Pharos Target Druggability Scraper

Pharos Target Druggability Scraper

Scrape target druggability data from Pharos for any list of gene symbols, up to a million per run. Each target comes with its TDL classification, IDG development level, protein family, and known ligands. Export to CSV, JSON, Excel, or XML.

Pharos is the NIH's central knowledgebase for target druggability, but manually looking up each gene symbol through the web portal is slow and does not scale. This Actor reads the public target pages directly, accepts a list of gene symbols like ACE2 or EGFR, and returns a structured row for every matched target. You can optionally enrich each record with associated ligand and disease names.

Who uses it	What they scrape Pharos for
Computational biologists	Prioritizing a shortlist of protein targets for a new drug discovery program
Bioinformatics analysts	Enriching an internal gene list with public druggability annotations from the NIH
Pharma R&D teams	Screening a panel of targets to identify those with known chemical probes or drugs
Academic researchers	Fetching the IDG development level and protein family for a set of understudied kinases

What it does

This Actor collects target druggability profiles from Pharos by gene symbol and returns each target as a flat row with its TDL, IDG family, and development level.

• 🎯 Targeted lookup: Provide a list of gene symbols and get back exactly one record per matched target.
• 🧭 Browse mode: Leave the gene list empty to scrape the top-ranked targets from the Pharos catalog.
• 🧪 Ligand enrichment: Optionally add a list of known drug and chemical probe names to each target record.
• 🩺 Disease enrichment: Optionally add a list of associated disease names to each target record.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Pharos data

🎯 Prioritize a target shortlist.

A computational biologist uploads 200 gene symbols from a CRISPR screen and scrapes their TDL classifications to focus on Tchem and Tclin targets.

📋 Enrich an internal gene panel.

A bioinformatics analyst runs a quarterly job that fetches the latest IDG development levels for a fixed panel of 500 targets and exports the results to CSV.

🔬 Find targets with known chemical probes.

A medicinal chemist enables ligand enrichment for a list of novel targets to see which ones already have a small molecule probe they can use as a starting point.

📊 Audit understudied targets.

An academic lab scrapes all Tdark targets in their disease area of interest and enriches them with disease associations to pick the most relevant one for a grant application.

Why choose this scraper

	What you get
TDL classification	Whether a target is Tclin, Tchem, Tbio, or Tdark
IDG development level	The target's placement in the Illuminating the Druggable Genome knowledge pyramid
Protein family	The structural class, such as kinase, GPCR, or ion channel
Known ligands	Drug and probe names linked to the target when enrichment is enabled

How it compares

No other Store actor targets Pharos the same way, so the honest comparison is with the alternatives teams actually weigh.

	Pharos Target Druggability Scraper	Build it in-house	By hand
Setup	Run it now, zero config	Days of engineering	None, but hours per pull
When Pharos changes	Maintained for you	You fix it	You re-learn the page
Proxies, retries, anti-bot	Built in	Your problem	Browser only
Output	Fixed JSON schema, CSV/Excel export	Whatever you build	Copy-paste
Cost	Pay per result	Engineering time	Analyst hours

Configure the run

Drive the Actor with a list of gene symbols or leave it empty to browse top targets, and set a maximum item limit to control the run size. The Input tab lists every parameter.

A first run with the defaults:

{
  "targets": [
    "ACE2",
    "EGFR",
    "TP53"
  ],
  "maxItems": 10
}

A larger pull:

{
  "targets": [
    "ACE2",
    "EGFR",
    "TP53"
  ],
  "maxItems": 200
}

Pricing

Pay-per-result: $0.017 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$1.70
1,000 results	$17.00
10,000 results	$170.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the Pharos Target Druggability Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to Pharos through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/pharos-target-druggability-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that your gene symbols use standard HGNC nomenclature. Non-standard or outdated symbols may not match any Pharos page. Try leaving the list empty to confirm the scraper works in browse mode.

The run is taking a long time.

Ligand and disease enrichment each add one extra request per target. For large lists, disable enrichment or reduce the maximum items limit to speed up the run.

Some of my gene symbols are missing from the output.

Pharos may not have a dedicated page for every gene symbol. The Actor skips symbols that do not resolve to a valid target page. Verify the symbol on the Pharos website directly.

I hit the maximum items limit but I need more data.

Free users are limited to 10 items as a preview. Upgrade to a paid Apify plan to increase the limit up to 1,000,000 targets per run.

The ligand names column is empty even though I enabled enrichment.

Not every target has known ligands. If Pharos lists no ligands for a target, the field will be empty. Verify on the Pharos website that the target has ligand data.

FAQ

Question	Answer
What is a TDL classification?	TDL stands for Target Development Level. It is a four-tier classification from the IDG project: Tclin (targets with approved drugs), Tchem (targets with small molecule probes), Tbio (targets with no known chemical probes), and Tdark (targets with very little known biology).
Can I scrape all targets in Pharos?	Yes. Leave the gene symbols list empty and set a high maximum items limit. The Actor will browse the top targets from the Pharos catalog and return one record per target.
Does enabling ligand or disease enrichment slow down the run?	Yes, it adds one extra request per target for each enrichment option you enable. For large lists, expect the run time to increase proportionally.
What format does the output come in?	You can export the dataset in CSV, JSON, Excel, or XML format directly from the Apify dataset tab after the run finishes.
How do I provide the list of gene symbols?	Paste them into the gene symbols field in the Actor input, one per line. Use standard HGNC symbols like EGFR, TP53, or ACE2.
What happens if I provide a gene symbol that Pharos does not recognize?	The Actor will skip that symbol and continue with the next one. Only matched targets appear in the output dataset.
Is this using the official Pharos API?	No. This Actor reads the public target pages on the Pharos website directly, so you do not need an API key or registration.
Can I run this on a schedule?	Yes. Apify supports scheduled runs. You can set this Actor to run weekly or monthly to track changes in target annotations over time.
What is the IDG development level?	It is a measure from the Illuminating the Druggable Genome project that places each target on a knowledge pyramid, indicating how much is known about its biology and druggability.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by National Center for Advancing Translational Sciences (NCATS). It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.