Research Triangle AI raises $28M Series B to bring its drug discovery AI platform from lab partnerships to pharmaceutical commercialization.
# Research Triangle AI Series B Funding Announcement
Research Triangle AI, a Durham-based artificial intelligence company specializing in computational drug discovery, announced today that it has raised $28 million in Series B funding to accelerate the commercialization of its AI-powered platform across the pharmaceutical industry.
The funding round was led by Sequoia Capital, with participation from existing investors Bessemer Venture Partners and In-Q-Tel. The capital will support the company's expansion from academic research partnerships into direct collaborations with major pharmaceutical and biotech organizations seeking to streamline their drug discovery processes.
Research Triangle AI's platform leverages machine learning and deep learning algorithms to predict molecular properties and optimize chemical compounds at unprecedented speed and accuracy. The technology has demonstrated its potential through partnerships with leading research institutions, where it has helped identify promising drug candidates across multiple therapeutic areas.
"This funding validates what we've known from the beginning: AI has the power to fundamentally transform how drugs are discovered," said Dr. James Chen, CEO and co-founder of Research Triangle AI. "We're moving from proving our science in academic settings to delivering real commercial value to pharmaceutical companies facing increasing pressure to innovate faster and more efficiently."
The company plans to use the Series B funding to build out its commercial team, expand its scientific staff and establish dedicated partnership programs with pharmaceutical clients.
**About Research Triangle AI**
Research Triangle AI develops artificial intelligence solutions for computational drug discovery. Founded in 2021, the company combines advances in machine learning with deep expertise in medicinal chemistry and structural biology to accelerate the identification and optimization of drug candidates. More information is available at www.researchtriangleai.com.