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CytoReason Extends multi-Year Partnership with Pfizer

Will continue to provide its artificial intelligence technology for Pfizer’s drug development programs.

CytoReason has extended its multi-year partnership with Pfizer to use CytoReason’s artificial intelligence technology for Pfizer’s drug development programs.
 
Under the terms of the agreement, Pfizer will make a $20 million equity investment, have options to license CytoReason’s platform and disease models, and fund supplementary project support, in a deal potentially worth up to $110 million over the next five years.
 
Since launching the collaboration in 2019, Pfizer has used CytoReason’s biological models in its research to enhance the understanding of the immune system, as it develops innovative drugs for immune-mediated and immuno-oncology diseases. CytoReason’s platform has provided Pfizer with multiple insights in research and development programs across over 20 diseases.
The new research agreement and investment will support the development of additional disease models and the creation of high-resolution models, spanning across a number of therapeutic areas.
 
“We’re pleased to expand our strategic collaboration with CytoReason,” said Mikael Dolsten, chief scientific officer and president, Pfizer. “We look forward to continuing our work with the company’s leading scientists, and to leveraging its cutting-edge platform. CytoReason’s biological data allows us to gain deeper insight into the best drug development pathways for patients, resulting in more informed decisions that are timely and cost-effective.”
 
“Pfizer has been a strategic partner of CytoReason since 2019, and we are thrilled to scale our collaboration as one of Pfizer’s trusted AI partners for accelerating drug development,” said David Harel, CEO and co-founder of CytoReason. “This partnership is advancing a significant shift in the biotech industry, and helping drive future R&D for pharmaceutical companies as they continue to use machine learning to develop treatments more efficiently. Transforming complex data into useful actionable insights will potentially provide leading researchers and scientists a roadmap to further develop their drug portfolios.”

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