NIH Research Grants & Funding Scraper

Here is one real result, with every field the actor returns (AI add-ons were enabled for this run; the long abstractText, publicHealthRelevance, and terms values are trimmed here for readability, marked with [trimmed], and every shown value is verbatim from the record):

{
  "projectNum": "5F31AG090092-02",
  "coreProjectNum": "F31AG090092",
  "applId": 11248724,
  "fiscalYear": 2026,
  "projectTitle": "Investigating the role of calorie restriction-induced blood factors in rejuvenating the aged hippocampus",
  "piName": "Rhea  Misra",
  "piProfileId": 77784183,
  "piTitle": "GRADUATE STUDENT",
  "allPiNames": ["Rhea  Misra"],
  "piCount": 1,
  "programOfficerName": "MOLLY V WAGSTER",
  "orgName": "UNIVERSITY OF CALIFORNIA, SAN FRANCISCO",
  "orgCity": "SAN FRANCISCO",
  "orgState": "CA",
  "orgCountry": "UNITED STATES",
  "orgType": "SCHOOLS OF MEDICINE",
  "orgZipcode": "941432510",
  "orgUei": "KMH5K9V7S518",
  "congDist": "CA-11",
  "latitude": 37.767442,
  "longitude": -122.413937,
  "icCode": "AG",
  "icAbbreviation": "NIA",
  "icName": "National Institute on Aging",
  "agencyCode": "NIH",
  "activityCode": "F31",
  "awardType": "5",
  "awardAmount": 47696,
  "totalCostUsd": 47696,
  "directCostAmt": 47696,
  "indirectCostAmt": 0,
  "fundingMechanism": "Training, Individual",
  "mechanismCode": "TR",
  "cfdaCode": "93.866",
  "opportunityNumber": "PA-23-272",
  "projectStartDate": "2024-12-01",
  "projectEndDate": "2026-11-30",
  "budgetStartDate": "2025-12-01",
  "budgetEndDate": "2026-11-30",
  "awardNoticeDate": "2026-01-20",
  "isActive": true,
  "isNew": false,
  "covidResponse": null,
  "arraFunded": "N",
  "spendingCategories": null,
  "terms": ["Adherence", "Aging", "Alzheimer's Disease", "Amyloid beta-Protein", "Blood", "Brain", "Caloric Restriction", "Cognition", "Hippocampus", "Memory", "... [trimmed]"],
  "abstractText": "PROJECT SUMMARY\nAging leads to cognitive decline and increased risk for age-related neurodegenerative diseases such as Alzheimer's disease. The increasing rate of population aging places a larger number of people at risk for such cognitive dysfunction. [trimmed]",
  "publicHealthRelevance": "PROJECT NARRATIVE\nThe research described in this proposal will investigate the role of calorie restriction (CR)-induced blood factors in rejuvenating the aged brain. [trimmed]",
  "url": "https://reporter.nih.gov/project-details/11248724",
  "source": "NIH RePORTER",
  "observedAt": "2026-08-14T06:38:11.366Z",
  "aiSummary": "Aging leads to cognitive decline and a higher risk of neurodegenerative diseases like Alzheimer's, creating a need for effective therapies. This research aims to explore how blood factors induced by calorie restriction can rejuvenate the aging hippocampus and improve cognitive function. The findings could lead to blood-based treatments that mimic the benefits of calorie restriction, potentially helping to combat age-related cognitive decline.",
  "aiKeywords": ["calorie restriction", "aging", "hippocampus", "cognitive function", "neurodegenerative diseases", "Alzheimer's disease", "blood factors", "GPX3", "neuronal rejuvenation", "translational potential"],
  "aiField": "Neuroscience",
  "aiExtract": {
    "aims": ["Determine the potential of CR blood plasma administration to reverse age-related cognitive dysfunction and promote neuronal rejuvenation in the aged hippocampus.", "Investigate the role of CR-induced circulating GPX3 in rejuvenating the aged hippocampus."],
    "approach": "Investigate the mechanisms by which CR blood plasma rejuvenates the aged brain.",
    "expectedOutcomes": ["Identify a potential blood-based therapeutic approach to confer the cognitive benefits of CR.", "Increase the translational potential of CR to counter age-related cognitive decline and aging-associated neurodegenerative diseases."]
  }
}

The most complete NIH research grant scraper available. It returns every field NIH RePORTER exposes for each funded project, including the full project identity, principal investigators, funded organization with geocode, institute, activity code, the complete cost breakdown, project and budget dates, research terms and abstract, plus optional AI add-ons (summary, keywords, field classification, structured extract), and gives you seven filters to target exactly the grants you need.

📥 Input · 📤 Output · 💰 Pricing · ▶️ Examples

Table of contents

• What it does
• Quickstart
• Input reference
• Output reference
• Example output record
• Run via API and CLI
• Fetch results
• Billing and limits
• FAQ and troubleshooting

What it does

The actor queries NIH RePORTER, applies the filters you pass as input, paginates through the matching projects, and writes one normalized record per grant to the run's dataset. Each record carries the full project identity, all principal investigators, the funded organization with geocode, the responsible institute or center, the activity code and funding mechanism, the complete cost breakdown (award, total, direct, indirect), project and budget dates, and the research terms and abstract text. Costs are returned as numbers and dates as YYYY-MM-DD.

Four optional AI add-ons run on a paid Apify plan: withAiSummary (a short plain-language summary), withAiKeywords (topical keywords), withAiField (research field classification), and withAiExtract (a structured aims / approach / expected-outcomes profile). Each is billed per grant only when it produces usable output.

Quickstart

Open the actor, paste this into the input, and press Run. It returns 10 CRISPR gene-editing grants.

{
  "textQuery": "crispr gene editing",
  "fiscalYears": ["2024"],
  "maxProjects": 10
}

Combine any of the filters below; at least one is required and all are matched together. Default maxProjects is 10.

Input reference

Field	Type	Required	Default	Description
textQuery	string	no	crispr gene editing	Free-text search across project title, abstract and research terms (for example alzheimer, vaccine).
piNames	string[]	no	(empty)	Investigator names (any part of the name), for example Doudna or Jennifer Doudna.
orgNames	string[]	no	(empty)	Funded organizations, for example Stanford University, Broad Institute.
states	string[]	no	(empty)	Two-letter US state codes of the funded organization, for example CA, MA, NY.
fiscalYears	string[]	no	["2024"]	One or more fiscal years, for example 2024, 2023.
activityCodes	string[]	no	(empty)	NIH activity codes (award types) to include, for example R01, R21, F32, U01.
orgCountry	string	no	(empty)	Full country name of the funded organization, for example UNITED STATES.
maxProjects	integer	no	10	Maximum number of funding records to collect. Minimum 1, maximum 100000.
withAiSummary	boolean	no	false	Paid add-on. Generate a 2-3 sentence plain-language summary from each abstract. Billed only when produced.
withAiKeywords	boolean	no	false	Paid add-on. Extract 5-10 topical keywords per grant. Billed only when produced.
withAiField	boolean	no	false	Paid add-on. Classify each grant's research field / discipline. Billed only when produced.
withAiExtract	boolean	no	false	Paid add-on. Extract a structured grant profile (aims, approach, expected outcomes) per project. Billed only when produced.

At least one search filter is required. Filters combine with logical AND.

Output reference

One dataset item per grant. Types: string, integer, number, boolean, string[], object, or null when the source value is absent.

Field	Type	Description
projectNum	string	Full NIH project number.
coreProjectNum	string	Core project number.
applId	integer	Application ID.
fiscalYear	integer	Fiscal year.
projectTitle	string	Project title.
piName	string	Contact principal investigator.
piProfileId	integer	PI profile ID.
piTitle	string	PI job title.
allPiNames	string[]	All principal investigators.
piCount	integer	Number of PIs.
programOfficerName	string	Program officer.
orgName	string	Funded organization.
orgCity	string	Organization city.
orgState	string	Organization state.
orgCountry	string	Organization country.
orgType	string	Organization type.
orgZipcode	string	Organization ZIP.
orgUei	string	Organization UEI.
congDist	string	Congressional district.
latitude	number	Latitude.
longitude	number	Longitude.
icCode	string	Institute code.
icAbbreviation	string	Institute abbreviation.
icName	string	Institute / center name.
agencyCode	string	Funding agency.
activityCode	string	Activity code.
awardType	string	Award type.
awardAmount	number	Award amount (USD).
totalCostUsd	number	Total cost (USD).
directCostAmt	number	Direct cost (USD).
indirectCostAmt	number	Indirect cost (USD).
fundingMechanism	string	Funding mechanism.
mechanismCode	string	Mechanism code.
cfdaCode	string	CFDA code.
opportunityNumber	string	Funding opportunity number.
projectStartDate	string	Project start date (YYYY-MM-DD).
projectEndDate	string	Project end date (YYYY-MM-DD).
budgetStartDate	string	Budget start date (YYYY-MM-DD).
budgetEndDate	string	Budget end date (YYYY-MM-DD).
awardNoticeDate	string	Award notice date (YYYY-MM-DD).
isActive	boolean	Currently active.
isNew	boolean	New award.
covidResponse	string	COVID-19 response funding, or null.
arraFunded	string	ARRA funded (Y / N).
spendingCategories	string[]	Spending categories, or null.
terms	string[]	Research terms / keywords.
abstractText	string	Project abstract.
publicHealthRelevance	string	Public health relevance narrative.
url	string	Project detail URL.
source	string	Data source.
observedAt	string	ISO 8601 timestamp of when the record was collected.
aiSummary	string	AI plain-language summary (only when withAiSummary is on).
aiKeywords	string[]	AI keywords (only when withAiKeywords is on).
aiField	string	AI research field / discipline (only when withAiField is on).
aiExtract	object	AI structured grant profile (only when withAiExtract is on).

On a failed run, the actor writes a single item with a populated error field instead of grant records, and does not charge for it.

Example output record

See the hero record at the top of this README, taken from a real run with input {"textQuery": "alzheimer", "maxProjects": 3, "withAiSummary": true, "withAiKeywords": true, "withAiField": true, "withAiExtract": true}. The abstractText, publicHealthRelevance, and terms values are shown trimmed there; the full-length values are returned in the dataset.

Run via API and CLI

Start a run and wait for it to finish, then read the dataset. Replace <TOKEN> with your Apify API token.

Run synchronously and get dataset items in one call:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~usa-nih-reporter-scraper/run-sync-get-dataset-items?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"textQuery":"crispr gene editing","fiscalYears":["2024"],"maxProjects":25}'

Start a run asynchronously:

curl -X POST "https://api.apify.com/v2/acts/scrapers_lat~usa-nih-reporter-scraper/runs?token=<TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"orgNames":["Broad Institute"],"activityCodes":["R01"],"maxProjects":100}'

Apify CLI:

apify call scrapers_lat/usa-nih-reporter-scraper \
  --input '{"piNames":["Doudna"],"fiscalYears":["2024"]}'

Fetch results

Every run writes to a dataset. Fetch items as JSON, CSV, or Excel by changing format:

# JSON
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=json"

# CSV
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&clean=true&format=csv"

# Paginate large datasets
curl "https://api.apify.com/v2/datasets/<DATASET_ID>/items?token=<TOKEN>&offset=1000&limit=1000"

<DATASET_ID> is returned as defaultDatasetId in the run object. Use offset and limit to page through large result sets. clean=true drops empty and internal fields.

Billing and limits

• Pay per result. You are charged per record returned (result event). See the pricing tab for the current per-result price.
• AI add-ons billed separately. Each enabled AI add-on is billed per grant only when it returns usable output, and requires a paid Apify plan.
• No charge on failure. If a run errors, the actor writes a single item with a populated error field and does not charge for it. Empty runs cost nothing.
• Spend cap respected. Set maxTotalChargeUsd on the run; once reached, the actor stops emitting and charging further billable results.
• Free Apify plans are capped at 10 records per run. Upgrade for higher maxProjects.

FAQ and troubleshooting

A run returned 0 records. Why? The filter combination matched nothing in NIH RePORTER. Loosen filters (for example widen fiscalYears or drop activityCodes), or broaden the keyword. Zero-result runs are not charged.

Do I have to provide a keyword? At least one search filter is required, but it does not have to be textQuery. You can search by PI, organization, state, fiscal year, or activity code instead.

What is the difference between award amount and total cost? awardAmount and totalCostUsd are the funding figures RePORTER reports for the project year; directCostAmt and indirectCostAmt break the total into direct and indirect (overhead) components.

When are the AI fields populated? Only when you enable the matching add-on (withAiSummary, withAiKeywords, withAiField, withAiExtract) on a paid Apify plan and the abstract has enough text to work with. Otherwise those fields are omitted or null.

Why are abstracts so long? abstractText and publicHealthRelevance are the full narratives NIH publishes. They are returned verbatim; the hero example in this README trims them only for readability.

Is this an official NIH tool? No. This actor is independent and has no affiliation with the NIH. It reads only data that is publicly available through NIH RePORTER. Use it in accordance with the NIH RePORTER terms of service.

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• USGS Earthquakes Scraper: Global earthquake events from USGS.

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Independent tool, not affiliated with the NIH. Accesses only publicly available NIH RePORTER data. Use in accordance with the NIH RePORTER terms of service.