Reactwise Raises $3.4 Million in Pre-Seed Funding to Transform Pharmaceutical R&D with AI-Driven Robotics
Reactwise, a leading innovator of AI-driven robotic laboratories, has raised pre-seed funding of $3.4 million, including a competitive grant from Innovate UK, to further research and development in pharmaceutical manufacturing.
The funding round had the support of some of the most renowned entities, such as Y Combinator, the government of the United Kingdom, and a list of leading venture capital firms and angel investors. The investment will further accelerate the pace of AI-enabled solutions for enabling sustainable innovation across the pharmaceutical industry.
Reengineering Drug Manufacturing and Development
Reactwise addresses a major challenge in pharmaceutical development: the slow and inefficient trial-and-error process in drug manufacturing.
Alexander Pomberger, CEO and Co-Founder of ReactWise, said, “However, the drug development pipeline is often driven by trial-and-error and held up for many months during the identification of scalable manufacturing processes, delaying clinical trials.”
He added, “Our AI-powered models learn from historical data, cutting up to 95% of experimental work and accelerating these workflows by 30x.”
AI-Driven Robotics in Pharmaceutical R&D
Since completing Y Combinator’s summer 2024 batch, Reactwise has made significant strides. The company has launched its improved software and runs 12 pilot studies with leading pharmaceutical companies.
Reactwise’s robotic laboratory has also screened thousands of chemical reactions, contributing to developing proprietary reactivity models. Reactwise is positioning itself as a key intelligence layer in next-generation pharmaceutical R&D by integrating seamlessly with automated lab infrastructure and electronic lab notebooks.
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Revolutionizing Drug Manufacturing with AI
Reactwise’s innovative technology offers a transformative solution to pharmaceutical R&D. As explained by Daniel Wigh, CTO and Co-Founder, the company’s AI system enables chemists to input a drug molecule and receive an optimized, scalable manufacturing process. The process is carried out independently in an autonomous laboratory, which optimizes conditions in real time. Not just does this strategy accelerate drug production, but it enhances sustainability by minimizing chemical waste, energy use, and raw materials expenses.
