Back

The Immunogenicity Database Collaborative (IDC): A Standardized, Publicly Available Database for Clinical Immunogenicity Observations and Insights

The Immunogenicity Database Collaborative (IDC), ; Agnihotri, S.; Gonzalez-Nolasco, B.; Monian, B.; Pattijn, S.; Ackaert, C.; Wu, P.; Kettenberger, H.; Tourdot, S.; Hickling, T.; Hu, Z.; Higgs, R. E.; Leventhal, D. S.

2025-12-17 pharmacology and toxicology
10.64898/2025.12.08.692993 bioRxiv
Show abstract

The incidence and impact of anti-drug antibodies (ADAs) against biotherapeutics remain difficult to predict, limiting efforts to mitigate immunogenicity risk prior to clinical trials. Existing data are fragmented across disparate sources with inconsistent definitions, representing a key barrier to progress in the field. Here, we present the Immunogenicity Database Collaborative (IDC) and its release of the Immunogenicity Database (DB) V1: a structured clinical immunogenicity dataset integrating therapeutic characteristics, sequence, and patient cohort-level data from publicly available sources. The dataset includes 4,146 ADA datapoints, 1,788 cohorts, 727 clinical trials and 218 therapeutics. We highlight trends in ADA incidence, evaluate sources of variability, and identify driving factors of immunogenicity risk. This work provides a foundational resource to standardize and support immunogenicity risk assessment across the industry. It also provides an initial data architecture and invites the research community to contribute towards future expansions of the database into key areas of interest to the field.

Published in Frontiers in Immunology (predicted rank #13) · training set

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.