# Atlas Discovery

**Canonical:** https://apis.io/providers/atlas-discovery/  
**Website:** https://atlasdiscovery.bio  
**APIs profiled:** 0

Atlas Discovery is an AI-powered biotechnology company (Y Combinator Summer 2026) building foundation models of human patient biology to predict how people will respond to drugs in clinical trials. Nine of ten drugs fail in trials because no animal model or cell in a dish reliably predicts a human response; Atlas Discovery trains models on preclinical and clinical data to improve trial design and rescue stalled drug programs. Its research spans single-cell representation learning (ExpressionVAE) and clinical response prediction, with work presented at ICLR '26, ICML '26, and CSHL '26. The company is an early-stage research lab with no public API, developer program, or product surface yet; this profile is maintained in the API Evangelist network as a portfolio lead awaiting a public developer offering.

## Kin Score — 3.8 / 100 (minimal)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 3.8).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Commercial Clarity | 0.0 |
| Access Clarity | 0.0 |

Regulatory layer — **Health**: 7.5 (matched via tags).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Atlas Discovery Domain Security** — TLSv1.3 · HSTS

## Tags

Company, Biotechnology, Drug Discovery, Artificial Intelligence, Machine-Learning, Clinical Trials, Foundation Models, Life Sciences

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/atlas-discovery/). Scores are computed from the provider's own public artifacts under a published rubric.