Cheiron has raised $8 million in seed funding to develop an artificial intelligence-native operating system for managing drug development programs. The round was led by Menlo Ventures, with backing and strategic support from investors and industry leaders including Moderna co-founder and MIT Institute Professor Robert Langer, former Pfizer Chief Medical Officer Freda Lewis-Hall, Chai Discovery co-founder and CEO Josh Meier, and former Starbucks CEO Laxman Narasimhan.
Cheiron is developing a software platform that models the current state of a drug program as one connected system.
Drug development teams rely on large volumes of information generated across laboratory experiments, clinical trials, regulatory submissions, scientific publications, patents, competitive research and prior internal decisions.
That information is often distributed across documents, databases and individual employees. When a team needs to make an important development decision, researchers may need to reconstruct the program’s history before they can determine which evidence supports or challenges a particular strategy.
Cheiron is seeking to organize these materials into a continuously updated representation of a drug program’s claims, evidence, assumptions, risks, decisions and commitments.
The company’s goal is to give development teams a shared understanding of why a therapy is advancing, which questions remain unresolved and what evidence could change the program’s direction.
At the center of Cheiron’s platform is its proprietary Life Sciences Knowledge Graph.
A knowledge graph organizes information by representing relationships among data. In drug development, those connections could include relationships among a biological target, experimental results, clinical outcomes, regulatory precedents, patents, and competing therapies.
Cheiron’s knowledge graph brings together biomedical, clinical, regulatory, patent and commercial information within a single model.
The platform is designed to support the kinds of comparisons and inferences drug developers make during a program. A team could use it to compare a proposed clinical trial design with prior regulatory decisions, identify inconsistencies between a competitor’s reported data and its patents, or test a scientific assumption against a wider body of evidence.
Drug development programs can cost hundreds of millions or billions of dollars and take years to complete. Decisions made early in the process can affect clinical trial design, manufacturing strategy, regulatory positioning and the likelihood that a therapy ultimately reaches patients.
By creating a structured record of the evidence behind those decisions, Cheiron aims to reduce the time teams spend searching for context and allow scientists and executives to concentrate more heavily on judgment.
The system could also help organizations preserve institutional knowledge when employees leave a company or transition between programs. Important reasoning that might otherwise remain in meeting notes, emails or individual memories could become part of the program’s connected record.
Cheiron plans to use the seed funding to accelerate development of its Life Sciences Knowledge Graph and expand the platform across clinical, regulatory and strategic workflows.
The company will also grow its engineering, product and life sciences teams. In addition, Cheiron is adding scientific and operating advisors with experience building and leading drug development programs.
Cheiron is positioning its platform as an operating layer for the drug program itself rather than another isolated research or document-management product.
The company believes that representing a therapy’s complete development history in software can help teams identify contradictions, evaluate risks and make decisions without repeatedly reconstructing the same information.
