{"id":"W2922723892","doi":"10.1073/pnas.1817246116","title":"Structure-guided design fine-tunes pharmacokinetics, tolerability, and antitumor profile of multispecific frizzled antibodies","year":2019,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Wnt/β-catenin signaling in development and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"National Institutes of Health; Mitacs; Canada Research Chairs; Canadian Institutes of Health Research; University of Arizona Cancer Center","keywords":"Monoclonal antibody; Wnt signaling pathway; Frizzled; In vivo; Antibody; Epitope; Cancer research; Tolerability; Pharmacology; Chemistry; Biology; Signal transduction; Biochemistry; Immunology","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":[0.0002790691,0.0004492214,0.0002746083,0.0003046333,0.0001168599,0.0004572928,0.0003580818,0.000298326,0.0006481947],"category_scores_gemma":[0.0002044013,0.0002263929,0.0002484643,0.0001479317,0.0001506002,0.0002216303,0.0002110174,0.0005522254,0.000218727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006181714,"about_ca_system_score_gemma":0.0002975732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007930453,"about_ca_topic_score_gemma":0.001913927,"domain_scores_codex":[0.9998373,0.00002611133,0.00001051178,0.00002824557,0.00004467677,0.00005318295],"domain_scores_gemma":[0.9999249,0.00001255787,0.0000285515,0.000006823079,0.00001446911,0.00001264382],"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":[0.0001852975,0.0001884042,0.000291023,0.00004623662,0.00002275214,0.00004332058,0.00001555063,0.003305415,0.9854789,0.0002613031,0.0001511659,0.01001071],"study_design_scores_gemma":[0.0001824993,0.002352828,0.001696292,0.000009133612,0.00008161969,0.000268228,0.00002014317,0.00976107,0.9794132,0.0001233474,0.006074561,0.00001715169],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984055,0.001972326,0.01111875,0.0001549825,0.00003154038,0.0001691338,0.000166421,0.0001378491,0.002194018],"genre_scores_gemma":[0.9914026,0.0009515094,0.006334941,0.00008865592,0.000008193512,0.00005346532,0.0001398062,0.00002983477,0.000991124],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007930453,"threshold_uncertainty_score":0.00448519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04044296117327803,"score_gpt":0.3096860073049507,"score_spread":0.2692430461316726,"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."}}