# 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 - **Stats:** 2 total users, 1 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/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # 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 '' with your token const client = new ApifyClient({ 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 '' with your token. client = ApifyClient("") # 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("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=wakey7dev/nih-reporter-normalizer", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/oOhR4Lxc2y2Kek71a/builds/1BAIIxTWBRNQDutmg/openapi.json