BullFrog AI Holdings, Inc. (NASDAQ:BFRG), a technology company focused on applying artificial intelligence and machine learning to biomedical data analysis, announced a commercial agreement with one of the world’s top five pharmaceutical companies by revenue in 2025. The partnership will use BullFrog AI’s proprietary bfLEAP® platform to identify and prioritize potential therapeutic targets for major depressive disorder (MDD), supporting the partner’s drug discovery and clinical development efforts in this area. The agreement also grants the pharmaceutical company exclusive access to a selected target candidate.
According to data from Stellar Market Research, the global MDD treatment market was valued at more than $8 billion in 2025 and is projected to expand at an average annual growth rate of nearly 5%, potentially exceeding $11 billion by 2032.
“This agreement represents strong, high-quality validation of our proprietary capabilities from a leading industry partner, and we are confident that this relationship will expand across other areas of the Customer’s research and development portfolio,” said BullFrog AI Founder and CEO Vin Singh. “Our platform provides drug developers with an end-to-end analytical tool engineered to resolve multimodal biological complexity at scale. Our bfLEAP®, bfPREP™, and bfARENAS™ integrated platform leverages causal network inference to provide drug developers a clearer path forward in the discovery and characterization of drug targets for complex disease like MDD. We look forward to continuing to build on our successful record in identifying and prioritizing portfolios and expanding our commercial partnerships.”
About BullFrog AI
BullFrog AI applies artificial intelligence and machine learning technologies to improve the drug discovery and development process. Working with leading research institutions, the company combines causal AI methods with its proprietary bfLEAP® platform to analyze complex biological datasets. The goal is to enhance therapeutic development while helping reduce the likelihood of failure during clinical trials.