,0.002166518,0.001470078,0.08454921],"genre_scores_gemma":[0.3644576,0.1695484,0.3711229,0.006205481,0.003346631,0.0004390654,0.001831532,0.001265138,0.08178329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007410123,"threshold_uncertainty_score":0.02478927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03322566239138656,"score_gpt":0.3005959734312342,"score_spread":0.2673703110398477,"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."}}