Rowan Announces $2.1M to Build Machine Learning-Powered Computational Tools for Chemistry

Startup aims to replace expensive, slow, quantum mechanics simulations with inexpensive, fast machine-learned potentials.

BOSTON, Dec. 9, 2024 — Rowan, a company building molecular design and simulation tools for scientists, today announced $2.1 million in pre-seed funding. Investors include Pillar VC, AI Grant, and angel investors.

"Modern algorithms and machine learning models can dramatically accelerate scientific R&D by replacing resource-intensive experiments," said Corin Wagen, PhD, CEO and founder of Rowan. "As Rowan helps more scientists use modern computational techniques, our company will accelerate the speed of scientific progress across drug discovery and materials science."

Rowan makes it possible for any scientist to run modern simulation workflows, not just experts in computational chemistry. Users can design, simulate, and analyze molecules and materials through the company's web platform. Rowan's capabilities include:

• Modern ML-based methods: Rowan's platform combines rigorous physics-based calculations with modern AI-based algorithms to accelerate accurate simulation.
• Predicting pKa values: Users can predict the acidity of small molecules with Rowan's pKa workflow. Rowan uses AIMNet2, a machine-learned interatomic potential, to obtain fast and reasonable pKa values with minimal empiricism.
• Finding low-energy conformers: Rowan uses fast, low-level methods to generate conformers, and then scores each structure with a more accurate final method.
• Custom scientific solutions: Rowan works with companies to build custom computational solutions tailored to specific problems and domains.

"Rowan is now my first port of call for QM modeling," said Lewis Martin, chief scientific officer of OpenBench. "The attention paid to pragmatic and benchmarked methods means the software suite is practical to incorporate into our workflows."

"Today, biotech and pharma companies can invest hundreds of millions of dollars developing a single drug, and conventional simulations struggle to accelerate this process," said Tony Kulesa, partner at Pillar VC. "Rowan is building the next generation of powerful computational tools to save these companies an extraordinary amount of time and money as they advance their research."

About Rowan
Rowan is building machine learning-powered computational tools to accelerate chemical innovation. To learn more, visit rowansci.com.