ALP AI Advances Safer Antibody Drug Development Through AI-Driven Immunogenicity Prediction
ALP AI, a biotech AI startup with Luxembourg roots, is addressing one of the most persistent challenges in drug development: immunogenicity. By predicting and reducing anti-drug antibody (ADA) risk early in development, the company aims to make antibody therapeutics safer and more reliable.
26/02/2026
Antibody therapies have transformed treatment across oncology, immunology and rare diseases — but many biologics still trigger anti-drug antibodies (ADAs). When this happens, drugs can lose effectiveness or cause side effects, sometimes forcing treatment to stop. Current in silico and in vitro approaches remain limited in their ability to predict clinical immunogenicity.
ALP AI’s technology addresses this gap with a platform that combines human tonsil-derived organoids and machine learning to model immune responses more realistically.
By analysing antibody sequence and structure holistically — rather than focusing on individual epitopes — the approach helps teams identify immunogenicity risk earlier and make better lead-selection and optimisation decisions.
Immunogenicity remains one of the key hidden risks in biologics development,” says Lucas Schaus, Co-Founder and CSO of ALP AI. “Our goal is to provide developers with a reliable, quantitative assessment early enough to influence design decisions.
The company’s scientific foundation traces back to Luxembourg. ALP AI’s CSO and inventor of the underlying technology is originally from Luxembourg and now based in California, strengthening transatlantic ties in biotech innovation.
ALP AI is currently engaging in exploratory collaborations with biotech and biologics developers seeking to de-risk antibody pipelines. Companies developing antibodies or novel biologics are invited to connect with ALP AI to explore potential collaboration opportunities.
