{"id":"W4414675678","doi":"10.2147/ceg.s521893","title":"Optimising Monoclonal Antibody Drug Development for Inflammatory Bowel Disease","year":2025,"lang":"en","type":"review","venue":"Clinical and Experimental Gastroenterology","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"Medac; Genentech; Nordic Pharma Group; Celltrion; Biogen; Gilead Sciences; Amgen; Pfizer; Eli Lilly and Company","keywords":"Inflammatory bowel disease; Monoclonal antibody; Immunogenicity; Antibody; Blockade; Drug development; Cytokine; Drug; Disease","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005428724,0.0005799024,0.002085847,0.0002496284,0.0002203337,0.00004258951,0.0002685395,0.0002889122,0.00009799962],"category_scores_gemma":[0.0001264127,0.0004379489,0.0008449067,0.00006597582,0.0006539819,0.00005092933,0.0005998597,0.0006428902,0.00003623501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007327511,"about_ca_system_score_gemma":0.0006381939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003989522,"about_ca_topic_score_gemma":0.000001730901,"domain_scores_codex":[0.9963111,0.0002535012,0.001486415,0.0009387338,0.0002785744,0.0007317223],"domain_scores_gemma":[0.9980059,0.0005082166,0.0002410267,0.0003209586,0.00008738486,0.0008365555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01681432,0.003886032,0.05412699,0.09352638,0.003262848,0.0008530651,0.0001962092,0.000001700439,0.00002485967,0.000413194,0.01668305,0.8102114],"study_design_scores_gemma":[0.002103259,0.0007622718,0.001599617,0.007624799,0.0005212587,0.0001100945,0.00003139448,0.00005075279,0.00001216323,0.00001560844,0.9868924,0.0002764072],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01649232,0.9805127,0.00007776226,0.0003890803,0.0006085011,0.001595563,0.0001221493,0.00004805704,0.000153853],"genre_scores_gemma":[0.0002384558,0.988894,0.003408409,0.0009661675,0.000663306,0.000443162,0.001269615,0.00005116658,0.004065694],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9702093,"threshold_uncertainty_score":0.9998072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06802773564517675,"score_gpt":0.4532540421494152,"score_spread":0.3852263065042384,"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."}}