Medical AI

OpenClaw for Clinical Research Teams: Literature Summaries and Protocol Drafts

Clinical researchers spend enormous time reading and summarising literature, drafting protocol sections, and tracking regulatory submissions. OpenClaw on Slack automates literature summaries, drafts protocol sections from outlines, and tracks study milestones — giving researchers more time for actual science.

Huzaifa Tahir
7 min read

OpenClaw for Clinical Research Teams: Literature Summaries and Protocol Drafts


Clinical research is knowledge-intensive work. A research coordinator or junior researcher may spend 30–40% of their working time on tasks that are important but do not require their specific scientific expertise: reading through papers to extract key findings, drafting standard sections of study protocols, tracking IRB submission deadlines, and formatting study reports.


OpenClaw handles the parts of research workflow that are structured and repeatable — giving researchers more time for the thinking that only they can do.


Setting Up OpenClaw for a Research Team


```bash

curl -fsSL https://openclaw.ai/install.sh | bash

openclaw onboard --install-daemon

```


Connect Slack as the primary interface for the research team. Create channels: #research-qa, #literature-search, #protocol-drafts. Configure OpenClaw to respond in each with the appropriate skill.


Literature Summary Skill


A researcher pastes the full text (or abstract) of a paper into Slack and receives a structured summary:


```

Skill: literature-summary

Trigger: message in #literature-search Slack channel

Prompt: "Summarise the provided research paper in the following structured format:


**Citation:** Author(s), Year, Journal, DOI

**Study Design:** (RCT, cohort, case-control, systematic review, etc.)

**Population:** Who was studied (n, demographics, inclusion/exclusion criteria)

**Intervention/Exposure:** What was done or measured

**Primary Outcome:** What they were trying to show

**Key Findings:** Main results with statistics (p-values, confidence intervals, effect sizes) where available

**Limitations:** What the authors or the study design could not address

**Relevance to [our research question]:** A brief note on how this relates to our study area


Use precise language. Do not overstate findings. Note if a finding is statistically significant but clinically small."

```


A researcher can process 10 papers in the time it would previously take to process 3.


Protocol Section Drafts


Standard sections of clinical trial protocols follow established formats (ICH GCP guidelines, specific funder templates). A researcher sends an outline and OpenClaw drafts the section:


```

Skill: protocol-draft

Trigger: message in #protocol-drafts starting with "DRAFT:"

Example prompt: "DRAFT: Background section for a Phase II trial of [Drug X] in patients with treatment-resistant depression. Key points to include: current treatment landscape for TRD, mechanism of action of Drug X, preclinical data supporting efficacy, rationale for this study population and dose."

AI Prompt: "Draft a Background section for a clinical trial protocol based on the researcher's outline. Follow ICH E6 (R2) GCP guideline formatting conventions. Write in formal scientific prose appropriate for regulatory submission. Use hedged language ('evidence suggests', 'preliminary data indicate') rather than overclaiming. Flag with [CITATION NEEDED] wherever specific claims should be referenced. Provide approximately 600-900 words."

```


The researcher's job becomes editing and adding citations rather than drafting from scratch — saving 2–3 hours per protocol section.


Regulatory Submission Tracking


Clinical research has non-negotiable regulatory deadlines — IRB renewals, adverse event reporting windows, protocol amendment submissions, FDA/TGA correspondence. OpenClaw monitors the research calendar:


```

Skill: regulatory-calendar

Schedule: 0 8 * * 1 (Monday morning)

Prompt: "Review the regulatory calendar for [Study Name]. For the next 30 days, list all regulatory deadlines: IRB renewals, SAE reporting deadlines, protocol amendment approvals due, data safety monitoring board meetings, and any sponsor submissions. Flag any items due within 7 days as URGENT. Post to #research-regulatory Slack channel and send a direct message to the principal investigator."

```


Research Question Answering


During study design or literature review, researchers query OpenClaw directly for scientific information:


```

Skill: research-qa

Trigger: message in #research-qa Slack channel

Prompt: "Answer the clinical research question accurately, drawing on current scientific knowledge. For statistical or methodological questions, explain the concept clearly with an example relevant to clinical research. For clinical questions, provide the current evidence-based understanding and note key uncertainties. Always note the knowledge cutoff and recommend searching PubMed or Cochrane for the latest publications. For regulatory questions, note that this is general guidance only and official regulatory guidance documents should be consulted."

```


Consent Form Plain-Language Drafts


Informed consent forms must be written in plain language (typically 6th-grade reading level) but are often drafted in dense scientific prose that patients cannot understand. OpenClaw converts scientific language to plain language:


```

Skill: consent-plain-language

Trigger: researcher pastes a section of the consent form with "PLAIN LANGUAGE:" prefix

Prompt: "Rewrite this section of an informed consent form in plain, accessible language at approximately a 6th-grade reading level. Preserve all required information — risks, benefits, alternatives, voluntary participation. Use short sentences, everyday words, and an active voice. Use 'you' to address the participant directly. Check that no medical jargon remains unexplained."

```


What Research Teams Report


Research teams using OpenClaw for literature and protocol support report completing systematic literature reviews faster, spending less time on protocol drafting and more on study design, and producing better-quality first drafts of regulatory documents. The AI does not do the science — it clears the administrative path so researchers can.

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