BullFrog AI Holdings, Inc. unveiled a pivotal white paper, “Why Drug Discovery Fails and How AI is Changing the Equation,” which fundamentally re-evaluates the landscape of pharmaceutical and biologic development. At its core, the paper introduces bfLEAP™, BullFrog AI’s proprietary artificial intelligence and machine learning platform, engineered to address the alarmingly high failure rate—nearly 90%—of drug candidates in conventional clinical trials. In a burgeoning $200B+ market often characterized by opaque "black-box" AI solutions, bfLEAP™ distinguishes itself by delivering biologically grounded, composition-aware analytics, providing biopharma teams with unprecedented confidence in predicting therapeutic success.

The critique laid out in the white paper highlights the shortcomings of traditional R&D approaches, advocating for a forward-looking, biology-native AI framework to reverse current trends. Built on technology originating from the Johns Hopkins University Applied Physics Lab, bfLEAP™ is purpose-built to navigate the inherent complexity, high dimensionality, and biological non-linearity of therapeutic development. Unlike generic AI models that struggle with the unique characteristics of biomedical data, bfLEAP™ excels by leveraging causal AI, combinatorial modeling, and proprietary techniques to effectively manage sparse, high-dimensional information. Crucially, its ability to apply composition-aware transformations corrects for misleading patterns often found in proportional datasets like gene expression or microbiome profiles, ensuring the detection of genuine biological signals.

This advanced platform provides actionable insights across the entire drug development lifecycle. In early discovery, it identifies targets with high mechanistic potential from molecular data. During preclinical and Phase I trials, bfLEAP™ detects patient subpopulations most likely to respond to treatment. For late-stage trials and post-market analysis, it stratifies patients by genetic and behavioral variables, optimizes endpoint design, and uncovers hidden success patterns within vast trial data. As the AI in drug discovery market is projected to exceed $35 billion by 2034, BullFrog AI strategically positions bfLEAP™ not merely as an automation tool, but as a category-defining solution that delivers scientific clarity. By offering domain-native analytics and an explainable, measurement-centric approach, BullFrog AI aims to improve the odds of therapeutic success with transparency, interpretability, and rigorous scientific integrity, standing apart from vendors who retrofit generic AI tools for complex biological challenges.