{"id":"W4390402849","doi":"10.1007/s13346-023-01491-9","title":"Data-driven development of an oral lipid-based nanoparticle formulation of a hydrophobic drug","year":2023,"lang":"en","type":"article","venue":"Drug Delivery and Translational Research","topic":"Drug Solubulity and Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Structural Genomics Consortium; Canadian Institute for Advanced Research; Vector Institute; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bioavailability; Drug; Drug delivery; Solid lipid nanoparticle; Solubility; First pass effect; Computer science; Pharmacokinetics; Nanotechnology; Biochemical engineering; Chemistry; Pharmacology; Materials science; Organic chemistry; Engineering; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004239402,0.0001275608,0.0002433026,0.0003447295,0.0003772402,0.00001716862,0.000359924,0.00011928,0.0001843689],"category_scores_gemma":[0.00003965813,0.0001269643,0.00004476082,0.0006827438,0.0002653202,0.0004092165,0.0001004037,0.000353552,0.00007095876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001967462,"about_ca_system_score_gemma":0.0004621493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001325347,"about_ca_topic_score_gemma":0.000577195,"domain_scores_codex":[0.9972241,0.0008111214,0.0005489821,0.0003561277,0.0006560092,0.0004036862],"domain_scores_gemma":[0.9980097,0.001081408,0.00009089111,0.0002770397,0.000343735,0.0001972315],"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":[0.008907726,0.00418281,0.1179765,0.002751023,0.001035085,0.0001034173,0.04507558,0.1145614,0.5236475,0.006186734,0.006213713,0.1693585],"study_design_scores_gemma":[0.002698951,0.00009842673,0.02424799,0.00006636608,0.00005261991,0.000002921884,0.0005811817,0.8475795,0.09764814,0.0006487057,0.02613808,0.0002371518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980634,0.0001845549,0.00004758053,0.0003728968,0.0001432295,0.0004025184,0.0004042271,0.00004543193,0.0003361679],"genre_scores_gemma":[0.9981803,0.00003869977,0.0006546645,0.00004259837,0.00005846604,0.00002507065,0.0007926016,0.00001374384,0.0001938768],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7330181,"threshold_uncertainty_score":0.5177455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.339010982347674,"score_gpt":0.4914863620635999,"score_spread":0.1524753797159259,"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."}}