Miles Wang, a researcher at OpenAI known for applying artificial intelligence to accelerate scientific and biological discovery, is departing the company to establish a new venture focused on AI-driven drug development. Several additional OpenAI researchers are anticipated to join the new enterprise as it moves forward with initial funding discussions. According to sources familiar with the matter, the startup is targeting a valuation of approximately $2 billion while in talks to secure around $200 million in early-stage financing. Venture capital firm Lightspeed is reportedly leading the round. Negotiations remain ongoing, and final terms are subject to change. Wang has publicly contested specific funding figures and the current characterization of the company, though he has not provided updated details. Lightspeed declined to comment. The new venture is understood to be developing proprietary AI models aimed at identifying novel applications for existing pharmaceuticals and repurposing compounds that previously encountered hurdles in clinical trials. Targeting FDA-approved medications offers a distinct commercial advantage, as repurposed drugs bypass extensive early-stage safety testing, substantially accelerating pathways to regulatory approval and revenue generation. This strategic direction aligns with a broader wave of venture capital flowing into artificial intelligence for life sciences. The sector recently demonstrated robust investor appetite when Chai Discovery secured $400 million at a $3.8 billion valuation, and Google DeepMind spinoff Isomorphic Labs closed a $2.1 billion Series B in May. Both competitors similarly leveraged AI to map molecular interactions and predict drug efficacy. Wang joined OpenAI in 2024 after leaving Harvard University, where he was pursuing a computer science bachelor degree. His tenure at OpenAI included co-authoring research examining how large language models and advanced AI architectures can automate and expedite complex scientific workflows. The rapid commercialization of Wang venture reflects a shifting investor tolerance for young, non graduate founders in high stakes technology sectors, provided they possess demonstrable expertise in cutting edge machine learning and computational biology. As the startup formalizes its funding structure and expands its engineering team, it will navigate an increasingly competitive landscape at the intersection of generative AI and precision medicine. Success in scaling these molecular prediction models could redefine pipeline development timelines across the pharmaceutical industry, establishing new benchmarks for AI-augmented therapeutic discovery.