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The companies will join forces to use artificial intelligence (AI) and machine learning to discover and develop new treatments for two chronic diseases.
On April 30, 2019, AstraZeneca and BenevolentAI, a UK-based artificial intelligence (AI) company, announced a long-term collaboration to use AI and machine learning to discover and develop new treatments for chronic kidney disease (CKD) and idiopathic pulmonary fibrosis (IPF).
Under the collaboration, scientists from both companies will combine AstraZeneca’s genomics, chemistry, and clinical data with BenevolentAI’s target identification platform and biomedical knowledge graph-a network of contextualized scientific data (genes, proteins, diseases, and compounds) and the relationship between them. Machine learning systematically analyses data to find connections between facts and AI-based reasoning is used to extrapolate previously unknown connections. Together, the companies will interpret the results to understand the underlying mechanisms of these complex diseases and more quickly identify new potential drug targets.
BenevolentAI combines computational medicine and AI with the principles of open systems and cloud computing to aid in drug design, development, testing, and commercialization. The company has developed the Benevolent Platform, an AI discovery platform that can be used by scientists to discover novel pathways and mechanisms important in the pathophysiology of disease.
According to AstraZeneca, CKD and IPF are complex diseases in which the underlying disease biology is poorly understood and require the interrogation of vast datasets.
“The vast amount of data available to research scientists is growing exponentially each year,” said Mene Pangalos, executive vice-president and president, biopharmaceuticals R&D, AstraZeneca, in a company press release. “By combining AstraZeneca’s disease area expertise and large, diverse datasets with BenevolentAI’s leading AI and machine learning capabilities, we can unlock the potential of this wealth of data to improve our understanding of complex disease biology and identify new targets that could treat debilitating diseases.”