Joint Efforts: ConcertAI and Bayer Set to Boost Precision Oncology with AI and ML Insights

Both teams hope to improve and expedite clinical development in oncology.

Apr 23, 2025
Joint Efforts: ConcertAI and Bayer Set to Boost Precision Oncology with AI and ML Insights
ConcertAI

By integrating data solutions and AI, the company aims to help choose programmes with the likelihood of success. ConcertAI has announced an agreement that will allow Bayer to utilize its Translational360 and AI software-as-a-service (SaaS) solutions to expedite clinical development in precision oncology using insights from AI and machine learning (ML).

The multi-year agreement will completely utilise Translational360, a recently introduced integrated research-grade longitudinal clinical molecular database.

ConcertAI notes that Translational360 merges genomic, clinical, transcriptomic and whole-slide imaging data from comprehensive molecular testing, offering genomic and phenotypical insights.

Improving Therapeutics 

Transcriptomics, a key component of biopharma translational sciences, enables researchers to know the molecular mechanisms of diseases, patient response, and inter-patient variability.

These insights are crucial for the development of new therapeutics. By integrating data solutions and AI, the company aims to help choose programmes with the likelihood of success and to design studies that are informed by multi-genomic, transcriptomic, and multi-modal data.

ConcertAI CEO Jeff Elton said: “This partnership furthers causal biological inferences where multi-modal and multi-molecular data can be integrated with AI/ML-based approaches across discovery, translation, and development, accelerating oncology pipelines, allowing our biopharma partners to deliver better medicines faster.

“This partnership builds on a multi-year history of working together and is unique in offering both tissue and liquid biopsy molecular data, allowing insights into patterns of treatment response, acquisition of resistance, AI modelling of likely success and benefit, informing programme priority and clinical study design.”