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โ‡ฑ Open Targets Drug-Target-Disease Scraper - Drug Discovery ยท Apify


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Open Targets Platform Scraper

Query Open Targets Platform GraphQL API for targets (genes), diseases, or drugs and return rich associations including drugs by disease, known drugs, indications, mechanisms of action, pathways, tractability and genetic constraint. No API key required.

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๐ŸŽฏ Open Targets Platform Scraper

๐Ÿš€ Export drug-target-disease associations in seconds. Query the Open Targets Platform GraphQL API across targets, diseases, drugs, and free-text search. No API key, no registration, no manual GraphQL stitching.

๐Ÿ•’ Last updated: 2026-05-13 ยท ๐Ÿ“Š 4 entity modes ยท ๐Ÿงฌ 60,000+ targets ยท ๐Ÿฆ  26,000+ diseases ยท ๐Ÿ’Š 13,000+ drugs ยท ๐ŸŒ EBI GraphQL API

The Open Targets Platform Scraper queries the Open Targets v4 GraphQL API and returns rich, joined records for targets (genes), diseases, drugs, and free-text search. Open Targets is a public-private partnership between EMBL-EBI, GSK, Sanofi, Bristol Myers Squibb, Pfizer, Genentech, MSD, and the Wellcome Sanger Institute that integrates genetics, genomics, transcriptomics, drug, and literature evidence into target-disease association scores used across drug discovery.

This Actor exposes four query modes in one input form: pull a target by Ensembl ID (or HGNC symbol), a disease by EFO / MONDO ID, a drug by ChEMBL ID, or a free-text search across all three. Each record returns the canonical ID, name, descriptive metadata, and the relevant association table (associated diseases, associated targets, mechanisms of action, indications, drug warnings).

๐ŸŽฏ Target Audience๐Ÿ’ก Primary Use Cases
Drug discovery teams, target ID scientists, computational biologists, bioinformaticians, regulatory analysts, journal editors, ML researchersTarget prioritization, drug repurposing, disease-target maps, ChEMBL-to-EFO joins, indication discovery, mechanism-of-action audits, ML feature engineering

๐Ÿ“‹ What the Open Targets Scraper does

Four query modes in a single Actor:

  • ๐Ÿงฌ Target mode. Fetch by Ensembl gene ID (e.g. ENSG00000146648 for EGFR), or by HGNC symbol that the Actor resolves via the GraphQL search hit. Returns approvedSymbol, approvedName, biotype, function descriptions, hallmarks, tractability modalities, pathways, the top associated diseases (scored), and the drug + clinical-candidate table.
  • ๐Ÿฆ  Disease mode. Fetch by EFO or MONDO ID (e.g. EFO_0000222 for Acute Myeloid Leukemia). Returns description, therapeutic areas, synonyms, parents, children, the top associated targets (scored), and the drug + clinical-candidate table.
  • ๐Ÿ’Š Drug mode. Fetch by ChEMBL ID (e.g. CHEMBL1201583). Returns description, drug type, maximum clinical stage, synonyms, trade names, cross-references, mechanisms of action with target objects, indications with diseases, drug warnings, and parent molecule.
  • ๐Ÿ”Ž Search mode. Free-text search across target + disease + drug. Returns one row per hit with entity type, ID, name, description, and relevance score.

๐Ÿ’ก Why it matters: Open Targets is the canonical public source for evidence-based target prioritization in pharma. Building your own GraphQL queries means schema introspection, pagination plumbing, and constant rewrites. This Actor returns ready-joined records on every run.


๐ŸŽฌ Full Demo

๐Ÿšง Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded target-disease dataset.


โš™๏ธ Input

InputTypeDefaultBehavior
modeenum"target"One of target, disease, drug, search.
maxItemsinteger10Records to return. Free plan caps at 10, paid plan at 1,000,000.
ensemblIdstring"ENSG00000146648"For target mode. EGFR by default.
symbolstring""For target mode. HGNC symbol fallback resolved via search.
efoIdstring"EFO_0000222"For disease mode. EFO or MONDO ID.
chemblIdstring"CHEMBL1201583"For drug mode. ChEMBL drug ID.
searchQuerystring""For search mode. Free-text query string.
searchEntitiesstring[][]For search mode. Restrict to target, disease, or drug. Empty = all three.

Example: target mode for EGFR with associated diseases.

{
"mode":"target",
"ensemblId":"ENSG00000146648",
"maxItems":50
}

Example: free-text search across targets and diseases for "cancer".

{
"mode":"search",
"searchQuery":"cancer",
"searchEntities":["target","disease"],
"maxItems":25
}

โš ๏ธ Good to Know: target mode accepts either ensemblId or symbol. When you provide a symbol like BRAF, the Actor first calls the GraphQL search query to resolve the canonical Ensembl ID, then fetches the target object. Disease IDs follow EFO / MONDO / Orphanet conventions (EFO_*, MONDO_*, Orphanet_*). Drug IDs follow the ChEMBL CHEMBL* convention. Search hits include a relevance score that you can sort downstream.


๐Ÿ“Š Output

The output shape varies by mode. Each record always carries an entity field, an id, a url, and a scrapedAt timestamp.

๐Ÿงพ Search-mode schema

FieldTypeExample
๐Ÿท๏ธ entityenum"target", "disease", or "drug"
๐Ÿ†” idstring"ENSG00000139618"
๐Ÿ”— urlstring"https://platform.opentargets.org/target/ENSG00000139618"
๐Ÿ“› namestring"BRCA2"
๐Ÿ“ descriptionstring"BRCA2 DNA repair associated"
๐ŸŽฏ scorenumber471.1691
๐Ÿ•’ scrapedAtISO 8601"2026-05-13T22:26:22.091Z"

๐Ÿงพ Target-mode schema (selected fields)

FieldTypeNotes
๐Ÿท๏ธ entitystring"target"
๐Ÿ†” idstringEnsembl gene ID
๐Ÿ”ฌ approvedSymbolstringHGNC symbol
๐Ÿ“› approvedNamestringFull gene name
๐Ÿงฌ biotypestringe.g. protein_coding
๐Ÿ“œ functionDescriptionsstring[]UniProt descriptions
๐ŸŽฏ hallmarksobjectCancer hallmarks block
๐Ÿ’Š tractabilityobject[]Modality / value / label tuples
๐Ÿ” pathwaysobject[]Reactome pathways
๐Ÿฆ  associatedDiseasesobjectTop diseases with scores
๐Ÿ’Š drugAndClinicalCandidatesobjectDrugs in development

๐Ÿ“ฆ Sample record (search mode)


โœจ Why choose this Actor

Capability
๐ŸŽฏFour query modes. Target, disease, drug, and free-text search in one Actor.
๐ŸงฌJoined records. Target rows carry associated diseases, drugs, hallmarks, pathways, and tractability in a single document.
๐Ÿ”Symbol fallback. Pass BRCA1 or EGFR and the Actor resolves the Ensembl ID via the search hit before fetching the full object.
๐Ÿฆ EFO + MONDO + Orphanet. Standard biomedical ontologies, ready for joins.
๐Ÿ’ŠChEMBL cross-reference. Drug mode joins ChEMBL IDs to mechanisms of action, indications, and warnings.
โšกFast. GraphQL queries with retry and pagination size 250.
๐ŸšซNo authentication. Works on the public GraphQL endpoint. No login or API key.

๐Ÿ“Š Open Targets is the de facto reference dataset for target prioritization in modern drug discovery.


๐Ÿ“ˆ How it compares to alternatives

ApproachCostCoverageRefreshModesSetup
โญ Open Targets Scraper (this Actor)$5 free credit, then pay-per-useFull Open TargetsLive per runtarget, disease, drug, searchโšก 2 min
Hand-rolled GraphQLFreeFullManualManual๐Ÿข Days
OmicsDB / commercial target-ID platforms$$$/yearCurated subsetQuarterlyManyโณ Weeks
Static EBI dataset dumpsFreeSnapshotStaleNone๐Ÿ•’ Variable

Pick this Actor when you want broad target-disease-drug coverage, four ready-built query modes, and no pipeline maintenance.


๐Ÿš€ How to use

  1. ๐Ÿ“ Sign up. Create a free account with $5 credit (takes 2 minutes).
  2. ๐ŸŒ Open the Actor. Go to the Open Targets Platform Scraper page on the Apify Store.
  3. ๐ŸŽฏ Set input. Pick a mode, enter an ID (or a search query), and set maxItems.
  4. ๐Ÿš€ Run it. Click Start and let the Actor collect your data.
  5. ๐Ÿ“ฅ Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

โฑ๏ธ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.


๐Ÿ’ผ Business use cases

๐Ÿ’Š Pharma R&D & Target ID

  • Target prioritization scored by disease association
  • Tractability dashboards across portfolios
  • Drug repurposing audits against new indications
  • Mechanism-of-action joins with ChEMBL

๐Ÿงฌ Computational Biology

  • ML feature tables joining ENSG, EFO, and ChEMBL IDs
  • Pathway enrichment with Reactome IDs
  • Genetic-constraint annotation of candidate genes
  • Cross-disease target overlap analyses

๐Ÿ“ฐ Scientometrics & Competitive Intelligence

  • Tracking competitor pipelines by ChEMBL drug ID
  • Indication-creep mapping across portfolios
  • Clinical-stage distribution by mechanism
  • Drug-warning surveillance for safety teams

๐Ÿค– ML & AI for Drug Discovery

  • Knowledge graphs joining target, disease, and drug
  • Embedding generation for drug-target prediction
  • Benchmark suites for biomedical NLP
  • Retrieval-augmented LLM applications

๐Ÿ”Œ Automating Open Targets Scraper

Control the scraper programmatically for scheduled runs and pipeline integrations:

  • ๐ŸŸข Node.js. Install the apify-client NPM package.
  • ๐Ÿ Python. Use the apify-client PyPI package.
  • ๐Ÿ“š See the Apify API documentation for full details.

The Apify Schedules feature lets you trigger this Actor on any cron interval. Quarterly refreshes catch every Open Targets release.


๐ŸŒŸ Beyond business use cases

Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.

๐ŸŽ“ Research and academia

  • Reproducible target prioritization with versioned dataset pulls
  • Teaching datasets for bioinformatics and pharmacology
  • Open-source benchmark publications
  • Cross-database joins with ChEMBL, UniProt, and PDB

๐ŸŽจ Personal and creative

  • Indie biomedical-search apps for curious users
  • Visualizations for science communication
  • Educational drug-target dashboards
  • Portfolio projects on biomedical NLP

๐Ÿค Non-profit and civic

  • Neglected-disease target prioritization
  • Open-science pandemic preparedness
  • Public-domain biomedical-data outreach
  • Civic transparency on pharma pipelines

๐Ÿงช Experimentation

  • Train target-disease association models
  • Prototype agentic tools that resolve gene symbols
  • Benchmark biomedical knowledge graphs
  • Generate target embeddings at scale

๐Ÿค– Ask an AI assistant about this scraper

Open a ready-to-send prompt about this ParseForge actor in the AI of your choice:


โ“ Frequently Asked Questions

๐Ÿงฉ How does it work?

Pick a mode (target / disease / drug / search), enter the ID or query, click Start, and the Actor posts a GraphQL document to api.platform.opentargets.org/api/v4/graphql. Records are emitted as clean JSON ready for download. No browser automation, no captchas, no setup.

๐Ÿงฌ Where does the data come from?

Directly from the Open Targets Platform GraphQL API. Open Targets is a public-private partnership coordinated by EMBL-EBI.

๐Ÿ”ฌ Why are there four modes instead of one?

Each entity (target, disease, drug) has a different shape and a different set of association tables. Modelling them as one mode would force a lowest-common-denominator schema. The four modes return the right joined data for each entity, plus a flat-list search mode for discovery.

๐Ÿ†” How do I resolve a gene symbol to an Ensembl ID?

Use target mode and pass the symbol in the symbol field while leaving ensemblId empty. The Actor runs the GraphQL search query, takes the top hit with entity = target, and uses its Ensembl ID to fetch the full target object.

๐Ÿฆ  Which disease ontologies are supported?

Open Targets uses EFO, MONDO, and Orphanet identifiers. The efoId input accepts all three (e.g. EFO_0000222, MONDO_0003582, Orphanet_145).

๐Ÿ’Š Which drug ontology is supported?

ChEMBL drug IDs (CHEMBL*). Drug records cross-reference DrugBank, PubChem, and other sources via the crossReferences block.

๐Ÿ” How often is the dataset refreshed?

Open Targets ships quarterly platform releases. Every run of this Actor hits the live GraphQL endpoint, so your dataset reflects the current release at run time.

โฐ Can I schedule regular runs?

Yes. Use Apify Schedules to run this Actor on any cron interval (weekly, monthly, quarterly) and keep a downstream target-disease database in sync.

โš–๏ธ Is this data legal to use?

Open Targets data is released under a CC0 dedication. The raw association data is publicly accessible. Review Open Targets licensing for your specific use case, especially for redistribution.

๐Ÿ’ณ Do I need a paid Apify plan to use this Actor?

No. The free Apify plan is enough for testing and small runs (10 records per run). A paid plan lifts the limit and unlocks scheduling, higher concurrency, and larger datasets.

๐ŸŽฏ What if I need evidence-level detail?

This Actor returns target-level, disease-level, drug-level, and search-result records. For row-level evidence (single GWAS hits, single literature citations), reach out via the contact form below to request a companion evidence scraper.

๐Ÿ†˜ What if I need help?

Our support team is here to help. Contact us through the Apify platform or use the Tally form linked below.


๐Ÿ”Œ Integrate with any app

Open Targets Scraper connects to any cloud service via Apify integrations:

  • Make - Automate multi-step workflows
  • Zapier - Connect with 5,000+ apps
  • Slack - Get run notifications in your channels
  • Airbyte - Pipe target-disease data into your warehouse
  • GitHub - Trigger runs from commits and releases
  • Google Drive - Export datasets straight to Sheets

You can also use webhooks to trigger downstream actions when a run finishes. Push fresh association data into your drug-discovery backend, or alert your team in Slack when a watched target updates.


๐Ÿ”— Recommended Actors

๐Ÿ’ก Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.


๐Ÿ†˜ Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.


โš ๏ธ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Open Targets, EMBL-EBI, or any of its partner organizations. All trademarks mentioned are the property of their respective owners. Only publicly available open biomedical data is collected.

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