MLCommons Joins EU-Funded AIRIS Project to Build and Benchmark Next-Generation Biomedical AI
MLCommons ·
Standardizing independent evaluation, fairness, and interpretability for mechanism-informed generative AI in healthcare The post MLCommons Joins EU-Funded AIRIS Project to Build and Benchmark Next-Generation Biomedical AI appeared first on MLCommons .
Over the summer, MLCommons was honored to be announced as a consortium member in a new research project AIRIS , (Mechanism-Informed Multimodal Generative AI for Causal and Dynamical Modeling in Biomedical Research), funded by the European Union’s Horizon Europe Program.
AIRIS unites 21 partners from Europe, Canada and the US to develop generative AI models that integrate biological knowledge and clinical data. AIRIS’ main goal is to deliver an AI collaborator that helps researchers better understand disease progression and advance personalized medicine. Over the next four years, the consortium will receive €16.9 million in funding from the Horizon Europe Program to develop a generative AI platform that builds and reasons with mechanistic models of disease, rather than relying solely on statistical patterns. The goal is to design a platform that helps researchers identify previously unknown disease pathways and develop novel scientific hypotheses.
As a global leader in AI benchmarking, MLCommons will play a central role in ensuring that AIRIS is rigorously and independently evaluated. We will lead the development of a comprehensive evaluation framework and integrated benchmark suite that measures the platform across accuracy, robustness, fairness, interpretability, and usability, with dedicated benchmarks for each of the five disease areas and for detecting bias across patient subgroups such as sex, ethnicity, and age.
“Rigorous, independent evaluation is what turns a promising AI system into one that researchers can actually trust,” says Alexandros Karargyris, Lead for the Medical working group at MLCommons. “By building open benchmarks that probe not just accuracy but fairness, robustness, and interpretability across real disease settings, we want to give the scientific community a transparent yardstick for mechanism-informed biomedical AI — and set a standard that reaches the whole community.”
Building on this framework, MLCommons will coordinate AIRIS’ iterative evaluation rounds, track progress across successive versions of the platform, and open these benchmarks to external researchers so the wider scientific community can test AIRIS on their own data, establishing AIRIS as a reference benchmark for multimodal, mechanism-informed biomedical generative AI.
In the years ahead, AIRIS seeks to transform how scientists investigate complex diseases by providing a trustworthy AI collaborator that supports every stage of the research process – moving past black-box predictions and grounding its reasoning in biological knowledge. To learn more about the AIRIS project and explore how MLCommons is advancing open benchmarks for biomedical AI, visit the AIRIS website and join the MLCommons Medical Working Group to help shape in the future of trustworthy, mechanism-informed healthcare AI.
The post MLCommons Joins EU-Funded AIRIS Project to Build and Benchmark Next-Generation Biomedical AI appeared first on MLCommons .