YC-Backed ReactWise is Leveraging AI to Accelerate Drug Production

YC-Backed ReactWise is Leveraging AI to Accelerate Drug Production

AI is making waves in chemistry, and YC-backed ReactWise, based in Cambridge, U.K., is at the forefront. The startup applies AI to accelerate chemical manufacturing, a crucial step in scaling up drug production for clinical trials.
Image Credits: ReactWise

AI is making waves in chemistry, and YC-backed ReactWise, based in Cambridge, U.K., is at the forefront. The startup applies AI to accelerate chemical manufacturing, a crucial step in scaling up drug production for clinical trials.

ReactWise offers an “AI copilot for chemical process optimization,” which it claims can speed up the traditionally slow trial-and-error approach by 30 times.

Making drugs is like cooking,” explained co-founder and CEO Alexander Pomberger. “You need the right recipe to achieve high purity and yield.”

Historically, pharmaceutical companies have relied on trial-and-error or expert intuition to refine manufacturing processes. ReactWise introduces automation to reduce the number of iterations needed to optimize drug synthesis.

The company envisions a future where AI can achieve “one-shot prediction“—identifying the best experiment immediately without multiple cycles of refinement. Pomberger estimates this breakthrough could arrive within two years.

Even before reaching that milestone, ReactWise’s machine-learning models already cut costs and time by minimizing the number of experiments required in drug development.

Automating Chemical Synthesis with AI

The idea stemmed from my background as a chemist and my experience in Big Pharma, where I saw firsthand how tedious and reliant on trial and error the industry is,” he explained. He noted that the company is essentially distilling five years of academic research—his Ph.D. focused on automating chemical synthesis through robotic workflows and AI—into what he describes as “a straightforward software solution.”

ReactWise’s technology is built on data from thousands of chemical reactions conducted in its labs, feeding its AI-driven predictions. The startup used a “high throughput screening” approach, testing 300 reactions simultaneously to accelerate data collection for training its AI models.

In pharma, there are only a handful of reaction types that are repeatedly used,” Pomberger explained. “We’ve set up a lab to generate thousands of data points on these key reactions, training foundational reactivity models that deeply understand chemistry. This allows pharmaceutical companies to develop scalable processes without starting from scratch.”

Accelerating Chemical Insights with AI

ReactWise began compiling reaction data in August and expects to complete this phase by summer, aiming to reach 20,000 chemical data points covering essential reactions. Traditionally, obtaining a single data point takes a chemist one to three days, making this process both time-intensive and costly.

Currently, the company focuses on optimizing manufacturing processes for small-molecule drugs, which are used to treat a wide range of diseases. However, the technology has broader applications, as ReactWise is also collaborating with material manufacturers on polymer-based drug delivery systems.

The company’s automation strategy includes software that integrates with robotic lab equipment to enhance precision in drug manufacturing. While ReactWise doesn’t produce robotic lab hardware itself, its software can operate such systems if a client has them in place.

Founded in July 2024, the U.K.-based startup has 12 pilot trials underway with pharmaceutical companies. Pomberger anticipates the first full-scale deployments of its subscription-based software later this year, with some trials involving major pharmaceutical firms.


Read the original article on: TechCrunch

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