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The world's first AI-maximalist pharma company
An AI-maximalist pharma platform. We use agents to buy drugs, run clinical trials, and sell for a profit. 10x faster and 20x leaner than incumbents. Sourcing Agent: Mines public/private databases and unstructured global data to surface overlooked preclinical candidates. Scientific Agent: Runs comp bio models (ESM-3, RFdiffusion, Boltz-2, AlphaFold) to assess safety and efficacy in silico. Commercial Agent: Analyzes FDA incentives, pricing dynamics, TAM, competitive landscape, and payer alignment. Clinical Agent: Runs digital twin simulations, evaluates CRO/CMC risk, and builds trial plans to Phase 1. PoS Agent: Evaluates the most critical factors that impact the likelihood of clinical trial success. Built by 2 Stanford CS students who have built 3 startups together before.
Convexia is an AI-powered platform that sources and evaluates overlooked drug assets, combining an end-to-end AI stack with human expert review to accelerate drug discovery decisions. It offers a modular suite of AI agents for asset discovery, scientific evaluation, market insight, and risk assessment, with live humans validating and final go/no-go decisions.
Convexia provides an end-to-end AI-driven asset discovery and evaluation workflow: 1) Asset Discovery Agent scans global sources to surface high-potential drug assets; 2) Scientific Evaluation Stack runs in-silico simulations using 50+ models to assess binding, toxicity, ADME/PK, immunogenicity, and mechanistic fit; 3) Specialist Human Review where PhDs validate biology, risks, and translatability; 4) Market Insight Agent ranks assets by unmet need, competitive landscape, IP, reimbursement signals, and financial projections; 5) Operational Risk Agent uses digital twin simulations to score trial execution risk; 6) Probability of Success Model informs Go/No-Go decisions; 7) Final Human Review with a live KOL roundtable for final determination. Assets are sourced globally, and users can license individual components or pilot the platform.
Who it’s for: Pharma, biotech, and investment groups seeking to source, evaluate, and accelerate overlooked drug assets; organizations looking to license modular AI components for drug asset discovery and diligence.
Funding/backed by Stanford and YC; active pilots and licensing of platform components; seeking collaborators and discovery partners
Building agents to find and acquire early-stage drug assets. Stanford CS + Bio Built 3 healthtech startups (telemedicine, addiction recovery, hydroponic systems). Published 4 papers on molecular dynamics. Biotech VC and consulting experience.
Building agents to find and acquire early-stage drug assets. Stanford CS + Econ Built 3 healthtech startups (telemedicine, gamified recovery, hydroponic systems).
AI agents that search and evaluate early-stage drugs
Convexia builds AI agents to source early-stage drugs, perform scientific diligence, model markets, simulate clinical trials, and handle business development to buy, test, and sell drug candidates. They are running pilots with early customers to accelerate search and evaluation processes for pharma and biotech partners.
AI drug discovery platform for neurotherapeutics
Agent Platform for Life Sciences
