BioPhy launched its advanced AI operating system platform designed to accelerate the process of identifying and developing potential drug candidates. The company is testing its technology with big pharmaceutical companies and has received $4.5 million in funding. Its investors include Chelsea Clinton and Caroline Kassie’s Metrodora Ventures, Audere Capital, and TRCM. In addition, Jeff Marrazzo, co-founder and former CEO of Spark Therapeutics, participated in the funding among other prominent figures in life sciences.
Dave Latshaw, a computational biomolecular and chemical engineer, co-founded BioPhy. He previously implemented over 20 AI programs in drug development at Johnson & Johnson’s Advanced Technologies Center of Excellence. This led to a $16 billion increase in annual sales, a 20% reduction in costs, and a 50% improvement in reliability. The World Economic Forum, McKinsey & Company, and the National Academy of Engineering have all recognized Latshaw’s achievements.
Latshaw commented on BioPhy’s AI platform:
“Working inside the four walls of a major pharmaceutical company, I experienced first-hand how AI can be leveraged to solve the inefficiencies that come with functions supporting drug development, including R&D, Search and Evaluation, Quality, and Regulatory. Biotechnology organizations are manually combing through scientific literature, conducting lab experiments, and using traditional statistical analysis to identify promising compounds. Inefficiencies like these in drug development mean that billions of dollars are wasted every year by even the world’s leading companies, tragically resulting in significant delays that cost lives and fewer therapies reaching patients in need. That’s why we designed BioPhy’s platform, which harnesses the power of predictive and generative AI to dramatically increase the likelihood of clinical success, improve capital efficiency and decrease development timelines for pharmaceutical companies, government agencies, and more.”
BioPhy’s AI platform uses a combination of scientific, clinical, and regulatory knowledge to assess whether a clinical trial is likely to succeed. It helps pharmaceutical companies allocate their resources efficiently and get new drugs to market faster. In the last 27 months, their technology accurately predicted the outcomes of more than 1,500 clinical trials with an 80% success rate, saving these companies millions in development costs. BioPhy’s AI also supports key aspects of drug development like clinical operations, regulatory compliance, and quality assurance.
BioPhy collaborates with top pharmaceutical and life science companies, including Ambrose Healthcare, a rare disease specialist. They help identify promising drug opportunities and design clinical trials. BioPhy has two products in its AI system for drug development:
- BioPhyRx: This AI platform creates a user-friendly space for accessing scientific and regulatory information. This service assists pharmaceutical companies at all stages of development. It does so by analyzing scientific literature, clinical trials, regulations, and quality assurance data to provide accurate and current information.
- BioLogicAI: This predictive AI engine customizes insights for life science companies during drug development. It assists with various stages, such as predicting clinical trial outcomes, selecting indications, licensing decisions, drug repurposing, asset acquisitions, and divestment. It also assesses the feasibility of preclinical assets in comparison to FDA-approved ones.
Caroline Kassie, Managing Partner at Metrodora Ventures, said in a statement:
“If there’s anything we learned from the past few years amid a global pandemic and a slew of new illnesses that have come from it, it is that the need to bring drugs to market – quickly and effectively – has never been greater. In fact, research shows that with just a 10 percent improvement in the success rates of clinical trials from AI is predicted to lead to an additional 250 novel therapies over the next 10 years. I’m excited to partner with Dave and the BioPhy team, who are dedicated to turning this prediction into a reality.”