Owkin and the University of Pittsburgh Launch a Collaboration to Advance Cancer Research With AI and Federated Learning

Owkin, a startup that deploys AI and Federated Learning technologies to augment medical research and enable scientific discoveries, announces a collaboration with the University of Pittsburgh. This pilot leverages the high-quality datasets and world-class medical research within Pitt’s Departments of Biomedical Informatics and Pathology, as well as Owkin’s pioneering technologies and research platform. Collaborations such as these have potential to advance clinical research and drug development.

Pitt researchers led by Michael Becich, MD, PhD, Associate Vice Chancellor for Informatics in the Health Sciences and Chairman and Distinguished University Professor of the Department of Biomedical Informatics (DBMI), will team up with Owkin to develop and validate prognostic machine learning models. The pilot project will then have the potential to expand into several key therapeutic areas for the University.

Recommended AI News: Vectors Of Innovation With Conversational AI

“The Pitt Department of Biomedical Informatics in partnership with the Department of Pathology is committed to improving biomedical research and clinical care through the innovative application of informatics and best practices in next generation data sharing. This collaboration with Owkin will expand our innovations in the computational pathology space,” Dr. Becich said. “Our currently funded projects explore areas such as the intersection of genomics and machine learning applied to histopathologic imaging (computational pathology) to broaden our understanding of the role of the tumor microenvironment for precision immune-oncology.”

This partnership makes it possible for Pitt to join the Owkin Loop, a federated network of US and European academic medical centers that collaborate with Owkin to generate new insights from high-quality, curated, research-grade, multi-modal patient data captured in clinical trials or research cohorts. Loop generated insights can inform pharmaceutical drug development strategy, from biomarker discovery to clinical trial design, and product differentiation. Owkin seeks to create a movement in medicine by establishing federated learning at the core of future research.

Recommended AI News: AiThority Interview with Ben John, Chief Technology Officer at Xandr

Federated learning technologies enable researchers in different institutions and different geographies to collaborate and train multicentric AI models on heterogeneous datasets, resulting in better predictive performance and higher generalizability. Data does not move, only the algorithms travel, thus protecting an institution’s data governance and privacy. Furthermore, Owkin’s data use is compliant with local ethical body consent processes and data compliance regulations such as HIPAA and GDPR.

“We’re thrilled to launch this project with Dr. Becich and his team at Pitt. The quality and size of the University’s research cohorts in combination with the DBMI’s mandate to bring together healthcare physicians and innovative academics to work on some of the most cutting-edge science, makes this collaboration a great opportunity to develop predictive AI models and to scale other research in the future. Owkin is proud to bring their expertise in machine learning technologies and data scientists to the table to foment new clinical insights,” Meriem Sefta, Owkin Head of Partnerships said.

Recommended AI News: 5 Innovative Applications Of Quantum Computing