Aitia, the leader in computationally discovering and applying new knowledge of biological causes of disease to pharmaceutical discovery and development, announced a collaboration with Gustave Roussy, the premier cancer research institute in Europe. The new partners will collaborate to transform Gustave Roussy’s extensive cancer patient data into human “Gemini Digital Twins” – computer-based in silico models that reveal the hidden underlying causes of complex diseases like cancer to drive the discovery and clinical development of effective new therapies.
Cancer (the overall name given to >200 different diseases characterized by out-of-control cell growth) is second only to cardiovascular disease as a major cause of death worldwide. While overall cancer death rates have decreased in recent years, cancer rates have been rising in young adults, and incidence rates are returning to pre-COVID pandemic levels. Although there have been a few notable successes, most cancers still have limited if any effective treatment options, including many brain, pancreatic and ovarian cancers. The Gustave Roussy-Aitia agreement announced today seeks to bring an end to that devastating reality for many cancer types with ongoing high unmet medical need.
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“If we identify the specific cancer-causing changes buried in the massively complex biology that leads to diseases like cancer, we can also identify a clear path to the ‘next generation’ of effective therapeutic interventions,” said Colin Hill, CEO and co-founder of Aitia. “Informed by Gustave Roussy’s extensive database of de-identified human multiomic and patient outcome data, our causal AI discovery engine and the Gemini Digital Twins it builds, reveals the fundamental knowledge needed for successful drug discovery and clinical development.”
“Gustave Roussy is excited to work with Aitia to realize our shared mission of accelerating and applying new knowledge of cancer biology to its successful treatment,” said Prof. Fabrice Barlesi, CEO of Gustave Roussy. “Aitia’s ability to accurately model complex biological systems from de-identified human multiomic and patient outcome data should give us a significant advantage in the battle against these devastating diseases and bring renewed hope to cancer patients and their families worldwide.”
SOURCE: PRNewswire