Collaboration to discover novel targets and advance new programmes across MASH and cardiomyopathies.
AstraZeneca today announced that it has entered into a new strategic drug discovery collaboration and licensing agreement with insitro, a leading artificial intelligence (AI) therapeutics company. Using advanced AI systems, the collaboration will identify novel drug targets and advance the design of new therapeutics for patients for metabolic dysfunction-associated steatohepatitis (MASH) and cardiomyopathies. These are complex heterogeneous diseases where there is significant unmet need.
Identifying the biological and genetic drivers of disease remains one of the core challenges in drug discovery. insitro will apply its Virtual Human™ AI platform to identify causal disease biology across both indications and advance AstraZeneca-nominated targets from discovery through to development candidate. This AI platform brings together large-scale human and cellular data with AI-enabled target identification and medicine design, generating insights to inform the discovery of novel therapeutic candidates. AstraZeneca will use its leading clinical development and regulatory expertise to advance novel medicines that address the underlying drivers of disease.
Sharon Barr, Executive Vice President and Head of BioPharmaceuticals R&D, AstraZeneca, said: "We know that disease biology is incredibly complex, and one of the most critical decisions in R&D is selecting the right target. This strategic collaboration underscores our commitment to maximising the potential of cutting-edge AI to tackle the root cause of disease. Partnering with insitro, we will use advanced AI to identify the biological drivers of disease to support the rapid discovery of high-quality novel targets, advancing our ambition to deliver the next generation of medicines to patients faster."
Daphne Koller, Founder and CEO of insitro, said: "MASH and cardiomyopathies are prevalent, underdiagnosed diseases where high-content data holds immense signal for uncovering disease drivers. By applying AI to these complex datasets, we can unlock greater discovery power and reveal novel genetic insights. Our platform simultaneously deconvolutes disease biology and identifies causal drivers of disease pathologies. Partnering with AstraZeneca allows us to pair our deep biological precision with their deep pharmaceutical expertise and scale with potential accelerated advancement of novel programmes through development and to patients."
Financial considerations
Under the terms of the agreement, insitro will receive an upfront payment of $40 million, and is also eligible for up to approximately $1.46 billion in potential development and commercial milestones, plus potential single digit royalties based on global commercial sales.
AstraZeneca will have exclusive worldwide rights to advance selected programmes identified under the collaboration.
AstraZeneca (LSE/STO/NYSE: AZN) is a global, science-led biopharmaceutical company that focuses on the discovery, development, and commercialisation of prescription medicines in Oncology, Rare Disease, and BioPharmaceuticals, including Cardiovascular, Renal & Metabolism, and Respiratory & Immunology. Based in Cambridge, UK, AstraZeneca's innovative medicines are sold in more than 125 countries and used by millions of patients worldwide. Please visit astrazeneca.com and follow the Company on Social Media @AstraZeneca.
AstraZeneca in CVRM Cardiovascular, Renal and Metabolism (CVRM), part of BioPharmaceuticals, forms one of AstraZeneca's main disease areas and is a key growth driver for the Company. By following the science to understand more clearly the underlying links between the heart, kidneys, liver and pancreas, AstraZeneca is investing in a portfolio of medicines for organ protection by slowing or stopping disease progression, and ultimately paving the way towards regenerative therapies. The Company's ambition is to improve and save the lives of millions of people, by better understanding the interconnections between CVRM diseases and targeting the mechanisms that drive them, so we can detect, diagnose and treat people earlier and more effectively.
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