Uncover Drug Assets 10x faster
The world's first AI-maximalist pharma company
How Convexia Works
An end-to-end AI stack that replaces months of manual diligence with fast execution.
Asset Discovery Agent
We scan the globe for overlooked drug assets.
From preclinical biotech to abandoned pharma IP, our AI pulls in structured and unstructured data to find high-potential candidates.
Scientific Evaluation Stack
We run deep in silico simulations.
Over 50 custom-tuned models assess binding, toxicity, ADME/PK, immunogenicity, and mechanistic fit.
Specialist Human Review
Experts validate the science.
PhDs with domain expertise review each asset's biology, risks, and translatability before greenlighting it for development.
Market Insight Agent
Uncovers the strongest signals in the market
Every asset is ranked based on unmet need, competitive landscape, IP positioning, reimbursement signals, financial projections, and other market-shaping factors.
Operational Risk Agent
Digital twin simulations to score execution risk before trials start.
CRO fragility, CMC complexity, site readiness, and real-world disruption are modeled to flag trial fragility and avoid costly delays.
Business Development Agent
We help package and pitch to pharma.
We craft buyer-specific decks and term sheets backed by analog deals, targeting pharma with the right modality fit, portfolio synergy, and deal appetite.
Final Human Review
A live roundtable makes the final call.
Scientific, regulatory, commercial, and clinical leaders align on risk, timing, and exit strategy before making a go/no-go decision.
Explore Our Playground
Step inside the Convexia Playground — a live showcase of our AI agents in action. From sourcing overlooked molecules to predicting clinical feasibility, see how our tools uncover and evaluate hidden drug assets in real time.
Explore Our In-Silico Drug Evaluation Stack
We combine 50+ models to assess every asset across molecular, structural, and translational domains.
Binding & Mechanistic Coherence
Evaluates whether a molecule binds its target and drives the desired downstream effects, using structure-based docking and pathway-aware models.
ADME & Pharmacokinetics
Predicts absorption, distribution, metabolism, and excretion using validated ML models, flagging liabilities like poor bioavailability or rapid clearance.
Toxicity & Safety Profiling
Screens for general and organ-specific toxicity risks using multi-modal predictors trained on human and animal datasets.
Off-Target & Immunogenicity Risk
Scans for unintended interactions and immune triggers using structure- and sequence-based predictors to minimize adverse effects and immune rejection.
Why Our AI is Different
Built for real-world drug development, not just to say we use AI.
Modular Agents, Not Monolithic Models
Each step of the drug lifecycle is handled by a specialized agent tuned for its specific role.
Human-in-the-Loop by Design
Expert review is integrated into every decision layer, improving accuracy, interpretability, and trust.
Smarter Training with Unlabeled Data
We use semi-supervised learning and synthetic augmentation to train on scarce or unlabeled biomedical data.
Frequently Asked Questions
We’re a Stanford- and YC-backed team with experience across biotech, venture, and AI. We’re supported by advisors from leading pharma, regulatory bodies, and computational biology groups — all aligned around accelerating overlooked therapeutics.
Yes. You can access specific modules, including our sourcing engine, diligence stack, and BD agent. Reach out to schedule a pilot at founders@convexia.bio.
Our long-term goal is to operate the full drug lifecycle ourselves — acquiring assets, running clinical trials, and selling them to strategic buyers. As a first step, we are licensing components of our platform and running pilots with pharma, biotech, and investment groups to demonstrate value and build traction.
We source globally from academia, stealth biotech, early-stage pharma, and overlooked IP repositories — surfacing high-potential assets often missed by traditional scouts.
Each AI-prioritized asset is reviewed by internal scientists and a rotating panel of domain experts in drug development, regulatory strategy, and translational research.
We don’t operate a wet lab. Instead, we partner with CROs for IND-enabling studies and early trials.
Not currently. We focus on sourcing and evaluating existing assets, not designing new molecules.
Let's Talk
We're actively seeking collaborators, pilot customers, and discovery partners.