Rahul Vijayan
| Rahul Vijayan | |
| Occupation | Co-founder and CTO of Convexia |
|---|---|
| Known for | Convexia, AI-driven pharmaceutical company |
Rahul Vijayan is an Indian-American entrepreneur and technologist who is the co-founder and chief technology officer (CTO) of Convexia, a pharmaceutical company that describes itself as "AI-maximalist," using artificial intelligence agents to discover, evaluate, and develop drug assets. Convexia is a participant in Y Combinator's Summer 2025 batch and is based in San Francisco, California.[1]
Early Life and Education
Vijayan is of Indian-American background and studied computer science at Stanford University. According to Y Combinator's company profile, he and co-founder Ayaan Parikh had previously built three startups together before founding Convexia.[2] Further details regarding his specific program of study, graduation year, and the nature of his earlier ventures have not been publicly disclosed.
Career
Convexia
Vijayan co-founded Convexia alongside Ayaan Parikh, who serves as the company's chief executive officer. The two Stanford computer science students had collaborated on multiple prior ventures before turning their attention to the pharmaceutical sector. Vijayan leads the company's technical direction as CTO, overseeing the design and development of Convexia's end-to-end artificial intelligence platform for drug discovery and development.[3]
Convexia's stated mission is to use autonomous AI agents to acquire overlooked drug assets, run clinical trials, and sell them for profit, claiming to operate at speeds ten times faster and with twenty times less overhead than traditional pharmaceutical companies.[4] The company describes its approach as "AI-maximalist," meaning that artificial intelligence is positioned as the primary driver of decisions across the full drug development pipeline, with human expert review incorporated at key validation stages rather than as the default mode of operation.
The platform is organized around a series of specialized agents. A Sourcing Agent mines public and private databases as well as unstructured global data to identify overlooked preclinical drug candidates, including abandoned pharmaceutical intellectual property. A Scientific Agent runs computational biology models — including ESM-3, RFdiffusion, Boltz-2, and AlphaFold — to assess drug safety and efficacy through in silico simulations covering binding affinity, toxicity, ADME/PK properties, immunogenicity, and mechanistic fit. A Commercial Agent analyzes FDA incentives, pricing dynamics, total addressable market, competitive landscape, and payer alignment. A Clinical Agent conducts digital twin simulations, evaluates contract research organization (CRO) and chemistry, manufacturing, and control (CMC) risk, and builds trial plans through Phase 1. A Probability of Success Agent evaluates critical factors impacting clinical trial outcomes, benchmarking against historical analog deals. Each stage incorporates human expert review, including PhD-level scientific validation and a final roundtable with key opinion leaders.[5]
Convexia was accepted into Y Combinator's Summer 2025 batch, one of the most competitive startup accelerator programs in the world. In July 2025, the company's official debut was covered by The American Bazaar, which described Convexia as an "AI-maximalist pharma company" using autonomous agents to discover, evaluate, and develop overlooked drug assets. No funding figures or valuation data had been publicly disclosed as of that time.
References
- ↑ "Convexia – Y Combinator". 'Y Combinator}'. Retrieved 2025-07-01.
- ↑ "Convexia – Y Combinator". 'Y Combinator}'. Retrieved 2025-07-01.
- ↑ "Convexia – Y Combinator". 'Y Combinator}'. Retrieved 2025-07-01.
- ↑ "How Convexia Works". 'Convexia}'. Retrieved 2025-07-01.
- ↑ "How Convexia Works". 'Convexia}'. Retrieved 2025-07-01.