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Sam Altman-backed Startup Partners with Microsoft to Enable the AI Infrastructure for Drug Discovery

A new five-year commercial agreement and go-to-market collaboration aims to merge 1910 Genetics’ comprehensive computational and biological data with Microsoft’s HPC platform, Azure Quantum Elements. This union is expected to provide researchers worldwide access to a specialized cloud platform designed to expedite scientific discovery by leveraging the combined strengths of AI and HPC.

Founded in 2018 and based in Cambridge, Massachusetts, 1910 Genetics merges AI, computational analysis, and biological automation to expedite the creation of small-molecule and protein therapeutics. In 2021, the company raised a combined Seed and Series A funding of $26.1M backed by M12-Microsoft’s Venture Fund, Playground Global, OpenAI’s Sam Altman, and other leading investors.

By merging AI-driven drug design with wet lab automation, the company aims to enhance productivity, reduce failure rates in pharmaceutical R&D, and improve the efficiency of drug discovery processes. Leveraging its multi-platform engines, ELVIS™ and ROSALYND™, 1910 Genetics is capable of generating novel drug candidates more swiftly and cost-effectively, enhancing success probabilities compared to conventional pharmaceutical approaches. 

The company’s technology is modality-agnostic and supports the entire early drug discovery process, from novel hit discovery through lead optimization. 1910 Genetics is actively applying its technology to various therapeutic areas, including neuroscience, infectious diseases, immunology, and oncology.

“We are thrilled to be collaborating with 1910 Genetics to bring their pioneering AI drug discovery engines to Azure Quantum Elements,” said Jason Zander, Executive Vice President of Strategic Missions and Technologies at Microsoft.

Building on the Lab Automation Trend

For initial discovery, 1910 Genetics utilizes SUEDE™, a gigascale virtual screening platform capable of evaluating 14 billion molecules in under six hours to pinpoint potential hit compounds. This efficiency starkly contrasts with conventional methods that take up to six months for physical high throughput screening (HTS), which has a success rate of less than 0.01%.

As the process advances from hit discovery to lead generation, the company employs BAGEL™, a generative chemistry platform that accelerates the development of lead compounds from identified hits, reducing a process that could take up to 24 months to just two months. 

Additionally, 1910 Genetics emphasizes the importance of balancing a drug candidate’s potency with its absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile. To achieve this, from the outset of discovery and particularly during lead optimization, CANDID™, a physical property prediction platform, is used for multi-parameter optimization.

These AI platforms are seamlessly integrated with the company’s in-house biological automation wet lab platform through cloud computing. This setup conducts in vitro biochemical and cell-based assays on drug candidates, creating a feedback loop to the AI platforms and establishing a unique and proprietary data set. 

For protein design, 1910 Genetics is developing ROSALYND™, aimed at refining, predicting, and designing 3D protein structures more rapidly, affordably, and accurately than traditional methods like X-ray crystallography.

This capability can help streamline the process for pharmaceutical R&D teams, reducing both the time and cost associated with developing novel lead molecules for a broad spectrum of therapeutic targets and diseases, including neuroscience, infectious diseases, autoimmune diseases, and cancer.

Realizing that AI-driven transformation of drug discovery is only possible with sufficient amount of biological data, more companies are investing into building proprietary highly automated laboratories for preclinical experimentation. 

For instance, in 2022 BiopharmaTrend reported that Insilico Medicine raised a $60 million Series D to invest into building a next-gen robotic lab in China, the facility that was launched in January 2023. Other notable AI-driven drug discovery companies in this lab automation space include Arctoris, Recursion Pharmaceuticals, and Insitro, to name a few. 

Microsoft’s Increasing Footprint in Science

In June 2023, Microsoft introduced Azure Quantum Elements (AQE), a supercomputer for chemistry that contains AI models trained on hundreds of millions of molecules. It is designed as an expert in chemistry and materials science, and, using generative AI, a “Copilot for Azure Quantum” to write code and answer tough questions for computational chemists and material scientists.

Just six months after launching, on January 9, 2024, Microsoft announced its first concrete case study in Azure Quantum Elements for chemistry, demonstrating that Azure Quantum Elements 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, paving the way for the next generation of sustainable batteries.

This landmark discovery is a first-of-its-kind in the application of AI for Scientific Discovery for the design of new materials and foreshadows the transformative potential of Azure Quantum Elements to increase productivity in more industries, including pharmaceuticals. 

Building the Infrastructure Layer for Drug Discovery

With today’s announcement, 1910 Genetics and Microsoft expand their relationship into a commercial agreement that combines the biotechnology company’s massive computational and wet lab biological data, robotics-driven laboratory automation, and multimodal AI models for drug discovery with Azure Quantum Elements. 

Together, the companies will build arguably the most powerful, fully integrated AI-driven drug discovery and development platform, with the goal of demonstrating significant cost and time savings for pharmaceutical companies engaged in the R&D of small and large molecule therapeutics for a variety of target classes and disease areas. 

“Azure Quantum Elements brings the most powerful AI engine created to facilitate this new AI for Scientific Discovery wave,” said Zulfi Alam, Corporate Vice President of Quantum at Microsoft. Together with 1910, Microsoft is charting a course for a billion-dollar business in AI-driven drug discovery and development.

“1910 Founder and CEO Jen Nwankwo adds: We believe that as the biopharma industry prepares for the inevitable transition from human-intensive, rational drug design to AI-enabled discovery with generative AI at the frontier, the winning companies will, like 1910, be those who innovate across the entire drug discovery tech stack to use optimized, high-performance computing today and quantum computing tomorrow, in concert with high-throughput lab automation to generate large-scale, multimodal data sets. By bringing 1910 and Azure Quantum Elements together, we enable biopharma companies worldwide to realize the potential of AI and reverse decades of declining R&D productivity.”

Potential customers interested in learning more about 1910 Genetics’ small and large molecule drug discovery platform in Azure Quantum Elements can sign up here for early access.

Topics:
Emerging Technologies