# Biomedical Trial & Literature Evidence Report (`taroyamada/biomedical-trial-literature-evidence-report`) Actor Search PubMed through official NCBI E-utilities, monitor new publications, and generate citation-metadata literature reports and exports. - **URL**: https://apify.com/taroyamada/biomedical-trial-literature-evidence-report.md - **Developed by:** [naoki anzai](https://apify.com/taroyamada) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $8.00 / 1,000 biomedical evidence rows This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use 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 ## Biomedical Trial & Literature Evidence Report Biomedical research, medical affairs, and evidence teams use this Actor to compare ClinicalTrials.gov records with PubMed citation metadata. Input trial-literature watchlists, NCT IDs, conditions, interventions, PubMed queries, and a recurring monitor key. Get source-linked evidence rows, trial-to-literature gap alerts, evidence reports, and research exports from official APIs. ### Store Quickstart ```json { "watchlists": [{ "id": "cancer-immunotherapy", "conditions": ["cancer"], "interventions": ["immunotherapy"], "pubmedQuery": "cancer immunotherapy clinical trial" }], "searchTerms": ["cancer immunotherapy clinical trial"], "fromDate": "2026", "sort": "most_recent", "maxArticles": 25, "runMode": "monitor", "monitorKey": "cancer-immunotherapy-evidence", "initialRunMode": "emit_backfill", "emitRawRows": false, "generateReport": true, "generateExport": false, "maxChargeUsd": 3, "dryRun": false } ```` The default `initialRunMode: "baseline_only"` stores the first trial and literature baseline with zero rows and zero charge. An unchanged later run also emits zero rows and zero charge. ### Run the next report - Use [OpenAlex Research Intelligence](https://apify.com/taroyamada/openalex-research-intelligence) for broader cross-domain publication metadata. ### Input examples #### Current literature report ```json { "searchTerms": ["GLP-1 obesity"], "fromDate": "2025", "maxResultsPerQuery": 25, "maxArticles": 50, "runMode": "audit", "emitRawRows": false, "generateReport": true, "dryRun": false } ``` #### PMID metadata export ```json { "pmids": ["39763750", "39763800"], "runMode": "extract", "emitRawRows": true, "generateReport": false, "generateExport": true, "dryRun": false } ``` #### New-publication monitor ```json { "searchTerms": ["CAR-T solid tumor"], "sort": "most_recent", "maxArticles": 100, "runMode": "monitor", "monitorKey": "car-t-solid-tumor-watch", "initialRunMode": "baseline_only", "emitRawRows": false, "generateReport": true, "generateExport": false, "dryRun": false } ``` The first baseline-only monitor emits no rows. Later runs emit only changed trials, newly observed PMIDs, evidence gaps, and requested reports. ### Sample output ```json { "rowType": "literature_update_report", "billingEventName": "biomedical-evidence-report", "query": { "searchTerms": ["cancer immunotherapy"], "fromDate": "2026" }, "articleCount": 12, "pmids": ["39763750", "39763800"], "topJournals": [{"value": "Cancer Research", "count": 3}], "summary": "12 PubMed publications matched this literature update.", "sourceUrl": "https://pubmed.ncbi.nlm.nih.gov/" } ``` ### Pricing | Event | Price | Emitted when | | --- | ---: | --- | | `biomedical-evidence-row` | $0.008 | A normalized trial or literature evidence row is emitted | | `evidence-gap-alert` | $0.15 | A saved monitor observes a source-linked evidence gap | | `biomedical-evidence-report` | $5.00 | A trial and literature evidence report is generated | | `biomedical-evidence-export` | $3.00 | A normalized evidence export is generated | There is no start charge. Use `emitRawRows: false` for report-first runs, and `maxChargeUsd` to cap planned Actor charges. ### Source and limits - Uses official NCBI ESearch and ESummary JSON endpoints; no browser scraping or login is required. - An optional free NCBI API key increases the documented request allowance. Keyless mode is paced conservatively. - This Actor exports citation metadata, not article full text or abstracts. - PubMed records can be incomplete or updated after publication. ### Compliance Outputs support literature research and screening workflows. They are not medical advice, clinical efficacy claims, or a substitute for reviewing the source publication. Keep NCBI attribution and source URLs in downstream reports. # Actor input Schema ## `searchTerms` (type: `array`): PubMed query strings passed to NCBI ESearch. ## `pmids` (type: `array`): Known PubMed IDs to summarize directly. ## `fromDate` (type: `string`): Optional publication date lower bound accepted by PubMed. ## `toDate` (type: `string`): Optional publication date upper bound accepted by PubMed. ## `sort` (type: `string`): PubMed result order for query searches. ## `maxResultsPerQuery` (type: `integer`): Maximum PMIDs fetched from each query. ## `maxArticles` (type: `integer`): Maximum deduplicated PubMed records processed in one run. ## `maxStudiesPerWatchlist` (type: `integer`): Maximum ClinicalTrials.gov studies returned for each watchlist. ## `maxPagesPerWatchlist` (type: `integer`): Maximum ClinicalTrials.gov pages fetched for each watchlist. ## `runMode` (type: `string`): Extract returns metadata, audit generates a current report, and monitor emits new PMIDs. ## `monitorKey` (type: `string`): Stable private state namespace for a scheduled PubMed query. ## `initialRunMode` (type: `string`): Initial run mode for this run. ## `emitRawRows` (type: `boolean`): Emit citation, author, and journal metadata rows. ## `generateReport` (type: `boolean`): Generate one query-level literature update report when matches are emitted. ## `generateExport` (type: `boolean`): Generate one citation metadata export for screening workflows. ## `tool` (type: `string`): Tool identifier sent to NCBI E-utilities. ## `apiKey` (type: `string`): Optional NCBI API key. NCBI\_API\_KEY is used when this is empty. ## `timeoutMs` (type: `integer`): Maximum time for each NCBI request. ## `delivery` (type: `string`): Keep dataset only or also POST the billed row payload to an HTTPS webhook. ## `webhookUrl` (type: `string`): Optional public HTTPS destination when delivery is webhook. ## `maxChargeUsd` (type: `number`): Optional Actor-side spending cap; zero uses only the Apify run limit. ## `dryRun` (type: `boolean`): Return illustrative rows without NCBI requests or billing. ## `watchlists` (type: `array`): Named portfolio watch definitions. ## `emitUnchanged` (type: `boolean`): Emit unchanged for this run. ## Actor input object example ```json { "searchTerms": [ "cancer immunotherapy" ], "pmids": [], "fromDate": "", "toDate": "", "sort": "most_recent", "maxResultsPerQuery": 25, "maxArticles": 100, "maxStudiesPerWatchlist": 25, "maxPagesPerWatchlist": 1, "runMode": "monitor", "monitorKey": "", "initialRunMode": "baseline_only", "emitRawRows": false, "generateReport": true, "generateExport": false, "tool": "biomedical-trial-literature-evidence-report", "timeoutMs": 20000, "delivery": "dataset", "maxChargeUsd": 0, "dryRun": true, "watchlists": [], "emitUnchanged": false } ``` # 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 = { "searchTerms": [ "cancer immunotherapy" ] }; // Run the Actor and wait for it to finish const run = await client.actor("taroyamada/biomedical-trial-literature-evidence-report").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 = { "searchTerms": ["cancer immunotherapy"] } # Run the Actor and wait for it to finish run = client.actor("taroyamada/biomedical-trial-literature-evidence-report").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 '{ "searchTerms": [ "cancer immunotherapy" ] }' | apify call taroyamada/biomedical-trial-literature-evidence-report --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taroyamada/biomedical-trial-literature-evidence-report", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Biomedical Trial & Literature Evidence Report", "description": "Search PubMed through official NCBI E-utilities, monitor new publications, and generate citation-metadata literature reports and exports.", "version": "0.1", "x-build-id": "dIkcnumQCORrf22hf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taroyamada~biomedical-trial-literature-evidence-report/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taroyamada-biomedical-trial-literature-evidence-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/taroyamada~biomedical-trial-literature-evidence-report/runs": { "post": { "operationId": "runs-sync-taroyamada-biomedical-trial-literature-evidence-report", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/taroyamada~biomedical-trial-literature-evidence-report/run-sync": { "post": { "operationId": "run-sync-taroyamada-biomedical-trial-literature-evidence-report", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "searchTerms": { "title": "PubMed search terms", "type": "array", "description": "PubMed query strings passed to NCBI ESearch.", "items": { "type": "string" }, "default": [] }, "pmids": { "title": "PMIDs", "type": "array", "description": "Known PubMed IDs to summarize directly.", "items": { "type": "string" }, "default": [] }, "fromDate": { "title": "From publication date", "type": "string", "description": "Optional publication date lower bound accepted by PubMed.", "default": "" }, "toDate": { "title": "To publication date", "type": "string", "description": "Optional publication date upper bound accepted by PubMed.", "default": "" }, "sort": { "title": "Sort", "enum": [ "relevance", "pub_date", "most_recent" ], "type": "string", "description": "PubMed result order for query searches.", "default": "most_recent" }, "maxResultsPerQuery": { "title": "Results per query", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum PMIDs fetched from each query.", "default": 25 }, "maxArticles": { "title": "Maximum unique articles", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum deduplicated PubMed records processed in one run.", "default": 100 }, "maxStudiesPerWatchlist": { "title": "Studies per watchlist", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum ClinicalTrials.gov studies returned for each watchlist.", "default": 25 }, "maxPagesPerWatchlist": { "title": "Pages per watchlist", "minimum": 1, "maximum": 5, "type": "integer", "description": "Maximum ClinicalTrials.gov pages fetched for each watchlist.", "default": 1 }, "runMode": { "title": "Run mode", "enum": [ "extract", "audit", "monitor" ], "type": "string", "description": "Extract returns metadata, audit generates a current report, and monitor emits new PMIDs.", "default": "monitor" }, "monitorKey": { "title": "Monitor key", "type": "string", "description": "Stable private state namespace for a scheduled PubMed query.", "default": "" }, "initialRunMode": { "title": "Initial run mode", "enum": [ "baseline_only", "emit_backfill" ], "type": "string", "description": "Initial run mode for this run.", "default": "baseline_only" }, "emitRawRows": { "title": "Emit raw rows", "type": "boolean", "description": "Emit citation, author, and journal metadata rows.", "default": false }, "generateReport": { "title": "Generate report", "type": "boolean", "description": "Generate one query-level literature update report when matches are emitted.", "default": true }, "generateExport": { "title": "Generate systematic-review export", "type": "boolean", "description": "Generate one citation metadata export for screening workflows.", "default": false }, "tool": { "title": "NCBI tool name", "type": "string", "description": "Tool identifier sent to NCBI E-utilities.", "default": "biomedical-trial-literature-evidence-report" }, "apiKey": { "title": "NCBI API key", "type": "string", "description": "Optional NCBI API key. NCBI_API_KEY is used when this is empty." }, "timeoutMs": { "title": "Request timeout", "minimum": 1000, "maximum": 60000, "type": "integer", "description": "Maximum time for each NCBI request.", "default": 20000 }, "delivery": { "title": "Additional delivery", "enum": [ "dataset", "webhook" ], "type": "string", "description": "Keep dataset only or also POST the billed row payload to an HTTPS webhook.", "default": "dataset" }, "webhookUrl": { "title": "Webhook URL", "type": "string", "description": "Optional public HTTPS destination when delivery is webhook." }, "maxChargeUsd": { "title": "Maximum charge (USD)", "minimum": 0, "maximum": 1000, "type": "number", "description": "Optional Actor-side spending cap; zero uses only the Apify run limit.", "default": 0 }, "dryRun": { "title": "Dry run", "type": "boolean", "description": "Return illustrative rows without NCBI requests or billing.", "default": true }, "watchlists": { "title": "Portfolio watchlists", "type": "array", "description": "Named portfolio watch definitions.", "default": [] }, "emitUnchanged": { "title": "Emit unchanged", "type": "boolean", "description": "Emit unchanged for this run.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```