# NIH RePORTER Grants Normalizer (`wakey7dev/nih-reporter-normalizer`) Actor

Search NIH RePORTER for research grants with normalized institution names, PI names, and deduplication. 200+ institution mappings, org type classification.

- **URL**: https://apify.com/wakey7dev/nih-reporter-normalizer.md
- **Developed by:** [Chris Wakefield](https://apify.com/wakey7dev) (community)
- **Categories:** Business, AI
- **Features:** Limited permissions
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

![Chris The Dev](https://raw.githubusercontent.com/chriswakefield87/appstore-screenshot-translator/main/assets/actor-banner.png)

## NIH RePORTER Grants Normalizer 🏥

Search the NIH RePORTER database for research grants and get **cleaned, normalized, analysis-ready data**. No more messy institution names — Harvard Medical School, Brigham and Women's Hospital, and Boston Children's Hospital are all correctly identified and mapped.

### What it does

- 🔍 **Search** by organization name(s) or Principal Investigator name
- 🧹 **Normalize** institution names (200+ mappings covering all major NIH-funded institutions)
- 👤 **Standardize** PI names to consistent "Last, First" format
- 🏷️ **Classify** organizations by type (Academic, Hospital, Research Institute, Government, Industry)
- 📊 **Output** human-readable summary + machine-readable stats + full dataset
- 🗑️ **Deduplicate** projects by project number

### Input

| Field | Type | Description | Default |
|---|---|---|---|
| `orgNames` | string\[] | Organization name(s) to search (e.g. "Harvard University") | \["Harvard University"] |
| `piNames` | string\[] | PI names to search (e.g. "Collins, Francis") | \[] |
| `fiscalYears` | integer\[] | Fiscal years to filter (e.g. 2024, 2025) | \[2024, 2025] |
| `maxResults` | integer | Max grants to return (1–500) | 100 |
| `includeAbstracts` | boolean | Include project abstracts in output | false |

### Example input

```json
{
  "orgNames": ["Stanford University", "UCSF"],
  "fiscalYears": [2024, 2025],
  "maxResults": 50
}
```

### Example output

```
================================================================================
  NIH RePORTER GRANTS — NORMALIZED RESULTS
================================================================================
  Total grants:     47
  Duplicates:       3
  Total funding:    $28,450,000

    #  Grant Title                               Org                       PI                   FY    Cost
  ───  ─────────────────────────────────────     ─────────────────────     ──────────────────  ────  ──────────
    0  Mechanisms of synaptic plasticity in..    Stanford University       Sudhof, Thomas      2025  $2,100,000
    1  Neural circuits underlying decision..     Stanford University       Deisseroth, Karl    2025  $1,850,000
    2  Immunotherapy resistance in gliobla..     UCSF                      Lim, Wendell        2024  $3,200,000
  ...
```

### Output schema

| Property | Location | Description |
|---|---|---|
| `results` | Dataset items | Full normalized grant records |
| `summary` | KVS `OUTPUT` | Human-readable summary table |
| `stats` | KVS `STATS` | Machine-readable statistics |
| `data` | KVS `RESULTS` | Full results array for API consumers |

### Use cases

- **Pharma competitive intelligence**: Track competitor research partnerships and funding
- **Biotech investment research**: Identify hot research areas and top-funded institutions
- **University research offices**: Benchmark against peer institutions
- **Grant writers**: Analyze funding patterns by agency, mechanism, and fiscal year
- **Academic researchers**: Find collaborators and track emerging research trends

### Data source

Data from the [NIH RePORTER API](https://api.reporter.nih.gov/) — a free, public API providing access to NIH-funded research projects. No API key required. Contains 500,000+ projects across all NIH institutes.

### Pricing

This is a value-add actor with institution name normalization, PI name standardization, org type classification, and deduplication. See store listing for current pricing.

# Actor input Schema

## `orgNames` (type: `array`):

One or more organization names to search (e.g. Harvard, Stanford). Use comma or newline to separate. Leave empty to search by PI names instead.

## `piNames` (type: `array`):

Search by Principal Investigator name instead of organization. Use format: first last or last,first.

## `fiscalYears` (type: `array`):

Filter by fiscal years (e.g. 2024,2025). Leave empty for all years.

## `maxResults` (type: `integer`):

Maximum number of grants to return (1-500).

## `includeAbstracts` (type: `boolean`):

Include full project abstracts in output. Increases data size.

## Actor input object example

```json
{
  "orgNames": [
    "Harvard University"
  ],
  "piNames": [],
  "fiscalYears": [
    2024,
    2025
  ],
  "maxResults": 100,
  "includeAbstracts": false
}
```

# Actor output Schema

## `results` (type: `string`):

Complete list of normalized grant records.

## `summary` (type: `string`):

Human-readable summary table of results.

## `stats` (type: `string`):

Machine-readable statistics about the run.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "orgNames": [
        "Harvard University"
    ],
    "piNames": [],
    "fiscalYears": [
        2024,
        2025
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("wakey7dev/nih-reporter-normalizer").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "orgNames": ["Harvard University"],
    "piNames": [],
    "fiscalYears": [
        2024,
        2025,
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("wakey7dev/nih-reporter-normalizer").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "orgNames": [
    "Harvard University"
  ],
  "piNames": [],
  "fiscalYears": [
    2024,
    2025
  ]
}' |
apify call wakey7dev/nih-reporter-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wakey7dev/nih-reporter-normalizer"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/oOhR4Lxc2y2Kek71a/builds/1BAIIxTWBRNQDutmg/openapi.json