Rediscovering Known Biology: Validating the Aignostics-Bayer Target ID Platform

Identifying the right therapeutic target for the right patient population is one of the most critical challenges in oncology drug development. The value of any AI-driven target identification platform depends on the trust placed in its outputs, which rests in part on biological credibility: the ability to independently recover established biology before surfacing novel findings.

Aignostics and Bayer have jointly developed an indication-agnostic Target ID Platform that integrates proteomics, transcriptomics, epigenomics, and imaging data into a single multimodal AI model. Applied to a lung squamous cell carcinoma (LUSC) cohort, the Platform independently rediscovered NRF2 pathway activation — a well-characterized disease mechanism in LUSC — across DNA, RNA, and proteomics, without any prior knowledge of pathway biology during model training. This case study describes methodology and findings that support the Platform's ability to surface novel therapeutic targets.