{"id":"W4400622862","doi":"10.1016/j.taap.2024.117034","title":"Can we do better with Mylotarg? Model-based assessment of opportunities to improve therapeutic index","year":2024,"lang":"en","type":"article","venue":"Toxicology and Applied Pharmacology","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fractal Systems (Canada)","funders":"","keywords":"Dosing; Pharmacology; Clinical trial; Toxicity; Pharmacokinetics; Adverse effect; Drug; Therapeutic index; Schedule; Medicine; Prioritization; Food and drug administration; Pharmacodynamics; Dose; Intensive care medicine; Internal medicine; Computer science","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":[0.002585158,0.0008152814,0.001590788,0.0003702844,0.0003070825,0.003157396,0.001454922,0.001232195,0.006370313],"category_scores_gemma":[0.002402755,0.0002771163,0.001135172,0.0003080069,0.0008047984,0.003376027,0.0007220763,0.002753332,0.001642156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009944589,"about_ca_system_score_gemma":0.001084968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007460624,"about_ca_topic_score_gemma":0.001081027,"domain_scores_codex":[0.9993374,0.000215976,0.0000322082,0.0001201601,0.0001686305,0.0001256496],"domain_scores_gemma":[0.9992405,0.0002695748,0.0001674078,0.00008558994,0.0001182036,0.0001188592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01515495,0.002652004,0.005294406,0.002748895,0.001018012,0.0008454713,0.0003325958,0.03902069,0.6807339,0.03422377,0.01620799,0.2017673],"study_design_scores_gemma":[0.002648289,0.04409063,0.005567528,0.0007464545,0.002020204,0.00241506,0.0007142727,0.09603057,0.5901865,0.03221315,0.222875,0.0004923983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7603238,0.08015966,0.09075274,0.02806456,0.002722197,0.0007542201,0.004395854,0.002644647,0.03018224],"genre_scores_gemma":[0.9512618,0.01834892,0.02106147,0.002665835,0.0002019202,0.0002616537,0.001381379,0.0002231536,0.004593824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006370313,"threshold_uncertainty_score":0.02131081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03795955727374511,"score_gpt":0.3382090716434077,"score_spread":0.3002495143696626,"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."}}