{"id":"W4385442519","doi":"10.4155/bio-2023-0135","title":"2022 White Paper on Recent Issues in Bioanalysis: Fda Draft Guidance on Immunogenicity Information in Prescription Drug Labeling, Lnp & Viral Vectors Therapeutics/Vaccines Immunogenicity, Prolongation Effect, Ada Affinity, Risk-Based Approaches, Ngs, Qpcr, Ddpcr Assays ( Part 3 – Recommendations on Gene Therapy, Cell Therapy, Vaccines Immunogenicity & Technologies; Immunogenicity & Risk Assessment of Biotherapeutics and Novel Modalities; NAb Assays Integrated Approach)","year":2023,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"","keywords":"Excellence; Bioanalysis; Regulatory science; Medicine; Computer science; Political science; Nanotechnology","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","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.00727012,0.001406761,0.00208653,0.002556514,0.0007781666,0.0002609801,0.001273772,0.00139904,0.0002646241],"category_scores_gemma":[0.0006305072,0.001125459,0.0009001604,0.004862301,0.0004827254,0.0005700464,0.0003863106,0.002281863,0.00004031476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008476942,"about_ca_system_score_gemma":0.0002597643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006085008,"about_ca_topic_score_gemma":0.003710567,"domain_scores_codex":[0.9891469,0.004678871,0.002788335,0.001562584,0.0006325661,0.00119075],"domain_scores_gemma":[0.9936322,0.001232894,0.002255884,0.002190526,0.0006070849,0.00008141466],"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":[0.01363938,0.01170966,0.279959,0.0003820773,0.01434731,0.00000276515,0.003039617,0.01861023,0.5076159,0.0003858226,0.001029919,0.1492784],"study_design_scores_gemma":[0.0365399,0.005225374,0.2114414,0.000986613,0.005513254,0.00001864107,0.004071245,0.03655902,0.5762821,0.001672723,0.1152707,0.006419019],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683501,0.0199814,0.003150075,0.002761753,0.0005685305,0.002683887,0.001835422,0.000512634,0.0001562591],"genre_scores_gemma":[0.93514,0.05203332,0.006622392,0.0004884801,0.00004511737,0.0005841175,0.004583033,0.0001163255,0.0003872859],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1428593,"threshold_uncertainty_score":0.9998974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04790826792381044,"score_gpt":0.3012674909984366,"score_spread":0.2533592230746262,"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."}}