# Clinical Trials & FDA Pipeline Intelligence Scraper (`constructive_calm/clinical-trials-fda-scraper`) Actor Unified clinical-trial + FDA intelligence: trial search, drug approvals, 510(k) and PMA device clearances, adverse events, recalls, drug shortages, and a sponsor-pipeline rollup. Built on official ClinicalTrials.gov v2 + OpenFDA APIs. Zero anti-bot. Optional Gemini AI summaries. - **URL**: https://apify.com/constructive\_calm/clinical-trials-fda-scraper.md - **Developed by:** [Omar Eldeeb](https://apify.com/constructive_calm) (community) - **Categories:** Agents, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $20.00 / 1,000 sponsor pipeline aggregateds 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Clinical Trials & FDA Pipeline Intelligence Scraper Unified clinical-trial + FDA intelligence in one actor. Search ClinicalTrials.gov, fetch FDA drug approvals, 510(k) and PMA device clearances, adverse events, recalls, and active drug shortages — and roll them all up into a single sponsor-pipeline view that no incumbent ships. Built on **two official, public, no-auth APIs**: ClinicalTrials.gov v2 and OpenFDA. Every output row carries a `verifyUrl` that links to the canonical public page so you can audit the data with one click. ### What does this actor do? It pulls structured biomedical regulatory data and unifies it into one normalized output shape. Ten modes cover the full surface: | Mode | Records returned | Buyer use case | |---|---|---| | `trials` | NCT records with phase, status, conditions, comparators, locations, primary endpoints | Search trials by indication / sponsor / phase / status | | `trial_details` | Full study record incl. eligibility criteria, secondary endpoints, sponsors/collaborators | Deep dives on specific NCTs | | `drug_approvals` | NDA / ANDA / BLA submissions with all status changes, products, NDCs | Approval timeline + commercial reality | | `device_clearances` | 510(k) + PMA records with decision date, decision, product code | Med-device pipeline tracking | | `adverse_events` | PII-stripped FAERS reports — reactions, seriousness, demographics | Pharmacovigilance signals | | `recalls` | FDA enforcement (Class I / II / III) — reason, distribution, status | Compliance & QA monitoring | | `shortages` | Active or resolved drug shortages with availability + reason | Hospital / pharmacy planning | | `pipeline` | **One row per sponsor** merging trials + approvals + clearances + recalls + shortages + next catalyst | Alt-data hedge fund, biotech VC, pharma BD | | `monitor` | Incremental change events vs. prior runs — new trials, status changes, new approvals, recalls | Scheduled daily / weekly diffs | | `ai_summary` | Gemini 2.5 Flash structured summary — TL;DR, risk flags, milestone class, outcome prior | Premium analyst layer | **Free trial:** the first 10 chargeable events of every run are free. Pay only on the 11th event onward. ### Why use this actor? - **Biotech VCs / hedge funds** — build a catalyst calendar from `pipeline.nextCatalystDate` and `upcomingMilestones[]`. Every trial readout, PDUFA-class submission, and 510(k) decision is normalized and ticker-tagged when the sponsor maps to an SEC filer. - **Pharma BD / corp dev** — find Phase 2 oncology assets at small biotechs, see their FDA submission history, then pivot to drug labels for MOA inference. Sponsor resolver bridges to SEC tickers when public. - **CROs / clinical operations** — query for `RECRUITING` Phase 3 trials in a target country, get full `locations[]` with city + facility + status. - **Insurance underwriters / pharmacovigilance teams** — pull adverse-event trends per drug with `serious=true` breakdowns. PII is stripped (no names, no contact info, no narrative free text) before the row is written. - **Hospital pharmacy / supply chain** — `shortages` mode lists every currently-active FDA drug shortage with availability, generic name, and affected NDCs. Schedule daily and pipe alerts. - **Compliance / QA** — `recalls` mode returns Class I / II / III enforcement actions with classification, recall reason, and distribution pattern. Combine with `monitor` for new-recall alerts. - **AI / LLM training** — every record has a stable PK (NCT, ANDA, k_number, recall_number) and a public `verifyUrl`. Perfect for grounded biomedical knowledge graphs. - **Public-health researchers** — trial geography by condition, sponsor class breakdowns, no API key required. ### How to use this actor 1. **Pick a mode** — see the table above. The most common starting points are `trials` (search) and `pipeline` (sponsor rollup). 2. **Set your filters** — conditions, phases, sponsor identifiers (ticker / name / domain / CIK), date range, etc. 3. **Run it** — first 10 chargeable events per run are free; you only pay on the 11th and beyond. Set `maxItems: -1` for unlimited bulk extraction (the actor uses `nextPageToken` and `search_after` pagination automatically). 4. **Verify any record** — click the `verifyUrl` field on any output row to land on the source's canonical page (clinicaltrials.gov, accessdata.fda.gov, etc.). 5. **Export** as JSON / CSV / Excel from the dataset, or hit the dataset API directly to chain into a downstream workflow. ### Input #### Search Phase 3 lung-cancer trials currently recruiting ```json { "mode": "trials", "conditions": ["non-small cell lung cancer"], "phases": ["PHASE3"], "statuses": ["RECRUITING"], "maxItems": 100 } ```` #### Full trial details by NCT ID ```json { "mode": "trial_details", "nctIds": ["NCT04368728", "NCT05636956"], "maxItems": 10 } ``` #### Pfizer's recent FDA drug approvals ```json { "mode": "drug_approvals", "sponsorIdentifiers": ["PFE"], "dateFrom": "2024-01-01", "maxItems": 50 } ``` #### Medtronic's 510(k) cardiac-monitor clearances ```json { "mode": "device_clearances", "applicantName": "Medtronic", "productCode": "DXN", "devicePathways": ["510k"], "maxItems": 25 } ``` #### Serious Ozempic adverse events ```json { "mode": "adverse_events", "drugName": "Ozempic", "seriousOnly": true, "maxItems": 200 } ``` #### Class I drug recalls in last 90 days ```json { "mode": "recalls", "recallClassifications": ["Class I"], "recallDomains": ["drug"], "dateFrom": "2026-02-01", "maxItems": 50 } ``` #### Active drug shortages ```json { "mode": "shortages", "shortageStatus": "currently_in_shortage", "maxItems": 100 } ``` #### Sponsor pipeline rollup (the killer mode) ```json { "mode": "pipeline", "sponsorIdentifiers": ["MRNA", "PFE", "LLY"], "maxItemsPerSource": 1000 } ``` #### Monitor for changes (run on a schedule) ```json { "mode": "monitor", "monitorTargets": ["NCT04368728", "MRNA", "PFE"], "maxItems": 100 } ``` #### AI-powered structured summary ```json { "mode": "ai_summary", "nctIds": ["NCT04368728"], "enableAiSummary": true } ``` ### Output #### Trial record (sample) ```json { "type": "trial", "id": "NCT06840782", "nctId": "NCT06840782", "briefTitle": "First-line Immunotherapy-based Standard of Care and Local Ablative Treatments for Oligometastatic NSCLC", "conditions": ["Oligometastatic Non-small Cell Lung Cancer (NSCLC)"], "interventions": [ { "type": "EXPERIMENTAL", "name": "Radiation: Radical local treatment", "description": "..." } ], "comparators": [ { "type": "ACTIVE_COMPARATOR", "name": "Drug: SoC-based immunotherapy", "description": "..." } ], "phase": "PHASE3", "status": "RECRUITING", "enrollmentTarget": 124, "actualEnrollment": 124, "studyDesign": { "allocation": "RANDOMIZED", "interventionModel": "PARALLEL", "masking": "NONE", "primaryPurpose": "TREATMENT" }, "primaryEndpoints": [ { "measure": "Overall Survival (OS)", "timeFrame": "From randomization up to two years", "description": "Time from randomization to documented death from any cause" } ], "sponsorClass": "OTHER", "locations": [ { "facility": "Gustave Roussy", "city": "Villejuif", "country": "France", "status": "RECRUITING" } ], "countries": ["France"], "primaryCompletionDate": "2030-02", "hasResults": false, "lastUpdateSubmitDate": "2025-09-12", "verifyUrl": "https://clinicaltrials.gov/study/NCT06840782", "scrapedAt": "2026-05-04T11:34:45.860Z" } ``` #### Pipeline record (sample, Moderna abridged) ```json { "type": "pipeline", "id": "0001682852", "ticker": "MRNA", "cik": "0001682852", "trialCountTotal": 111, "trialCountByPhase": { "PHASE1": 48, "PHASE2": 22, "PHASE3": 18, "PHASE4": 4 }, "trialCountByStatus": { "COMPLETED": 71, "RECRUITING": 12, "ACTIVE_NOT_RECRUITING": 19 }, "trialCountActiveRecruiting": 31, "drugApprovalCount": 1, "topConditions": [ { "condition": "SARS-CoV-2", "trialCount": 31 }, { "condition": "Influenza", "trialCount": 13 }, { "condition": "Respiratory Syncytial Virus", "trialCount": 11 } ], "upcomingMilestones": [ { "nctId": "NCT07089706", "milestone": "primary_completion", "date": "2026-08", "daysUntil": 92 } ], "nextCatalystDate": "2026-08", "nextCatalystType": "primary_completion", "nextCatalystId": "NCT07089706", "regulatorySignal": 0, "verifyUrl": "https://clinicaltrials.gov/search?spons=Moderna%20Inc" } ``` #### Verify any record | Record type | URL pattern | |---|---| | Trial | `https://clinicaltrials.gov/study/` | | Drug approval | `https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=<#>` | | 510(k) clearance | `https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=` | | PMA approval | `https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=` | | Recall | `https://www.accessdata.fda.gov/scripts/ires/index.cfm?Recall_Number=<#>` | ### How much does it cost? Pay-per-event pricing (the first 10 events of any run are free): | Event | Price | What you get | |---|---|---| | `trial-fetched` | $0.0003 | One CT.gov trial record | | `trial-details-fetched` | $0.0006 | Full trial detail (eligibility + endpoints + results) | | `drug-approval-fetched` | $0.0004 | One FDA drug application with all submissions | | `device-clearance-fetched` | $0.0004 | One 510(k) or PMA clearance | | `adverse-event-fetched` | $0.00015 | One PII-stripped FAERS report | | `recall-fetched` | $0.0004 | One FDA enforcement action | | `shortage-fetched` | $0.0004 | One drug-shortage record | | `pipeline-aggregated` | **$0.02** | One sponsor pipeline rollup (synthesizes 5+ source queries) | | `change-detected` | $0.0003 | One change event in monitor mode | | `ai-summary-generated` | $0.05 | One Gemini 2.5 Flash structured summary | #### Typical run costs - **100-trial NSCLC search:** ~$0.027 - **Pfizer drug approval scan (250 records):** ~$0.10 - **Daily class-I-recall watch (5 records / day):** ~$0.002 / day - **Weekly pipeline scan, top 10 biotech sponsors:** ~$0.20 / week - **Sponsor pipeline + AI summary (1 sponsor):** ~$0.07 Compare to enterprise alternatives: - Citeline / Datamonitor: $10K+/yr/seat - Phesi: $5K+/yr/seat - BioPharmaCatalyst: $99/mo - GlobalData Pharma: enterprise pricing ### Tips & advanced options - **Bulk extraction** — set `maxItems: -1` and the actor will use `search_after` (Link header `rel="next"`) on OpenFDA and `nextPageToken` on CT.gov to scroll through the entire dataset. There is no built-in cap. - **OpenFDA API key** — anonymous tier is 1,000 req/day per IP. For bulk users, set the optional `openFdaApiKey` input (free at https://open.fda.gov/apis/authentication, 120K req/day). - **Sponsor resolution** — every output row has `sponsor.matchConfidence` ∈ `{exact, alias, fuzzy, raw}`. `exact` = SEC ticker bridge, `alias` = hand-curated biopharma index (Wyeth → Pfizer, Genentech → Roche, etc.), `fuzzy` = token-set match, `raw` = passthrough. Audit ambiguous matches by checking the field. - **Monitor mode** — run on a schedule (Apify integrations → Schedule daily). The first run seeds fingerprints and emits 0 changes; subsequent runs emit only new or changed rows. - **Pipeline mode runtime** — for busy sponsors (Pfizer ≈ 600+ trials, ≈ 200 approvals), the parallel fan-out takes 30–60 seconds. Tighten with `maxItemsPerSource: 500` to reduce wall time. - **Combining mode + AI** — set `enableAiSummary: true` in `pipeline` mode to attach a Gemini structured summary to every sponsor row. Adds $0.05 per sponsor. - **Out of scope (v1)** — EU CTIS, WHO ICTRP, Health Canada, FDA orphan / breakthrough / fast-track designations. These are scoped for a future v2. ### Legal disclaimer This actor consumes only **public data from official US-government APIs** (ClinicalTrials.gov v2, OpenFDA). Both APIs are open, free, and explicitly distributed for re-use under federal open-data policy. The actor does not bypass authentication, does not scrape content from third-party sites, and does not violate the terms of service of either source. Adverse-event records are PII-stripped at emit time (`utils/piiStrip.ts`): emails, phone numbers, and SSN-shaped values are redacted. Patient identifiers are not present in the source data. This data is provided for research, analytical, and informational purposes only. **Do not use for medical decisions.** OpenFDA's own disclaimer states: "Do not rely on openFDA to make decisions regarding medical care." ### FAQ **Q: My sponsor returned `matchConfidence: "raw"`. Why?** A: Raw passthrough means the sponsor name didn't match an SEC ticker, didn't match a hand-curated biopharma alias, and didn't fuzzy-match within threshold. The actor still ran the query as-is. Either submit an SEC ticker / canonical name, or add the sponsor to your custom alias list (open a feature request). **Q: My pipeline mode showed `drugApprovalCount: 0` for a company that obviously has approvals.** A: OpenFDA tracks legal entities by sponsor\_name. Subsidiaries (e.g. ModernaTX, Inc.) may file under names that don't match the parent (Moderna Inc). Try passing the subsidiary string directly: `sponsorIdentifiers: ["ModernaTX, Inc."]`. Future v2 will widen the alias index. **Q: How fresh is the data?** A: ClinicalTrials.gov v2 reflects the current live database. OpenFDA datasets update on different cadences — drug approvals weekly, adverse events quarterly, recalls daily, shortages weekly. Each row's `scrapedAt` reflects when this actor fetched it; OpenFDA's last-update date is in `meta.last_updated` of the underlying API. **Q: Can I get EU trials?** A: Not in v1. EU CTIS uses an undocumented POST search endpoint and EUDRA-CT requires HTML scraping. Add as a feature request. **Q: Does the AI summary hallucinate?** A: Gemini 2.5 Flash with `thinkingBudget: 0` and `temperature: 0.2` is constrained to JSON output and only sees the structured record (no external context). It does not invent NCT IDs or sponsor names. Outcome priors are calibrated to BIO/Biomedtracker industry base rates (Phase 1→2 ~63%, Phase 2→3 ~31%, Phase 3→NDA ~58%, NDA→approval ~85%). **Q: How do I report a bug?** A: Open an issue on the Apify actor page or reach out via the developer's email (omar.eldeeb@remotegrowthpartners.com). # Actor input Schema ## `mode` (type: `string`): What to fetch. 'trials' searches ClinicalTrials.gov. 'trial\_details' fetches full records by NCT ID list. 'drug\_approvals' fetches FDA NDA/ANDA/BLA records. 'device\_clearances' fetches FDA 510(k) and PMA clearances. 'adverse\_events' fetches PII-stripped drug or device adverse-event reports. 'recalls' fetches FDA enforcement (Class I/II/III recalls). 'shortages' fetches FDA drug shortages. 'pipeline' merges trials + approvals + clearances + recalls + shortages into one row per sponsor. 'monitor' emits only changes since the last run. 'ai\_summary' generates Gemini 2.5 Flash structured summaries. ## `sponsorIdentifiers` (type: `array`): One or more sponsor identifiers. Accepts SEC tickers (PFE, MRNA, LLY), company names (Pfizer Inc, Moderna), domains (pfizer.com), or SEC CIK numbers. The actor auto-resolves via SEC company\_tickers + a hand-curated biopharma alias index, with fuzzy fallback. Every output row carries a sponsor.matchConfidence field so you can audit ambiguous matches. ## `nctIds` (type: `array`): Specific ClinicalTrials.gov NCT IDs to fetch in 'trial\_details' or 'ai\_summary' mode. Format: NCT followed by 8 digits, e.g. NCT04368728. ## `conditions` (type: `array`): Filter trials by condition / disease / indication. Examples: 'non-small cell lung cancer', 'type 2 diabetes', 'major depressive disorder'. Multi-word phrases are matched as a single term. ## `interventions` (type: `array`): Filter trials by intervention name. Can be a generic drug name (semaglutide), brand name (Ozempic), or device class (continuous glucose monitor). ## `phases` (type: `array`): Filter clinical trials by phase. Empty = all phases. ## `statuses` (type: `array`): Filter clinical trials by overall status. Empty = all statuses. ## `countries` (type: `array`): Filter trials by location country. ISO English country names (United States, United Kingdom, Germany). ## `applicantName` (type: `string`): Free-text applicant name for FDA device clearance search. The actor matches against OpenFDA's applicant field. ## `productCode` (type: `string`): FDA classification product code, e.g. DXN for cardiac monitor, OCM for blood-pressure monitor. See FDA Product Classification Database for the full list. ## `devicePathways` (type: `array`): Which FDA device clearance pathways to query. 510(k) = substantial-equivalence clearance, PMA = premarket approval (higher-risk). ## `drugName` (type: `string`): Brand or generic drug name to search adverse events for. The actor matches both patient.drug.openfda.brand\_name and generic\_name. ## `seriousOnly` (type: `boolean`): If enabled, only return serious adverse events (death, life-threatening, hospitalization, disability, congenital anomaly). ## `recallClassifications` (type: `array`): Filter recalls by classification. Class I = serious health risk, Class II = temporary or reversible health consequence, Class III = unlikely to cause harm. Empty = all. ## `recallDomains` (type: `array`): Which OpenFDA enforcement endpoints to query for recalls. ## `shortageStatus` (type: `string`): Filter drug shortages by status. 'Currently in Shortage' = active, 'Resolved' = closed. ## `dateFrom` (type: `string`): Lower bound for the mode's primary date field (YYYY-MM-DD). For trials = lastUpdateSubmitDate. For drug\_approvals = submission\_status\_date. For device\_clearances = decision\_date. For recalls = recall\_initiation\_date. Leave empty for no lower bound. ## `dateTo` (type: `string`): Upper bound for the mode's primary date field (YYYY-MM-DD). Leave empty for no upper bound. ## `maxItems` (type: `integer`): Maximum records to return. Set to -1 for unlimited (the actor uses search\_after / nextPageToken pagination automatically). Trial-mode free events are still capped — you only pay once you exceed the trial. ## `maxItemsPerSource` (type: `integer`): In pipeline mode, cap each source (CT.gov, OpenFDA drug, OpenFDA device, recalls, shortages) at this many rows when computing aggregates. Counts remain accurate via the API's totalCount; topN lists are sampled. Lower = faster. ## `incrementalMode` (type: `boolean`): If enabled, the actor saves a fingerprint of every emitted record. On the next run with the same input, only new or changed records are emitted. Pairs well with 'monitor' mode and Apify scheduled runs. ## `monitorTargets` (type: `array`): NCT IDs, sponsor identifiers, application numbers, or k\_numbers to watch in 'monitor' mode. The actor diffs against the prior fingerprints and emits only changes. ## `enableAiSummary` (type: `boolean`): If enabled in trial-related modes, an AI-powered structured summary (TL;DR + risk flags + milestone classification + outcome prior) is generated for each record via Gemini 2.5 Flash. Adds $0.05 per summary. ## `openFdaApiKey` (type: `string`): Optional OpenFDA API key for higher rate limits. Anonymous = 240 req/min and 1,000 req/day per IP. With a key = 240 req/min and 120,000 req/day. Get one free at https://open.fda.gov/apis/authentication. Leave empty to use anonymous tier. ## `proxyConfiguration` (type: `object`): ClinicalTrials.gov v2 and OpenFDA do not require proxies (no anti-bot, only fair-use rate limits). Leave empty in most cases. ## Actor input object example ```json { "mode": "trials", "sponsorIdentifiers": [ "PFE" ], "nctIds": [ "NCT04368728" ], "conditions": [ "non-small cell lung cancer" ], "interventions": [], "phases": [], "statuses": [], "countries": [], "applicantName": "Medtronic", "productCode": "", "devicePathways": [ "510k", "pma" ], "drugName": "Ozempic", "seriousOnly": false, "recallClassifications": [], "recallDomains": [ "drug", "device" ], "shortageStatus": "any", "dateFrom": "", "dateTo": "", "maxItems": 25, "maxItemsPerSource": 1000, "incrementalMode": false, "monitorTargets": [], "enableAiSummary": false, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset of trials, FDA approvals, clearances, adverse events, recalls, shortages, pipelines, and AI summaries. # 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 = { "sponsorIdentifiers": [ "PFE" ], "nctIds": [ "NCT04368728" ], "conditions": [ "non-small cell lung cancer" ], "applicantName": "Medtronic", "drugName": "Ozempic", "maxItems": 25, "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("constructive_calm/clinical-trials-fda-scraper").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 = { "sponsorIdentifiers": ["PFE"], "nctIds": ["NCT04368728"], "conditions": ["non-small cell lung cancer"], "applicantName": "Medtronic", "drugName": "Ozempic", "maxItems": 25, "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("constructive_calm/clinical-trials-fda-scraper").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 '{ "sponsorIdentifiers": [ "PFE" ], "nctIds": [ "NCT04368728" ], "conditions": [ "non-small cell lung cancer" ], "applicantName": "Medtronic", "drugName": "Ozempic", "maxItems": 25, "proxyConfiguration": { "useApifyProxy": false } }' | apify call constructive_calm/clinical-trials-fda-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=constructive_calm/clinical-trials-fda-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Clinical Trials & FDA Pipeline Intelligence Scraper", "description": "Unified clinical-trial + FDA intelligence: trial search, drug approvals, 510(k) and PMA device clearances, adverse events, recalls, drug shortages, and a sponsor-pipeline rollup. Built on official ClinicalTrials.gov v2 + OpenFDA APIs. Zero anti-bot. Optional Gemini AI summaries.", "version": "1.0", "x-build-id": "DFasTcGIveDGY79Nk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/constructive_calm~clinical-trials-fda-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-constructive_calm-clinical-trials-fda-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/constructive_calm~clinical-trials-fda-scraper/runs": { "post": { "operationId": "runs-sync-constructive_calm-clinical-trials-fda-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/constructive_calm~clinical-trials-fda-scraper/run-sync": { "post": { "operationId": "run-sync-constructive_calm-clinical-trials-fda-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "mode" ], "properties": { "mode": { "title": "Scraping mode", "enum": [ "trials", "trial_details", "drug_approvals", "device_clearances", "adverse_events", "recalls", "shortages", "pipeline", "monitor", "ai_summary" ], "type": "string", "description": "What to fetch. 'trials' searches ClinicalTrials.gov. 'trial_details' fetches full records by NCT ID list. 'drug_approvals' fetches FDA NDA/ANDA/BLA records. 'device_clearances' fetches FDA 510(k) and PMA clearances. 'adverse_events' fetches PII-stripped drug or device adverse-event reports. 'recalls' fetches FDA enforcement (Class I/II/III recalls). 'shortages' fetches FDA drug shortages. 'pipeline' merges trials + approvals + clearances + recalls + shortages into one row per sponsor. 'monitor' emits only changes since the last run. 'ai_summary' generates Gemini 2.5 Flash structured summaries.", "default": "trials" }, "sponsorIdentifiers": { "title": "Sponsors / companies (ticker, name, domain, or CIK)", "type": "array", "description": "One or more sponsor identifiers. Accepts SEC tickers (PFE, MRNA, LLY), company names (Pfizer Inc, Moderna), domains (pfizer.com), or SEC CIK numbers. The actor auto-resolves via SEC company_tickers + a hand-curated biopharma alias index, with fuzzy fallback. Every output row carries a sponsor.matchConfidence field so you can audit ambiguous matches.", "items": { "type": "string" }, "default": [] }, "nctIds": { "title": "NCT IDs (trial_details mode)", "type": "array", "description": "Specific ClinicalTrials.gov NCT IDs to fetch in 'trial_details' or 'ai_summary' mode. Format: NCT followed by 8 digits, e.g. NCT04368728.", "items": { "type": "string" }, "default": [] }, "conditions": { "title": "Medical conditions", "type": "array", "description": "Filter trials by condition / disease / indication. Examples: 'non-small cell lung cancer', 'type 2 diabetes', 'major depressive disorder'. Multi-word phrases are matched as a single term.", "items": { "type": "string" }, "default": [] }, "interventions": { "title": "Interventions / drugs / devices", "type": "array", "description": "Filter trials by intervention name. Can be a generic drug name (semaglutide), brand name (Ozempic), or device class (continuous glucose monitor).", "items": { "type": "string" }, "default": [] }, "phases": { "title": "Trial phases", "type": "array", "description": "Filter clinical trials by phase. Empty = all phases.", "items": { "type": "string", "enum": [ "EARLY_PHASE1", "PHASE1", "PHASE2", "PHASE3", "PHASE4", "NA" ], "enumTitles": [ "Early Phase 1", "Phase 1", "Phase 2", "Phase 3", "Phase 4", "Not applicable" ] }, "default": [] }, "statuses": { "title": "Trial statuses", "type": "array", "description": "Filter clinical trials by overall status. Empty = all statuses.", "items": { "type": "string", "enum": [ "NOT_YET_RECRUITING", "RECRUITING", "ENROLLING_BY_INVITATION", "ACTIVE_NOT_RECRUITING", "COMPLETED", "TERMINATED", "WITHDRAWN", "SUSPENDED", "UNKNOWN" ], "enumTitles": [ "Not yet recruiting", "Recruiting", "Enrolling by invitation", "Active, not recruiting", "Completed", "Terminated", "Withdrawn", "Suspended", "Unknown" ] }, "default": [] }, "countries": { "title": "Countries (trial locations)", "type": "array", "description": "Filter trials by location country. ISO English country names (United States, United Kingdom, Germany).", "items": { "type": "string" }, "default": [] }, "applicantName": { "title": "Applicant name (device_clearances mode)", "type": "string", "description": "Free-text applicant name for FDA device clearance search. The actor matches against OpenFDA's applicant field.", "default": "" }, "productCode": { "title": "FDA product code (3-letter code)", "type": "string", "description": "FDA classification product code, e.g. DXN for cardiac monitor, OCM for blood-pressure monitor. See FDA Product Classification Database for the full list.", "default": "" }, "devicePathways": { "title": "Device pathways", "type": "array", "description": "Which FDA device clearance pathways to query. 510(k) = substantial-equivalence clearance, PMA = premarket approval (higher-risk).", "items": { "type": "string", "enum": [ "510k", "pma" ], "enumTitles": [ "510(k)", "PMA" ] }, "default": [ "510k", "pma" ] }, "drugName": { "title": "Drug name (adverse_events mode)", "type": "string", "description": "Brand or generic drug name to search adverse events for. The actor matches both patient.drug.openfda.brand_name and generic_name.", "default": "" }, "seriousOnly": { "title": "Serious adverse events only", "type": "boolean", "description": "If enabled, only return serious adverse events (death, life-threatening, hospitalization, disability, congenital anomaly).", "default": false }, "recallClassifications": { "title": "Recall classifications", "type": "array", "description": "Filter recalls by classification. Class I = serious health risk, Class II = temporary or reversible health consequence, Class III = unlikely to cause harm. Empty = all.", "items": { "type": "string", "enum": [ "Class I", "Class II", "Class III" ], "enumTitles": [ "Class I (serious)", "Class II (reversible)", "Class III (unlikely harm)" ] }, "default": [] }, "recallDomains": { "title": "Recall domains", "type": "array", "description": "Which OpenFDA enforcement endpoints to query for recalls.", "items": { "type": "string", "enum": [ "drug", "device" ], "enumTitles": [ "Drug recalls", "Device recalls" ] }, "default": [ "drug", "device" ] }, "shortageStatus": { "title": "Shortage status", "enum": [ "any", "currently_in_shortage", "resolved" ], "type": "string", "description": "Filter drug shortages by status. 'Currently in Shortage' = active, 'Resolved' = closed.", "default": "any" }, "dateFrom": { "title": "Date from", "type": "string", "description": "Lower bound for the mode's primary date field (YYYY-MM-DD). For trials = lastUpdateSubmitDate. For drug_approvals = submission_status_date. For device_clearances = decision_date. For recalls = recall_initiation_date. Leave empty for no lower bound.", "default": "" }, "dateTo": { "title": "Date to", "type": "string", "description": "Upper bound for the mode's primary date field (YYYY-MM-DD). Leave empty for no upper bound.", "default": "" }, "maxItems": { "title": "Max items", "minimum": -1, "maximum": 100000, "type": "integer", "description": "Maximum records to return. Set to -1 for unlimited (the actor uses search_after / nextPageToken pagination automatically). Trial-mode free events are still capped — you only pay once you exceed the trial.", "default": 100 }, "maxItemsPerSource": { "title": "Max items per source (pipeline mode)", "minimum": 100, "maximum": 5000, "type": "integer", "description": "In pipeline mode, cap each source (CT.gov, OpenFDA drug, OpenFDA device, recalls, shortages) at this many rows when computing aggregates. Counts remain accurate via the API's totalCount; topN lists are sampled. Lower = faster.", "default": 1000 }, "incrementalMode": { "title": "Incremental mode (change detection)", "type": "boolean", "description": "If enabled, the actor saves a fingerprint of every emitted record. On the next run with the same input, only new or changed records are emitted. Pairs well with 'monitor' mode and Apify scheduled runs.", "default": false }, "monitorTargets": { "title": "Monitor targets (monitor mode)", "type": "array", "description": "NCT IDs, sponsor identifiers, application numbers, or k_numbers to watch in 'monitor' mode. The actor diffs against the prior fingerprints and emits only changes.", "items": { "type": "string" }, "default": [] }, "enableAiSummary": { "title": "Enable AI summary (premium event)", "type": "boolean", "description": "If enabled in trial-related modes, an AI-powered structured summary (TL;DR + risk flags + milestone classification + outcome prior) is generated for each record via Gemini 2.5 Flash. Adds $0.05 per summary.", "default": false }, "openFdaApiKey": { "title": "OpenFDA API key (optional)", "type": "string", "description": "Optional OpenFDA API key for higher rate limits. Anonymous = 240 req/min and 1,000 req/day per IP. With a key = 240 req/min and 120,000 req/day. Get one free at https://open.fda.gov/apis/authentication. Leave empty to use anonymous tier." }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "ClinicalTrials.gov v2 and OpenFDA do not require proxies (no anti-bot, only fair-use rate limits). Leave empty in most cases.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```