--- title: "Life Science API — Build on the life-science data engine" description: "Direct REST access across six cores — biomedical literature, clinical trials, drugs, genes, patents, and FDA + EMA regulatory — cross-linked and cited. Structured JSON, rich metadata, daily updates." url: https://amass.tech/life-science-api --- # Life Science API — Build on the life-science data engine API # Build on the life-science data engine. One REST API across six live cores — biomedical literature, clinical trials, drugs, genes, patents, and FDA + EMA regulatory — cross-linked and cited to source. Go from a gene to the drugs that target it, the trials that study it, the papers behind it, and the regulatory decisions that cover it — in one call. Structured JSON, typed schemas, daily updates. [Get API Key →](https://platform.amass.tech/api-keys)[Documentation](https://platform.amass.tech/documentation/getting-started/overview) [NewPatentCore is live in preview. 16M+ patent publications, cross-linked to drugs and papers.](https://amass.tech/core#patentcore) bash
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$ curl \
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 "https://api.amass.tech/api/v1/
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 cores/drugcore/records?
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 query=semaglutide&limit=1" \
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 -H "Authorization: Bearer amass_YOUR_KEY"
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→ 200 OK 1 record
Response — data.records\[0\] { "amassId": "AMDC\_CHEMBL2108724" "name": "Semaglutide" "tradeNames": \["Ozempic", "Wegovy", "Rybelsus"\] "modality": "Protein" "maxClinicalStage": "Approved" "crossLinks": { "trials": 184, "papers": 4216, "regulatory": \["FDA", "EMA"\] } } Join life-science AI builders on Discord [Join now](https://discord.gg/sEGaBHMhWa) Demo ## See the intelligence layer in action. Six live cores, and the API, MCP, app and agents that sit on top of them. Builders ## What people build with it Founders, fellows, and hackathon teams who pointed their agents at the API and shipped. > We'd tried scraping patent data ourselves and it was a nightmare. With PatentCore we built a full freedom-to-operate landscape of our space in a couple of days. > The API is really great — I've used it personally for my structural-biology workflows. BiomedCore surfaced epitope annotations we couldn't find in structured databases like UniProt. > Of everything we built on during the hackathon, Amass was the most valuable API. I built a landscape around patents and trials — very, very valuable for understanding where the field is going. > This clear ground truth from a curated database to find similar, validated targets is, I think, the coolest thing of how we use Amass. Data ## Six live cores. More on the way. Query curated life-science databases directly — no wrappers, no hallucinations. Every record carries full provenance and typed metadata, and cross-links to the others, so a gene, paper, trial, drug, patent, and approval all resolve to the same entity. ### BiomedCore /cores/biomedcore/records 40M+ Peer-reviewed biomedical literature from PubMed and PubMed Central. Every record includes MeSH terms and IDs, publication types (RCT, meta-analysis, systematic review), JuFo 0–3 journal quality tier, citation count, DOI, PMID, and PMCID. Optional: full text for PMC articles, ORCID-disambiguated authors with ROR-mapped affiliations, and links to the trials each paper describes in TrialCore. Filter parameters queryminJournalQualityJufominCitationCountminPublicationDateisRetractedminLastUpdateDateminCreateDateinclude=fulltextinclude=authorsMetadata [See more](https://amass.tech/core#biomedcore) ### TrialCore /cores/trialcore/records 1.2M+ Clinical trial records from ClinicalTrials.gov and international registries. Includes protocol data, eligibility criteria, primary and secondary endpoints, sponsor details, arm groups, recruitment status, NCT ID, and the full lifecycle — start, completion, results posting, and why stopped. Outcome measurements are available as structured values per arm, not PDF blobs. Records link back to the publications that describe them in BiomedCore. Filter parameters queryphaseoverallStatussponsorTypeinterventionTypefacilityCountrieshasResultsminEnrollmentminLastUpdateDateminCreateDateinclude=outcomes [See more](https://amass.tech/core#trialcore) ### DrugCore /cores/drugcore/records 22K+ ChEMBL-derived drugs and molecules, harmonized. Names, trade names, and synonyms; chemical structures with InChIKey and SMILES; modality classification; and highest clinical stage from preclinical through approval. Each drug cross-links to the trials, papers, and regulatory authorizations it appears in. Filter parameters querydrugTypemaxClinicalStage [See more](https://amass.tech/core#drugcore) ### RegulatoryCore /cores/regulatorycore/records FDA + EMA FDA and EMA regulatory data on one unified schema. FDA application records, drug labels, review documents, and approval letters; EMA EPARs, assessment reports, and SmPCs. Each record carries a unified authorization status, designations (Breakthrough Therapy, PRIME, Accelerated Approval), and orphan status — and cross-links to the drug it covers in DrugCore. Filter parameters queryagencyauthorizationStatushasDesignationisOrphanmoleculeTypeminLastUpdateDateminCreateDate [See more](https://amass.tech/core#regulatorycore) ### GeneCore /cores/genecore/records 43K+ 43,000+ harmonized human gene records from HGNC, NCBI, UniProt, and Ensembl. Druggability and tractability assessments, target safety data, genetic constraint via gnomAD v4.0 (pLI, LOEUF), and cellular essentiality from CRISPR dependency screens. Each gene cross-links to the drugs that target it in DrugCore, the trials that study it in TrialCore, and the papers that cite it in BiomedCore — from gene to clinical evidence in one call. Filter parameters querygeneTypeisDruggableisEssentialtargetClasstractabilityModalityhasSafetyLiabilitiesmaxConstraintLoeuf [See more](https://amass.tech/core#genecore) ### PatentCore Preview /cores/patentcore/records 16M+ Patent publications with English-preferred full text — title, abstract, claims, and description — plus bibliographic metadata (publication and application numbers, jurisdiction, kind code, family id), CPC/IPC classifications, inventors and assignees, four separate dates, and citation lineage. Search returns one publication per family, the most relevant member, and every record cross-links to the drugs it mentions in DrugCore and the papers it cites in BiomedCore. Filter parameters querycountryCodecpcCodesassigneeinventorminPriorityDateminCitedByCountinclude=claims [See more](https://amass.tech/core#patentcore) Coming soon:DiseaseCore— more data layers on the way How It Works ## From zero to your first response — three steps 01 Step 1 ### Create an account and get an API key Sign up at platform.amass.tech, go to API Keys, and click Create API Key. Your key starts with amass\_ and is shown only once — copy it immediately. Generate separate keys for dev and prod; both share your plan quota. API Keys\+ Create key production amass\_live\_•••••••••••• Active development amass\_dev\_•••••••••••• Active 02 Step 2 ### Make your first search request Pass your key in the Authorization header on every request. Every core answers the same three-endpoint pattern — search, get by Amass ID, batch lookup — so one query shape works across all six. Returns up to 300 records per call. bash ``` $ curl \ "https://api.amass.tech/api/v1/ cores/biomedcore/records? query=alzheimer+tau &minJournalQualityJufo=2 &limit=10" \ -H "Authorization: Bearer amass_YOUR_KEY" ``` 03 Step 3 ### Build your workflow — Python, JavaScript, or any HTTP client No official SDK needed — the API is plain REST. Use requests in Python or fetch in JavaScript. Handle 429s with exponential backoff; the rate-limit window resets every 60 seconds. ``` import requests BASE = "https://api.amass.tech/api/v1" HEADERS = {"Authorization": "Bearer amass_YOUR_KEY"} # Search BiomedCore resp = requests.get( f"{BASE}/cores/biomedcore/records", headers=HEADERS, params={ "query": "GLP-1 NASH liver fibrosis", "minJournalQualityJufo": 2, "limit": 50, }, ) records = resp.json()["data"]["records"] # → list of { amassId, pmid, doi, title, # citationCount, journalQualityJufo, … } ``` Use Cases ## What teams build with the API Real patterns used by R&D teams, data engineers, and builders. Every snippet below is copy-paste ready. Jupyter + pandasData scientist ### Literature mining pipeline Pull high-quality papers on any target, pipe the structured output into pandas, and sort by citation count for a prioritised reading list — all in 10 lines. python ``` import requests, pandas as pd r = requests.get( "…/cores/biomedcore/records", headers={"Authorization": "Bearer amass_…" }, params={ "query": "GLP-1 receptor agonist NASH", "minJournalQualityJufo": 2, "minPublicationDate": "2023-01-01", "limit": 300}, ) df = pd.DataFrame(r.json()["data"]["records" ]) df.sort_values("citationCount").head(20) ``` minJournalQualityJufo=2minPublicationDate=2023-01-01 LovableR&D team ### No-code trial tracker — built in one afternoon Paste your Amass API key into Lovable and describe what you want. It wires up the TrialCore endpoint, builds a filterable table, and deploys — no engineering required. Lovable prompt “Build a dashboard that fetches all recruiting Phase 3 NASH trials from the Amass API. Base URL: https://api.amass.tech/api/v1. Auth header: Authorization: Bearer amass\_xxx. Show a filterable table: trial name, NCT ID, sponsor, enrollment, start date.” generated request ``` GET /cores/trialcore/records ?query=NASH &phase=PHASE3 &overallStatus=RECRUITING &limit=100 ``` TrialNCT IDSponsorEnroll NASH-301 StudyNCT04822519Novo Nordisk1,200 RESOLVE-ITNCT02704403Ipsen2,516 MAESTRO-NASHNCT0390042989bio968 n8nR&D ops ### Nightly trial monitoring alerts An n8n HTTP Request node polls TrialCore every night and pushes a Slack message when new recruiting trials appear for your indication. Zero code. Schedule every night HTTP GET TrialCore IF new records? Slack notify team HTTP Request node ``` Method: GET URL: …/cores/trialcore/records Auth: Bearer amass_YOUR_KEY # Query params query: obesity GLP-1 phase: PHASE3 overallStatus: RECRUITING ``` StreamlitResearch engineer ### Internal research app in 20 lines A Streamlit app that wraps BiomedCore into an internal search tool — live search with JuFo score and citation count visible at a glance. Deployed on Streamlit Community Cloud for free. app.py ``` import streamlit as st, requests q = st.text_input("Search papers") if q: r = requests.get( "…/cores/biomedcore/records", headers={"Authorization": f"Bearer {st.secrets['KEY']}" }, params={"query": q, "limit": 20, "minJournalQualityJufo": 2 }, ) for rec in r.json()["data"]["records"]: st.markdown(f"**{rec['title']}** \n{rec['doi']}") st.caption(f"JuFo {rec['journalQualityJufo']} · {rec['citationCount']} citations") ``` Developer Resources ## Everything you need to get to production [ ### API Overview Base URL, authentication, rate limits, error codes, and response envelope. See more](https://platform.amass.tech/documentation/getting-started/overview)[ ### BiomedCore Reference Full parameter and field reference for all three BiomedCore endpoints. See more](https://platform.amass.tech/documentation/cores/biomedcore)[ ### TrialCore Reference Full parameter and field reference for all three TrialCore endpoints. See more](https://platform.amass.tech/documentation/cores/trialcore)[ ### DrugCore Reference 22K+ harmonized drugs and molecules — modality, clinical stage, structure, and mechanisms of action. See more](https://platform.amass.tech/documentation/cores/drugcore)[ ### RegulatoryCore Reference FDA and EMA authorizations on one schema, plus full-text search across labels, SmPCs, reviews, and EPARs. See more](https://platform.amass.tech/documentation/cores/regulatorycore)[ ### GeneCore Reference 43K+ human genes — druggability, genetic constraint, and cross-links to DrugCore and TrialCore. See more](https://platform.amass.tech/documentation/cores/genecore)[ ### PatentCore Reference 16M+ patent publications in preview — full-text search, family collapsing, and cross-links to drugs and papers. See more](https://platform.amass.tech/documentation/cores/patentcore)[ ### API Roadmap & Changelog What shipped, month by month, and what's being built next for the public REST API. See more](https://platform.amass.tech/documentation/getting-started/roadmap)[ ### Quickstart Guide From zero to your first cited response in under five minutes. See more](https://platform.amass.tech/documentation/getting-started/quickstart)[ ### LLM Quick Reference Self-contained reference designed for AI agents and automated tools. See more](https://platform.amass.tech/documentation/for-ai-agents/llm-quick-reference)[ ### OpenAPI Spec Machine-readable spec for code generation, Postman imports, and type inference. See more](https://api.amass.tech/api/doc/openapi.json)[ ### Developer Community Join the Amass developer community — talk to other life-science AI developers and builders. Join now](https://discord.gg/sEGaBHMhWa) ## Ship faster with cited science Start building with the Amass API today. Enterprise plans available for teams that need dedicated support. [Get API Key →](https://platform.amass.tech/api-keys)[Talk to Sales](https://amass.tech/contact)[Join our Discord](https://discord.gg/sEGaBHMhWa) By using the API you agree to the [API Terms of Service](https://amass.tech/legal/api-terms-of-service).