Researcher Email Finder: PubMed Authors by Topic

Find researchers by topic with the email they published in PubMed papers, plus affiliation, ORCID and recent papers. $0.005 per researcher with email. Answers "corresponding author email", "pubmed author email", "pubmed emails", "researcher contact email" and "academic email finder" for any research field: give it a topic such as crispr base editing, an author name, or a list of PMIDs or DOIs, and get one row per researcher with the address they printed in a paper for correspondence, their institution, country, ORCID iD and their latest papers on the topic. No login, no API key, no CAPTCHA.

Built to be called by AI agents ("find researchers working on CRISPR base editing with their emails") and by sales and recruiting pipelines as well as people: the same fields on every row, deduplicated by email, and the price tied to the answer you want.

Use cases

• Life-science and lab-supply sales: reach the labs publishing on the technique your reagent, instrument or software serves, with the address each corresponding author published.
• CROs and biotech business development: build a list of active investigators in an indication or modality ("car-t solid tumors", "spatial transcriptomics"), filtered by country or institution.
• Conference, journal and webinar marketing: invite the authors who published on your session topics in the last two years.
• Academic and industry recruiting: find postdocs and PIs publishing in a field, with their affiliation and ORCID.
• AI agents and research assistants: "who works on X, and how do I contact them?" as one tool call that charges only for researchers with an email.
• Enrichment: turn a list of PMIDs or DOIs into the contact emails of their corresponding authors.

What it finds

PubMed records the affiliation of every author, and when a paper names a corresponding author, PubMed usually keeps the email printed with it (often as "Electronic address: ..."). This Actor searches PubMed for your topic, reads the full records of the most relevant papers through NCBI's official E-utilities API, and pulls out every author who published an email. Measured on test runs, recent papers yield about 3 published emails for every 4 papers, so 200 papers give roughly 150 researchers.

Each email is cleaned (trailing periods and "Electronic address:" labels removed, lower-cased) and given to the right author. When an affiliation prints several addresses, or several authors share one affiliation string, the address goes to the author whose name matches its local part (wangfei@ goes to Fei Wang, not to his co-author Yang Wang); an address that cannot be tied to one person is dropped rather than guessed.

Researchers are deduplicated by email across all topics and papers in the run, and their other papers in the result (including ones where they did not print the email) are attached to the same row.

How it works

1. Each topic or author name is searched on PubMed (relevance order), with yearFrom limiting it to recent papers.
2. The matching records are fetched in batches of up to 200 and parsed from PubMed's XML.
3. Emails are extracted from author affiliations and assigned to authors; institution and country are read from the affiliation, ORCID from the author record.
4. A search stops early once it alone has enough researchers for maxResearchers, or at maxPapersScanned.
5. Rows are spread evenly across your topics, newest-publishing researchers first, and capped at maxResearchers.

Requests are paced to NCBI's public limit (about 3 a second) and identify the tool to NCBI, as its usage policy asks.

Input

Field	Meaning
queries	Research topics, one per line. PubMed syntax works: "base editing"[tiab] AND mice.
authorNames	A named researcher: Jennifer Doudna, Doudna JA or Doudna, Jennifer. Only that author is returned.
pmids, dois	Specific papers. Every author on them who published an email is returned.
yearFrom	Only papers from this year on, e.g. 2024. Applies to topics and author names.
affiliationContains	Keep researchers whose affiliations include this text (Harvard, Hospital).
countries	Keep researchers whose affiliation country is one of these (United States, DE, UK).
onlyWithEmail	On by default. Off also returns co-authors without an email, free.
maxResearchers	Rows to return across all topics (default 50).
maxPapersScanned	Papers read per topic or author (default 500).
source	pubmed (default, most emails) or europepmc (Europe PMC: ORCID for more authors, preprints, fewer emails).
delayMs, proxyConfiguration	Pacing (default 400 ms) and an optional proxy. No proxy by default.

Leave every source field empty to run a built-in example: 5 researchers on crispr base editing (about 5 seconds, 5 x $0.005).

{
  "queries": ["crispr base editing", "car-t cell therapy solid tumors", "spatial transcriptomics"],
  "yearFrom": 2024,
  "countries": ["United States", "United Kingdom", "Germany"],
  "maxResearchers": 100
}

Output

One row per researcher, deduplicated by email. Fields that were not found are null, never invented.

{
  "name": "Thomas Gaj",
  "firstName": "Thomas",
  "lastName": "Gaj",
  "email": "gaj@illinois.edu",
  "emailDomain": "illinois.edu",
  "isAcademicEmail": true,
  "hasEmail": true,
  "affiliation": "Department of Bioengineering, The Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA",
  "institution": "University of Illinois Urbana-Champaign",
  "country": "United States",
  "countryCode": "US",
  "orcid": "0000-0001-6004-9664",
  "orcidUrl": "https://orcid.org/0000-0001-6004-9664",
  "papers": [
    {
      "title": "In vivo CRISPR base editing for treatment of Huntington's disease",
      "pmid": "42527584",
      "doi": "10.1038/s41551-026-01747-y",
      "journal": "Nature biomedical engineering",
      "year": 2026,
      "url": "https://pubmed.ncbi.nlm.nih.gov/42527584/",
      "isCorresponding": true
    }
  ],
  "papersInResult": 11,
  "lastPublishedYear": 2026,
  "matchedQuery": "crispr base editing",
  "input": "query:crispr base editing",
  "scrapedAt": "2026-10-09T15:31:41+00:00"
}

• papers holds the 5 most recent papers in the result; papersInResult counts all of them. isCorresponding is true on papers where the researcher printed their email.
• isAcademicEmail is true for university, research-institute and public-research mailboxes, and false for free mail (Gmail, 163.com) and company domains.
• input says what found the row: query:<topic>, author:<name>, pmid:<id> or doi:<doi>.

The dataset has two views: Researchers (one row each) and Papers (one row per researcher and paper).

Pricing

One event, pay per result:

• researcher-with-email: $0.005 for each researcher returned with a published email.
• With onlyWithEmail on (default), researchers without an email are never returned. Turn it off and they are returned free.
• PubMed papers scanned are never charged; you pay for researchers, not for searching.

Worked example. Three topics with maxResearchers: 150 return 150 researchers with emails: 150 x $0.005 = $0.75. In our test that run read 793 papers in 16 seconds.

Set a maximum total charge on the run and the Actor stops cleanly when it is reached.

What to expect

• Yield: on recent papers (2024 on) in life-science topics, about 1.4 papers per email found with PubMed. Europe PMC prints fewer emails (about 2 papers per email in tests) but carries ORCID for more authors.
• Who has an email: usually the corresponding author, sometimes two or three per paper. First and middle authors rarely publish one.
• Free-mail addresses: some researchers publish a Gmail, 163.com or QQ address; isAcademicEmail lets you filter them.
• Speed: a few seconds per 200 papers.

Limits

• Only emails the authors printed in the paper are returned. The Actor does not guess addresses from name patterns or look them up elsewhere.
• Emails can go stale when a researcher moves; lastPublishedYear and yearFrom help you keep to current addresses.
• Institution and country are read from the affiliation text, which journals format in many ways; a few rows have no country.
• PubMed covers biomedicine and life sciences. For other fields try source: europepmc, which also indexes preprints.
• Very common author names (Wang Y) match many people; give a full first name.

Use with Python

# pip install apify-client
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("datagleaner/researcher-email-finder").call(run_input={
    "queries": ["crispr base editing"],
    "yearFrom": 2024,
    "maxResearchers": 20,  # at most 20 x $0.005 = $0.10
})
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item["name"], item["email"], item["institution"], item["country"])

Use with JavaScript / Node.js

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('datagleaner/researcher-email-finder').call({
    queries: ['spatial transcriptomics'],
    countries: ['Germany'],
    yearFrom: 2024,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const item of items) console.log(item.name, item.email, item.orcidUrl);

Use it from n8n, Make, Zapier or an AI agent

Actor ID: datagleaner/researcher-email-finder

Minimal input:

{"queries": ["crispr base editing"], "yearFrom": 2024}

Each tool below runs this Actor with your own Apify API token.

• n8n: add the Apify node (@apify/n8n-nodes-apify). On n8n Cloud you install it from the community node registry. Choose Run an Actor and get dataset, set Actor to datagleaner/researcher-email-finder and paste the input above.

• Make: use the Apify app's Run an Actor module, then Get Dataset Items to read the results. Watch Actor Runs can trigger a scenario when a run finishes.

• Zapier: use the Apify action Run Actor, then the search Fetch dataset items. The trigger Finished Actor run starts a Zap when a run ends.

• AI agents (MCP): connect to https://mcp.apify.com/?tools=datagleaner/researcher-email-finder. In Claude Code:

  claude mcp add --transport http apify "https://mcp.apify.com/?tools=datagleaner/researcher-email-finder"
  

  Then run /mcp to sign in to Apify in your browser. Other clients can sign in with OAuth or send the header Authorization: Bearer YOUR_APIFY_TOKEN. Clients that run local MCP servers can use Apify's package (@apify/actors-mcp-server, run with npx -y and APIFY_TOKEN set) instead. Then ask the agent in plain words, for example:

  Find 30 researchers in the US and UK who published on CRISPR base editing since 2024, with their emails, institutions and latest paper, as a table.

• LangChain (Python):

# pip install langchain-apify, then set APIFY_TOKEN in your environment
import json
from langchain_apify import ApifyActorsTool
tool = ApifyActorsTool("datagleaner/researcher-email-finder")
result = tool.invoke({"run_input": json.loads('{"queries": ["crispr base editing"], "yearFrom": 2024}')})

FAQ

How do I find a corresponding author's email? Give the paper's PMID or DOI, or a topic, to this Actor. It reads the paper's PubMed record and returns the email the corresponding author printed, with the author's affiliation.

Where do the emails come from? From the author affiliations in PubMed (or Europe PMC) records, where journals publish the corresponding author's address. Nothing is guessed or bought.

Can I find a specific researcher's email? Yes: put their name in authorNames, e.g. Doudna JA. If they published an email on any of their papers in range, it is returned with their papers.

Does it get ORCID iDs? Yes, when the record carries one. Europe PMC (source: europepmc) carries ORCID for more authors.

Do I need an NCBI API key? No. The Actor uses NCBI's public E-utilities within the published rate limit.

Is it only for biomedicine? PubMed is biomedical and life-science literature. Europe PMC adds preprints and some other fields.

Responsible use

The emails this Actor returns are addresses the authors themselves published in their papers for scholarly correspondence. They are still personal data. You are responsible for lawful use, including GDPR, CAN-SPAM and local law (a lawful basis, an opt-out in every message, honouring removals) and for the terms of PubMed and Europe PMC. Do not use it for bulk unsolicited email: write to researchers individually, about their work, and only when your message is relevant to it.