Microsoft and biotech company 1910 Genetics are partnering to create an AI-driven drug discovery and development platform. The collaboration aims to reverse the decline in pharmaceutical R&D productivity by using Microsoft’s high-performance computing platform, Azure Quantum Elements. The platform will combine 1910’s computational and biological data, laboratory automation, and AI models for drug discovery. The technology is expected to accelerate the design of therapeutics and will be offered to various institutions. Jason Zander, Executive Vice President of Strategic Missions and Technologies at Microsoft, and Jen Nwankwo, Founder and CEO of 1910 Genetics, expressed excitement about the collaboration’s potential.
1. Microsoft and 1910 Genetics: A Collaboration for AI-Driven Drug Discovery
Microsoft and 1910 Genetics have announced a five-year commercial agreement to develop an integrated platform for drug discovery and development. This platform will leverage advanced artificial intelligence (AI) and high-performance computing (HPC) to address the long-standing issue of declining productivity in pharmaceutical research and development (R&D). The collaboration aims to provide a solution that will enable faster and more cost-effective generation of therapeutics.
1910 Genetics, a biotechnology company, has been utilizing a multimodal AI platform powered by laboratory automation to advance small and large molecule drug discovery. The company will now combine its extensive computational and biological data, robotics-driven laboratory automation, and AI models for drug discovery with Microsoft’s HPC platform, Azure Quantum Elements. This collaboration will result in a cloud platform specifically designed to accelerate scientific discovery at the intersection of AI and HPC.
The Role of AI in Scientific Discovery
The traditional scientific method, which has remained largely unchanged since the 17th century, relies on slow, human-intensive, and iterative cycles of observation, hypothesis, experimentation, and analysis. AI offers an opportunity to compress these cycles, accelerate the time from observation to discovery, and reduce the need for experimentation.
This shift towards AI for Scientific Discovery could transform discovery across all industries, particularly the pharmaceutical industry. Currently, it takes an average of 12 to 15 years and costs over $2 billion to develop a new drug. To harness the potential of AI for pharmaceutical R&D, a new end-to-end drug discovery and development process must be reimagined using AI. This process must overcome the challenges of fragmented and disparate data, create new types of data at scale, and integrate massive parallel data, AI, and laboratory automation.
1910 Genetics: Harnessing AI to Boost R&D Productivity
1910 Genetics was established in 2018 with the aim of overcoming the pharmaceutical industry’s data scarcity problem. The company generates three proprietary data streams at scale: computational data using atomistic modeling and simulations, wet lab proxy biological data using next-generation sequencing, and wet lab ground truth biological data across biochemical, cellular, and in vivo assays.
The company’s state-of-the-art laboratory, powered by robotics and automation, creates massive wet lab proxy and ground truth biological data for AI training and molecular testing of synthesized drug candidates. This approach puts massive parallel data, AI, and automation in the same iterative loop. For drug discovery, 1910’s multimodal AI platform can design traditional small molecules, which make up 90 percent of approved drugs today, as well as large molecule therapeutics.
Microsoft Azure Quantum Elements: A Tool for Accelerating Scientific Discovery
Microsoft introduced Azure Quantum Elements (AQE) in June 2023 as a supercomputer for chemistry. AQE contains AI models trained on hundreds of millions of molecules, making it an expert in chemistry and materials science. Using generative AI, AQE can write code and answer tough questions for computational chemists and material scientists.
Just six months after its launch, Microsoft announced a case study demonstrating that AQE used advanced AI to screen 32.6 million candidates in record time to discover and synthesize a new material that could reduce the use of lithium in batteries by 70 percent. This discovery highlights the potential of Azure Quantum Elements to increase productivity in various industries, including pharmaceuticals.
Building the Infrastructure for AI-Driven Drug Discovery
The collaboration between 1910 Genetics and Microsoft began in 2021 when M12-Microsoft’s Venture Fund led a $22M Series A investment in 1910 Genetics. With the recent announcement, the companies will expand their pilot collaboration into a five-year commercial agreement that combines 1910 Genetics’ computational and biological data, robotics-driven laboratory automation, and AI models for drug discovery with Azure Quantum Elements.
The companies aim to build the infrastructure layer on which pharmaceutical and R&D teams across the world can begin, accelerate, and realize their transition to AI-driven drug discovery. This collaboration will enable biopharma companies worldwide to harness the potential of AI and reverse decades of declining R&D productivity.
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