> ## Documentation Index
> Fetch the complete documentation index at: https://docs.consensus.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Check whether a finding has human evidence yet

> Separate cell and animal work from human studies for a claim, and report the ratio — the number that tells you how translated a finding really is.

## What you get

A clear split of the evidence into preclinical and human tiers, with counts for each, the strongest study in each, and an explicit verdict on whether the claim has ever been tested in people.

## Who it's for

Discovery and translational teams deciding whether a finding is ready to build on, investors doing scientific diligence, and anyone evaluating a claim that sounds better-established than it is.

## Why the ratio is the finding

A large preclinical literature reads as strong evidence. Forty mouse studies and zero human trials is a very different situation from four of each — but a naive literature summary presents both as "well studied". Making the tier split explicit is the entire point of this workflow.

## How it works

<Steps>
  <Step title="Run the same question at two tiers">
    One search restricted to preclinical designs, one restricted to human studies. Identical concept, deliberately different populations.
  </Step>

  <Step title="Use study types as the tier boundary">
    `study_types=animal` and `non-rct in vitro` isolate preclinical work. `human=true` with `rct`, `cohort study`, and `non-rct observational study` isolates the clinical tier.
  </Step>

  <Step title="Report both counts, always">
    Even when one is zero. Especially when one is zero.
  </Step>

  <Step title="Check whether the human work tested the same thing">
    Human studies often measure a surrogate rather than the outcome the preclinical work implied. A human trial of a biomarker is not a human trial of the disease outcome — say which you found.
  </Step>

  <Step title="Look for failed translation explicitly">
    Search for trials that ran and did not replicate the preclinical finding. This is the most informative and most frequently skipped search.
  </Step>
</Steps>

## The API calls

```bash theme={null}
# preclinical tier
curl -G "https://api.consensus.app/v1/search" \
  -H "x-api-key: $CONSENSUS_API_KEY" \
  --data-urlencode "query=senolytic clearance of senescent cells lifespan extension" \
  --data-urlencode "study_types=animal,non-rct in vitro" \
  --data-urlencode "page_size=100"

# human tier
curl -G "https://api.consensus.app/v1/search" \
  -H "x-api-key: $CONSENSUS_API_KEY" \
  --data-urlencode "query=senolytic therapy clinical trial outcomes older adults" \
  --data-urlencode "human=true" \
  --data-urlencode "study_types=rct,cohort study" \
  --data-urlencode "page_size=100"

# failed translation
curl -G "https://api.consensus.app/v1/search" \
  -H "x-api-key: $CONSENSUS_API_KEY" \
  --data-urlencode "query=senolytic trial did not replicate preclinical finding null result" \
  --data-urlencode "human=true" \
  --data-urlencode "page_size=50"
```

## Reporting it

| Tier                 | Papers | Strongest study | Verdict                       |
| -------------------- | ------ | --------------- | ----------------------------- |
| In vitro             | 34     | …               | Consistent effect             |
| Animal               | 41     | …               | Consistent across two species |
| Human observational  | 3      | …               | Association only              |
| Human interventional | 0      | —               | **Never tested in people**    |

The bottom row is the output. Everything above it is context.

## What to check before you trust it

* **Zero human studies may mean zero, or may mean your query missed them.** Confirm with a different phrasing before reporting an absence — human trials often use a compound name where preclinical work uses a mechanism.
* **Watch the surrogate outcome.** "Tested in humans" for a biomarker change is not "tested in humans" for the clinical outcome.
* **Species matters.** Effects in short-lived model organisms translate especially poorly for anything involving lifespan or ageing.
* **Absence of failed trials is not evidence of success.** Negative results are under-published, so a clean record may reflect publication bias.

## Related

<CardGroup cols={2}>
  <Card title="Build a drug target validation dossier" icon="dna" href="/use-cases/target-evidence-tiers">
    The full tiered dossier this check is one section of.
  </Card>

  <Card title="Grade a set of papers with your own evidence rubric" icon="scale-balanced" href="/use-cases/evidence-grading-rubric">
    Score what you find on a consistent scale.
  </Card>

  <Card title="Best practices" icon="shapes" href="/use-cases/best-practices">
    Filter ladder and the rest of the primitives.
  </Card>

  <Card title="All use cases" icon="grid-2" href="/use-cases">
    Browse the gallery by persona.
  </Card>
</CardGroup>