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Skills/google-deepmind/science-skills/clinical-trials-database
clinical-trials-database logo

clinical-trials-database

google-deepmind/science-skills
693 installs2K stars
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Installation

npx skills add https://github.com/google-deepmind/science-skills --skill clinical-trials-database

Summary

>

SKILL.md

Clinical Trials Database

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure

uv is installed and on PATH.

  1. User Notification: If LICENSE_NOTIFICATION.txt does not already exist in

this skill directory then (1) prominently notify the user to check the terms at https://clinicaltrials.gov/, then (2) create the file recording the notification text and timestamp.

Overview

Access worldwide clinical trial data from ClinicalTrials.gov via the REST API v2. The CLI script at scripts/clinical_trials_api.py wraps the API with dedicated flags for common filters (phase, age group, status, intervention, sponsor, etc.) so you rarely need to construct raw queries.

Core Rules

  • Use the Wrapper: ALWAYS execute the provided helper scripts to query the

database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.

  • Always use --fields — trial JSON records can be very large; restrict

to the data points you need.

  • Use --count-total first — check result volume before fetching all

records.

  • Paginate large result sets — use --limit with --page-token to

iterate.

  • Trust Search Filters: Do not manually re-filter results unless

explicitly asked to verify detailed eligibility.

  • Notification: If this skill is used, ensure this is mentioned in the

output.

Context Efficiency Warning

Trial JSON records can be very large. Always use the --fields parameter to restrict the response to only the data points you need. After writing to file, read only the fields you need rather than the entire file.

[!TIP] Use references/studies_schema.md to identify exact field paths for --fields.

Response Layout Summary

API responses contain a list of studies (usually in a studies[] array). Each study is split into protocolSection and optional resultsSection.

[!Tip] Use the shorthand aliases below with the --fields parameter to request specific data and keep responses small.

Top-Level Fields

  • totalCount — Total studies matching query (integer)
  • studies[] — Array of study objects
  • nextPageToken — cursor string for pagination

Common Study Fields (and shorthand alias)

  • Identification
  • protocolSection.identificationModule.nctId (NCTId) — Unique trial ID
  • protocolSection.identificationModule.briefTitle (BriefTitle) — Short

title

  • Status
  • protocolSection.statusModule.overallStatus (OverallStatus) —

Recruitment status

  • Description
  • protocolSection.descriptionModule.briefSummary (BriefSummary) —

Short description

  • Arms & Interventions
  • protocolSection.armsInterventionsModule.interventions

(ArmsInterventionsModule)

  • Eligibility
  • protocolSection.eligibilityModule.eligibilityCriteria

(EligibilityCriteria) — Inclusion/Exclusion

  • protocolSection.eligibilityModule.stdAges (StdAge) — CHILD, ADULT,

etc.

Consult references/studies_schema.md for full paths (Locations, Outcomes, Results) and common --fields recipes.

Commands

Search for studies

Use for: finding trials by disease, drug, phase, status, age group, or any combination of these filters.

uv run scripts/clinical_trials_api.py search \
  --condition "<disease>" \
  --intervention "<drug_or_treatment>" \
  --status "<status>" \
  --phase "<phase>" \
  --age-group "<age_group>" \
  --study-type "<study_type>" \
  --sponsor "<sponsor_name>" \
  --has-results \
  --sort "<field>:<asc|desc>" \
  --fields "<fields>" \
  --limit <N> \
  --count-total \
  --page-token "<token>" \
  --output /tmp/search_results.json

All flags are optional and combine via AND logic.

Flag reference:

  • --condition — Disease or condition to search for (e.g. `"cystic

fibrosis"`).

  • --intervention — Drug, device, or treatment name (e.g. "pembrolizumab").
  • --status — Recruitment status filter. Values: RECRUITING, COMPLETED,

NOT_YET_RECRUITING, ACTIVE_NOT_RECRUITING, ENROLLING_BY_INVITATION, TERMINATED, SUSPENDED, WITHDRAWN.

  • --phase — Trial phase filter. Values: PHASE1, PHASE2, PHASE3, PHASE4,

EARLY_PHASE1, NA.

  • --age-group — Patient age group filter. Values: CHILD (0–17), ADULT

(18–64), OLDER_ADULT (65+).

  • --study-type — Type of study. Values: INTERVENTIONAL, OBSERVATIONAL,

EXPANDED_ACCESS.

  • --sponsor — Lead sponsor or institution name (e.g. `"National Cancer

Institute"`).

  • --has-results — Boolean flag (no value needed). When present, filters for

studies that have results available on ClinicalTrials.gov.

  • --sort — Sort order as FieldName:asc or FieldName:desc. Common fields:

LastUpdatePostDate, EnrollmentCount, StudyFirstPostDate, StartDate.

  • --fields — Comma-separated list of JSON field names to include in the

response. Use this to keep responses small (e.g. "NCTId,BriefTitle,OverallStatus,Phase"). See references/studies_schema.md for available field paths.

  • --limit — Maximum number of studies to return per request (1–1000, default

10).

  • --count-total — Boolean flag (no value needed). When present, the response

includes a totalCount field showing the total number of matching studies across all pages.

  • --page-token — An opaque cursor string used to fetch the next page of

results. Obtain this value from the nextPageToken field in a previous search response. Do not construct this string yourself; always copy it verbatim from the API response. See the Pagination section below.

  • --advanced — Raw Essie filter expression for structured queries beyond the

dedicated flags (e.g. "AREA[LocationCountry]United States"). Combined with other flags via AND. See references/clinical_trials_api.md for syntax.

  • --output — (Required) File path where the JSON response is written.

Example — actively recruiting Phase 3 pediatric cystic fibrosis trials:

uv run scripts/clinical_trials_api.py search \
  --condition "cystic fibrosis" \
  --status RECRUITING \
  --phase PHASE3 \
  --age-group CHILD \
  --fields "NCTId,BriefTitle,OverallStatus,Phase" \
  --limit 10 \
  --output /tmp/cf_trials.json

Example — recruiting atezolizumab trials for esophageal cancer:

uv run scripts/clinical_trials_api.py search \
  --condition "esophageal cancer" \
  --intervention "Atezolizumab" \
  --status RECRUITING \
  --fields "NCTId,BriefTitle,Phase" \
  --limit 10 \
  --output /tmp/atezolizumab_trials.json

Retrieve a study by NCT ID

Use for: fetching full details of a specific trial when you already have the NCT identifier.

uv run scripts/clinical_trials_api.py get-study \
  <nct_id> [--fields "<fields>"] \
  --output /tmp/study.json

Returns a useful default set of fields if --fields is omitted: NCTId,BriefTitle,OverallStatus,Phase,BriefSummary, ConditionsModule,ArmsInterventionsModule,EligibilityModule

Structure of the default response:

{
  "protocolSection": {
    "identificationModule": {
      "nctId": "NCT00000000",
      "briefTitle": "Study Title"
    },
    "statusModule": {
      "overallStatus": "RECRUITING"
    },
    "descriptionModule": {
      "briefSummary": "This study is about..."
    },
    "conditionsModule": {
      "conditions": [ "Condition Name" ]
    },
    "armsInterventionsModule": {
      "interventions": [ { "type": "DRUG", "name": "Drug Name" } ]
    },
    "eligibilityModule": {
      "eligibilityCriteria": "Inclusion:\n- ...",
      "stdAges": [ "ADULT" ]
    }
  }
}

Get eligibility / inclusion criteria

Use for: pulling inclusion/exclusion rules, age ranges, and sex requirements for patient-matching tasks.

uv run scripts/clinical_trials_api.py \
  get-eligibility <nct_id> \
  --output /tmp/eligibility.json

Shortcut that returns title and the full eligibility module (inclusion/exclusion criteria, age range, sex).

Example — inclusion criteria for NCT04886804:

uv run scripts/clinical_trials_api.py \
  get-eligibility NCT04886804 \
  --output /tmp/eligibility_NCT04886804.json

Count matching studies

Use for: exploring the trial landscape — checking how many trials exist for a condition, phase, or status before fetching full records.

uv run scripts/clinical_trials_api.py count \
  --condition "<disease>" \
  [--status "<status>"] [--phase "<phase>"] ... \
  --output /tmp/count.json

Returns only the total count of clinical trials matching the search criteria without fetching study records. Accepts the same filter flags as search.

Search by location / geography

Use for: narrowing trials to a specific country, state, or city.

Use --advanced with AREA[LocationCountry] or AREA[LocationCity] to restrict results by geography:

uv run scripts/clinical_trials_api.py search \
  --condition "cystic fibrosis" \
  --status RECRUITING \
  --advanced "AREA[LocationCity]New York" \
  --fields "NCTId,BriefTitle" \
  --limit 20 \
  --output /tmp/nyc_cf_trials.json

Search by sponsor / organization

Use for: identifying a sponsor's or institution's trial portfolio.

Use --sponsor to find trials run by a specific institution or company:

uv run scripts/clinical_trials_api.py search \
  --sponsor "National Cancer Institute" \
  --fields "NCTId,BriefTitle,LeadSponsorName" \
  --limit 20 \
  --output /tmp/nci_trials.json

Combined multi-criteria search

Use for: complex queries that layer multiple filters (condition and drug and phase and geography and sponsor, etc.).

All flags combine via AND, so you can layer conditions, interventions, status, phase, geography, and sponsor in a single query:

uv run scripts/clinical_trials_api.py search \
  --condition "pancreatic cancer" \
  --intervention "immunotherapy" \
  --status RECRUITING \
  --phase PHASE3 \
  --advanced "AREA[LocationCountry]United States" \
  --fields "NCTId,BriefTitle,Phase,LeadSponsorName" \
  --limit 20 \
  --output /tmp/panc_trials.json

Raw API query (escape hatch)

Use for: uncommon endpoints or parameter combinations not covered by the dedicated flags.

uv run scripts/clinical_trials_api.py raw-query \
  --endpoint <path> \
  --params '<json_dict>' \
  --output /tmp/raw_result.json

Pagination

When results exceed --limit, the response includes a nextPageToken. Pass it with --page-token to fetch the next page:

uv run scripts/clinical_trials_api.py search \
  --condition "breast cancer" \
  --status RECRUITING \
  --limit 50 --count-total \
  --output /tmp/breast_cancer_p1.json

uv run scripts/clinical_trials_api.py search \
  --condition "breast cancer" \
  --status RECRUITING \
  --limit 50 --page-token "CAo=" \
  --output /tmp/breast_cancer_p2.json

Advanced Querying

For complex filtering beyond the dedicated flags, use --advanced with an Essie expression.

What is an Essie Expression? Essie is the search engine powering ClinicalTrials.gov. An Essie expression is a structured query that targets specific fields (e.g., country, phase) rather than doing general keyword searches.

  • AREA[Field]Value: Targets a specific field.
  • AREA[LocationCountry]United States
  • AREA[Phase]PHASE3
  • Boolean operators: Combine with AND, OR, NOT.
  • RANGE[min, max]: For numeric/date fields (e.g. RANGE[500, MAX]).

See references/clinical_trials_api.md for syntax and available fields.

It is combined with other flags via AND:

uv run scripts/clinical_trials_api.py search \
  --condition "diabetes" \
  --advanced "AREA[LocationCountry]United States \
    AND AREA[EnrollmentCount]RANGE[500, MAX]" \
  --fields "NCTId,BriefTitle,EnrollmentCount" \
  --output /tmp/diabetes_us_large.json

References

  • API parameters, enum values, and Essie syntax:

references/clinical_trials_api.md

  • JSON field paths and --fields recipes: references/studies_schema.md

Score

0–100
57/ 100

Grade

C

Popularity17/30

693 installs — growing adoption. Source repo has 1,889 GitHub stars.

Completeness19/30

Documented: full SKILL.md body, one-line install. Missing: description, category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Clinical Trials Database skill score badge previewScore badge

Markdown

[![Clinical Trials Database skill](https://www.remoteopenclaw.com/skills/google-deepmind/science-skills/clinical-trials-database/badges/score.svg)](https://www.remoteopenclaw.com/skills/google-deepmind/science-skills/clinical-trials-database)

HTML

<a href="https://www.remoteopenclaw.com/skills/google-deepmind/science-skills/clinical-trials-database"><img src="https://www.remoteopenclaw.com/skills/google-deepmind/science-skills/clinical-trials-database/badges/score.svg" alt="Clinical Trials Database skill"/></a>

Clinical Trials Database FAQ

How do I install the Clinical Trials Database skill?

Run “npx skills add https://github.com/google-deepmind/science-skills --skill clinical-trials-database” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Clinical Trials Database skill do?

> The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Clinical Trials Database skill free?

Yes. Clinical Trials Database is a free, open-source skill published from google-deepmind/science-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Clinical Trials Database work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Clinical Trials Database works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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