# How to use an agent to find clinical trials for a research question

> A worked clinical-trial search: discover candidate studies, narrow by design and recruitment status, and inspect the original registry records.

- Canonical URL: https://www.searchforagents.com/blog/how-to-use-an-agent-to-find-clinical-trials
- Author: Mara Finch, Industry writer
- Published: 2026-09-25
- Updated: 2026-09-25
- Topic: Life Sciences
- Review due: 2026-12-25

## Direct answer

Define the condition, intervention, population, status, and geography first. Use a clinical-trials dataset and domain-filtered web search to find study records, then query structured trial metadata. Have the agent assemble a shortlist with registry IDs, phase, eligibility, locations, and open questions; check current recruitment and site details in the original registry.

## Key takeaways

- Make the condition, treatment, study status, population, and location explicit before searching.
- Combine registry-record discovery with structured trial fields for narrower research.
- Check the trial's arms and individual site statuses: a matching drug and overall recruiting status do not guarantee an applicable recruiting cohort or location.

An agent can save hours when a researcher asks, “Which studies might matter for this treatment question?” The output should be a **shortlist with reasons**, not a page of vaguely related links. To demonstrate, consider: **Which studies involving pembrolizumab and advanced non-small-cell lung cancer (NSCLC) are recruiting adults, and what populations and treatment arms do they study?** This is a research-landscape question, not a determination that a particular person is eligible.

We use three providers from the [market map](/market-map): [Valyu](https://valyu.ai) to search a clinical-trials dataset, [Dimensions](https://www.dimensions.ai) to query structured trial metadata, and [Perplexity](https://www.perplexity.ai) to search public registry pages. Each offers a different route to candidate studies; the [ClinicalTrials.gov](https://clinicaltrials.gov) record remains the place to inspect current study details. Search for Agents is produced by [Valyu](https://valyu.ai). The library calls below follow documented TypeScript interfaces for [Valyu](https://valyu.ai) and [Perplexity](https://www.perplexity.ai) and [Dimensions](https://www.dimensions.ai)' Python client; without subscriber credentials, we did not run the three provider queries or compare their retrieval quality. The named [ClinicalTrials.gov](https://clinicaltrials.gov) record was inspected separately on **25 September 2026**.

Install `valyu-js` and `@perplexity-ai/perplexity_ai` for the TypeScript examples with `npm install valyu-js @perplexity-ai/perplexity_ai`. The [Dimensions](https://www.dimensions.ai) example uses [Dimcli](https://digital-science.github.io/dimcli/) (`pip install dimcli`), the Python client documented by its publisher. Set `VALYU_API_KEY`, `DIMENSIONS_API_KEY`, and `PERPLEXITY_API_KEY` in your environment; [Dimensions](https://www.dimensions.ai) also needs the API endpoint supplied by your institution. Keep these examples on the server side, away from browser bundles.

## State the research question before searching

Give the agent five fields: condition (**advanced NSCLC**), intervention (**pembrolizumab, including combinations**), population (**adults**), status (**recruiting**), and geography (**anywhere initially; United States if location matters**). Ask it to return a study table with registry ID (NCT for [ClinicalTrials.gov](https://clinicaltrials.gov)), phase, treatment arms, biomarker and prior-treatment criteria, overall status, location status, last update, and registry link. This keeps a broad match from becoming a misleading recommendation.

In particular, a study that mentions NSCLC *somewhere* in its description and pembrolizumab *somewhere* in its interventions may be relevant only to a subset of patients or arms. Let the agent search broadly, then narrow by reading each registry record.

## 1. Discover candidate registry records

[Valyu](https://valyu.ai)'s [clinical-trials dataset](https://docs.valyu.ai/use-cases/healthcare) can be selected explicitly using its [TypeScript SDK](https://docs.valyu.ai/sdk/typescript-sdk/search):

```typescript
import { Valyu } from "valyu-js";

const results = await new Valyu().search(
  "Recruiting clinical trials for adults with advanced non-small cell lung cancer involving pembrolizumab, including combination arms",
  {
    searchType: "proprietary",
    includedSources: ["valyu/valyu-clinical-trials"],
    maxNumResults: 10,
    responseLength: "medium",
  },
);
if (!results.success) throw new Error("Trial search did not complete");
for (const hit of results.results) {
  console.log(hit.title, hit.url, hit.content.slice(0, 500));
}
```

For each hit, have the agent record the NCT number and the registry URL, then expand synonyms if the first pass is thin: “NSCLC,” “non-small-cell lung cancer,” “Keytruda,” and a particular mutation. Check the response status and warnings for incomplete search results. [Valyu](https://valyu.ai) documents this clinical-trials collection as **subscription-only** and says its trial data can lag by **24–48 hours**. Search relevance is a discovery tool, not an assertion that the study is still recruiting or that all its cohorts use pembrolizumab.

## 2. Filter the trial landscape

[Dimensions](https://www.dimensions.ai)' [clinical-trials source](https://docs.dimensions.ai/dsl/datasource-clinical_trials.html) exposes fields such as `overall_status`, `phase`, `conditions`, `interventions`, `study_eligibility_criteria`, and `linkout`. With institutional API access, [Dimcli](https://digital-science.github.io/dimcli/getting-started.html) handles authentication and runs a [Dimensions](https://www.dimensions.ai) Search Language (DSL) query. Set `DIMENSIONS_ENDPOINT` to your institution's full DSL v2 endpoint, such as `https://app.dimensions.ai/api/dsl/v2`:

```python
import os
import dimcli

dimcli.login(
    key=os.environ["DIMENSIONS_API_KEY"],
    endpoint=os.environ["DIMENSIONS_ENDPOINT"],
)
data = dimcli.Dsl().query('''
search clinical_trials for "non-small cell lung cancer pembrolizumab"
return clinical_trials[id + title + linkout + phase + overall_status + interventions + study_eligibility_criteria] limit 20
''').data
if "errors" in data:
    raise RuntimeError("Dimensions trial query did not complete")
for study in data.get("clinical_trials", []):
    print(study.get("id"), study.get("linkout"), study.get("overall_status"))
```

[Dimensions](https://www.dimensions.ai) returns JSON. Compare the returned `overall_status` values with the recruiting criterion and page beyond the first 20 records if necessary. If you add a server-side `where overall_status="..."` filter, inspect the actual status strings first rather than assuming one capitalization or registry vocabulary works everywhere. [Dimensions](https://www.dimensions.ai)' `id` is **its own trial identifier**; follow `linkout` to the original registry and obtain that registry's study ID (an NCT number for [ClinicalTrials.gov](https://clinicaltrials.gov)). Check whether a trial's `phase`, intervention arms, and eligibility meet the question. The indexed status may lag the registry; [Dimensions](https://www.dimensions.ai)' Analytics API requires an institutional subscription and is designed for analytical research, not as a general-purpose application backend.

## 3. Search public trial pages

[Perplexity](https://www.perplexity.ai)'s [Search SDK](https://docs.perplexity.ai/docs/search/quickstart) returns ranked web results and supports `search_domain_filter`. This lets an agent look for [ClinicalTrials.gov](https://clinicaltrials.gov) study pages using a separate web index:

```typescript
import Perplexity from "@perplexity-ai/perplexity_ai";

const results = await new Perplexity().search.create({
  query: "recruiting advanced non-small cell lung cancer pembrolizumab combination clinical trial adults",
  search_domain_filter: ["clinicaltrials.gov"],
  max_results: 10,
});
for (const page of results.results) {
  console.log(page.title, page.url, page.snippet);
}
```

Read the result URLs and excerpts to locate candidate NCT records, then open the originals. This is a useful second discovery route if a dataset query has missed a name or synonym, **not** a structured filter on registry status. A result's rank or snippet cannot establish that a trial is recruiting now; a web index may be incomplete or behind the registry. For publications associated with a shortlisted trial, search [PubMed](https://pubmed.ncbi.nlm.nih.gov) separately and keep those bibliographic records distinct from the trial registrations.

## What the agent can learn from one real registry hit

A direct [ClinicalTrials.gov](https://clinicaltrials.gov) [study search for NSCLC, pembrolizumab, and overall recruiting status](https://clinicaltrials.gov/data-api/about-api) surfaced [**NCT05789082**](https://clinicaltrials.gov/study/NCT05789082) in our 25 September 2026 check. Its [registry API record](https://clinicaltrials.gov/api/v2/studies/NCT05789082) describes a **phase 1/2** study of **divarasib**, alone or in combinations, for previously untreated advanced or metastatic NSCLC with a **KRAS G12C mutation**. The overall study status was **recruiting**; its September 2026 update includes U.S. locations with different site-level statuses.

That result changes the research answer in three ways. First, it is **not a phase 3 pembrolizumab trial**. Second, pembrolizumab appears in **combination cohorts A and B**, while other cohorts use divarasib without it. Third, the biomarker, prior-treatment, and study-arm criteria matter: the title and overall recruiting label alone cannot tell a reader which cohort or site is relevant. The agent should place those details next to the NCT link, not merely output “recruiting pembrolizumab study.” Trial status, sites, and eligibility may change after this check.

## Ask for a research shortlist, not an eligibility decision

Close the workflow with a prompt the reader can adapt:

> From the trial records, build a table of studies recruiting adults with advanced NSCLC that include pembrolizumab in at least one arm. Give the registry ID (NCT where applicable), phase, combination partner, relevant arm, mutation and prior-treatment restrictions, overall status, location status, last update, and original registry link. Deduplicate results from the three searches by registry ID. Flag any uncertain match and list the questions a researcher should check with the study team.

For NCT05789082, the useful takeaway is not “eligible” or “effective.” It is: **a recruiting phase 1/2 divarasib study includes pembrolizumab in some arms for a defined NSCLC population; inspect the mutation requirement, specific cohort, and current site before following up.** That is knowledge a researcher can act on by opening the registry record and contacting the study team. The [industry-search source check](/blog/how-to-verify-search-results-across-finance-biomedical-and-law) shows why a discovered study and an official decision support different claims.

*Method note: Library syntax and access requirements were checked against the linked provider SDK documentation on 25 September 2026. The NCT05789082 example comes from the [ClinicalTrials.gov](https://clinicaltrials.gov) v2 study-search response checked that day, not from a matched test of [Valyu](https://valyu.ai), [Dimensions](https://www.dimensions.ai), and [Perplexity](https://www.perplexity.ai). Recheck the live registry before using the record for current recruitment or location information.*

## Definitions

- **NCT number:** The identifier for a study record in the U.S. public clinical-trial registry; use it to reopen the specific registration and track updates rather than treating a search result title as a stable reference.

## Frequently asked questions

### Does a recruiting trial mean every listed site is recruiting?

No. The overall study can be recruiting while individual locations have different statuses. Check the current location entry and study contact before treating a site as an option.

### Can a web search result tell me which trials are recruiting now?

No. A web search can discover a study page, but an indexed excerpt may be stale. Open the original registry record and check the overall status, location statuses, eligibility and last update.

### Does a matching treatment name mean every arm of a trial uses it?

No. A treatment may appear only in certain cohorts or combinations. Open the study record and match the intervention to its specific arms, population and eligibility criteria before adding the trial to a shortlist.

### What should an agent do when trial sources disagree about recruitment?

Reopen the original registry record, check its last posted update and the status of the relevant site, and record which source is older. If the conflict remains, label recruitment unconfirmed and ask the study team rather than treating either search result as current.

## Sources

1. [Valyu Healthcare use case and clinical-trials source](https://docs.valyu.ai/use-cases/healthcare) — Valyu
2. [Valyu Search API reference](https://docs.valyu.ai/api-reference/endpoint/search.md) — Valyu
3. [Valyu TypeScript SDK Search guide](https://docs.valyu.ai/sdk/typescript-sdk/search) — Valyu
4. [Dimensions clinical trials data source and fields](https://docs.dimensions.ai/dsl/datasource-clinical_trials.html) — Dimensions
5. [Dimensions DSL API access and authentication](https://docs.dimensions.ai/dsl/api.html) — Dimensions
6. [Dimcli Python library getting started](https://digital-science.github.io/dimcli/getting-started.html) — Digital Science
7. [Perplexity Search API quickstart and domain filtering](https://docs.perplexity.ai/docs/search/quickstart) — Perplexity
8. [ClinicalTrials.gov data API](https://clinicaltrials.gov/data-api/about-api) — U.S. National Library of Medicine
9. [Divarasib with or without other therapies in advanced non-small cell lung cancer, NCT05789082](https://clinicaltrials.gov/study/NCT05789082) — ClinicalTrials.gov
10. [ClinicalTrials.gov v2 record for NCT05789082](https://clinicaltrials.gov/api/v2/studies/NCT05789082) — ClinicalTrials.gov

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