{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007000703,0.0002728774,0.0002293619,0.0002352186,0.0001747092,0.0005522765,0.0003353712,0.0003382787,0.001214402],"category_scores_gemma":[0.0007513894,0.0002020709,0.0002318137,0.0001235545,0.0001876805,0.000348244,0.0004336677,0.0004453912,0.0007232619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004592768,"about_ca_system_score_gemma":0.0008155361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007297095,"about_ca_topic_score_gemma":0.00131777,"domain_scores_codex":[0.9996774,0.00002288588,0.00001801257,0.00006709838,0.0001885025,0.00002606993],"domain_scores_gemma":[0.9997321,0.00005381959,0.00005071935,0.00002568866,0.0001161156,0.00002157219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001295286,0.00006739731,0.0004276274,0.0001167671,0.00001095006,0.00008737845,0.00003606748,0.003716147,0.9764632,0.0008424058,0.0003539053,0.01774855],"study_design_scores_gemma":[0.00001632912,0.0001906845,0.000325178,0.000005634535,0.00001390566,0.00006827154,0.00001239783,0.0236926,0.9695491,0.0001401356,0.0059764,0.000009394856],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6638415,0.0009642844,0.3147358,0.0008545798,0.0002154615,0.001337159,0.002057768,0.002360575,0.01363287],"genre_scores_gemma":[0.7931474,0.0006504815,0.1944698,0.0001725155,0.0000172841,0.0004293426,0.001253296,0.0002951326,0.009564711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001214402,"threshold_uncertainty_score":0.004062593,"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."}}