📦 Clinical Trial Finder
特定の遺伝子や病状(疾患)に関連
📺 まず動画で見る(YouTube)
▶ 【Claude Code完全入門】誰でも使える/Skills活用法/経営者こそ使うべき ↗
※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。
📜 元の英語説明(参考)
Find clinical trials for a gene, variant, or condition from ClinicalTrials.gov + EUCTR, with FHIR R4 output
🇯🇵 日本人クリエイター向け解説
特定の遺伝子や病状(疾患)に関連
※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。
下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o clinical-trial-finder.zip https://jpskill.com/download/4072.zip && unzip -o clinical-trial-finder.zip && rm clinical-trial-finder.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/4072.zip -OutFile "$d\clinical-trial-finder.zip"; Expand-Archive "$d\clinical-trial-finder.zip" -DestinationPath $d -Force; ri "$d\clinical-trial-finder.zip"
完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。
💾 手動でダウンロードしたい(コマンドが難しい人向け)
- 1. 下の青いボタンを押して
clinical-trial-finder.zipをダウンロード - 2. ZIPファイルをダブルクリックで解凍 →
clinical-trial-finderフォルダができる - 3. そのフォルダを
C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-17
- 取得日時
- 2026-05-17
- 同梱ファイル
- 1
💬 こう話しかけるだけ — サンプルプロンプト
- › Clinical Trial Finder の使い方を教えて
- › Clinical Trial Finder で何ができるか具体例で見せて
- › Clinical Trial Finder を初めて使う人向けにステップを案内して
これをClaude Code に貼るだけで、このSkillが自動発動します。
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
Domain Decisions
-
Source database: ClinicalTrials.gov API v2 (
https://clinicaltrials.gov/api/v2) — the authoritative US registry mandated by FDAAA 801 (2007) and mirrored by WHO ICTRP. Chosen over EudraCT/EUCTR because it covers the largest global trial volume (>500 000 studies), provides a stable versioned REST API, and is the primary registry for FDA-regulated interventions. Reference: Zarin et al., NEJM 2011; 364:852–860. -
Query field:
query.cond(condition/disease field), notquery.term(free-text across all fields).query.condis indexed against MeSH descriptors by the NLM indexing pipeline, giving substantially better recall for condition queries than unstructured text search. Reference: ClinicalTrials.gov API v2 specification,https://clinicaltrials.gov/data-api/api. -
MeSH condition coding: MeSH IDs are read from
derivedSection.conditionBrowseModule.meshes— the NLM-curated MeSH mapping that ClinicalTrials.gov computes internally during study indexing. This avoids a separate NLM API call and uses the same vocabulary thatquery.condis indexed against, ensuring query/result consistency. Reference: NLM Medical Subject Headings,https://www.nlm.nih.gov/mesh/. -
Max results: 20 trials per query by default (configurable with
--max-results). Clinical actionability does not scale with result volume — a clinician reviewing >20 trials without eligibility pre-screening is unlikely to act on any. The default balances coverage with usability. -
Status display: All statuses returned are shown — no pre-filtering. Recruiting trials are highlighted; TERMINATED and WITHDRAWN trials are flagged with a distinct visual indicator and never omitted. Selective display of only active trials would introduce reporting bias and obscure negative evidence. Reference: Chan et al., PLoS Med 2004; 1:e62 (trial publication bias).
-
Phase reporting: Phases are reported verbatim from the API and mapped to HL7 FHIR R4
ResearchStudy.phasecodes. No lay-term substitution is made to preserve accuracy and avoid misrepresentation. -
FHIR version: FHIR R4, not R5. The ONC 21st Century Cures Act Final Rule (2020) mandates FHIR R4 for certified EHR systems in the US, making R4 the de facto standard for EHR interoperability with Epic, Cerner, and Oracle Health. R5 is in early adoption as of 2026 — using R5 would reduce compatibility with deployed infrastructure. Reference: 45 CFR Part 170,
https://www.healthit.gov/cures/sites/default/files/cures/2020-03/ONCCuresActFinalRule.pdf. -
FHIR resource type:
ResearchStudy— the canonical HL7 FHIR R4 resource for clinical trials. Status and phase codes map verbatim from the published R4 value sets:research-study-status(http://hl7.org/fhir/research-study-status) andresearch-study-phase(http://terminology.hl7.org/CodeSystem/research-study-phase). -
Gene enrichment source: OpenTargets Platform (
--genemode), not DisGeNET. DisGeNET requires a commercial API key as of 2026. OpenTargets is public, freely accessible, and aggregates evidence across GWAS, somatic mutation, differential expression, and literature sources into a single harmonised score. Reference: Ochoa et al., Nucleic Acids Research 2023; 51:D1353–D1359. -
Association score threshold: ≥ 0.6 (
--ot-min-score). The OpenTargets overall association score is a harmonic sum across evidence types, normalised to [0, 1]. Scores < 0.5 typically reflect single-source, indirect, or low-confidence associations. The 0.6 threshold retains multi-evidence, replicated associations while excluding speculative links. Reference: Ochoa et al. 2023 (above); OpenTargets Platform scoring documentation,https://platform-docs.opentargets.org/associations. -
Max diseases per gene: 5 (
--ot-max-diseases). Querying more diseases per gene produces diminishing returns on trial relevance and increases API load. The top-5 by association score covers the primary phenotypic spectrum of most disease genes without introducing noise from peripheral associations. -
Status filter (
--status): Optional post-fetch filter to a single recruitment status (e.g.RECRUITING). Applied client-side after the API call so the chart and summary always reflect unfiltered counts first — filtered output is a view, not a re-query. -
Reproducibility outputs: Every run writes
commands.sh(exact CLI to reproduce) andchecksums.sha256(SHA-256 of all outputs). This ensures results are auditable and re-runnable without ambiguity. -
Eligibility criteria: Not parsed. The API returns eligibility as unstructured free text. Automated parsing would require NLP and introduces a high error rate for clinical use — users must review the full trial record on ClinicalTrials.gov before making any enrollment decisions.
-
Retry with exponential backoff: Transient failures (HTTP 429, 5xx, network timeouts) are retried up to 3 times with exponential backoff (1s, 2s, 4s). Non-retryable errors (4xx except 429) raise immediately. This follows the retry pattern recommended by CT.gov API documentation for rate-limited endpoints.
-
Multi-page pagination: CT.gov API v2 caps
pageSizeat 1000. For queries requesting more, the skill paginates vianextPageTokenand accumulates results untilmax_resultsis reached. This ensures correct behaviour for large result sets without hitting API limits. -
Country filter (
--country): Uses CT.govquery.locnparameter to restrict results to trials in a specific country. Accepts ISO 3166-1 country names or codes. Applied at the API level (not post-fetch) to reduce bandwidth and improve relevance. -
EU Clinical Trials Register (
--euctr): Secondary European source queried as a best-effort complement. The EUCTR API returns XML with no versioning guarantees and may be unavailable. Results are normalised to the same schema as CT.gov trials and merged with deduplication. All EUCTR failures degrade gracefully to an empty list — the skill never fails due to EUCTR unavailability. -
Variant-to-trial pipeline (
--rsid): Queries the EBI GWAS Catalog REST API (/singleNucleotidePolymorphisms/{rsid}/associations?projection=associationBySnp) to resolve a dbSNP rsID to genome-wide significant disease traits (p < 5 x 10^-8), then searches CT.gov for each trait. Disease traits are ranked above biomarker measurements to maximise trial relevance. Gene symbols are extracted fromauthorReportedGenesin the association loci. Reference: Buniello et al., Nucleic Acids Research 2019; 47:D1005--D1012 (GWAS Catalog). -
HTML report: Self-contained HTML with inline CSS and JavaScript, no external dependencies. Trial cards are colour-coded by recruitment status. Interactive client-side filters (status, phase, free-text search) with a live counter allow users to narrow results without re-querying. Opens correctly from any file manager or browser without a web server.
-
CSV output: Always generated at
tables/trials.csv. List fields (conditions, interventions) are pipe-delimited to survive CSV parsing. Designed for direct import into Excel, R, or pandas. -
FHIR inline validation: When
--fhiris used, the generated Bundle is validated against basic structural rules: required fields, status/phase value set membership, entry count consistency. This catches authoring errors before an external validator (e.g., HAPI) is needed.
Safety Rules
- Never suggest a patient enroll in a trial — always direct them to a clinician or the trial's contact listed on ClinicalTrials.gov
- Always include the ClawBio research-use disclaimer in every report
- Do not infer efficacy or safety from trial status alone — COMPLETED does not mean the intervention worked
- Flag TERMINATED and WITHDRAWN trials clearly with a visual indicator; never omit them from results
- Never fabricate NCT IDs, trial titles, or sponsor names — report only what the API returns
- Do not extrapolate trial eligibility across populations — a trial for adults does not apply to paediatric patients
Agent Boundary
The agent (LLM) dispatches the skill and explains results in plain language. The skill (Python) queries ClinicalTrials.gov and formats the output.
The agent must NOT:
- Invent trial data not returned by the API
- Override the 20-result default without the user explicitly requesting more
- Summarise eligibility criteria unless they appear verbatim in the API response
- Make clinical recommendations based on trial phase or status alone
- Modify the safety disclaimer or omit it from any report