clinical-research

Design clinical research informatics workflows compliant with CDISC and FDA regulations.

1|1|Updated May 16, 2026

Search Tags:#regulatory compliance #CDISC #clinical research #EDC #clinical informatics

Ready to run

npx skills add https://github.com/aks-builds/healthcareskills --skill clinical-research-aks-builds

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clinical-research
Source: https://github.com/aks-builds/healthcareskills/tree/main/skills/clinical-research
Command: npx skills add https://github.com/aks-builds/healthcareskills --skill clinical-research-aks-builds

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill unit helps users design, build, and operate clinical research informatics tools and workflows, ensuring compliance with regulatory standards and best practices.

Core Features & Use Cases

Clinical Research Informatics: Provide tools for building systems and workflows that turn protocols into clean, regulator-ready data.
Regulatory Compliance: Offer guidance on human subjects protection, FDA-regulated research, ICH GCP, and privacy regulations.
Data Capture: Offer insights into EDC, eSource, CDISC standards, and safety reporting.
Use Case: A user may need to design an eCRF for a clinical trial and ensure compliance with CDASH, SDTM, and ADaM standards. This skill provides information on how to do so and what considerations to take into account.

Quick Start

Use the clinical-research skill to understand the regulatory framework for a Phase 1 clinical trial with an IND.

Frequently Asked Questions about clinical-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design an eCRF for clinical trials that complies with CDISC and CDASH standards?▼

To design a compliant eCRF, apply CDASH standards for data capture and ensure alignment with CDISC formats. This skill provides guidance on eCRF design considerations and regulatory compliance checks required for clinical research data.

What is the best way to ensure clinical research data meets FDA regulations and ICH GCP?▼

The best way to ensure clinical research data meets FDA regulations and ICH GCP is to build workflows with automated compliance checks. This skill helps enforce human subjects protection, safety reporting, and regulatory standards throughout data processing.

Can I use Python to automate SDTM and ADaM dataset transformations for regulatory submissions?▼

Yes, you can use Python to automate SDTM and ADaM dataset transformations. This skill utilizes Python for clinical data processing and compliance checks to turn trial protocols into regulator-ready datasets.

Does this skill support Electronic Data Capture (EDC) and eSource integration workflows?▼

Yes, this skill supports EDC and eSource integration workflows. It provides insights into data capture methods and clinical research informatics tools needed for building systems that collect compliant clinical trial data.

When do I need to implement Common Rule compliance checks in clinical informatics workflows?▼

You need to implement Common Rule compliance checks when building clinical informatics workflows involving human subjects. This skill offers guidance on integrating privacy regulations, human subjects protection, and safety reporting into data operations.

How to build clinical research informatics tools for Phase 1 IND trials?▼

To build clinical research informatics tools for Phase 1 IND trials, define your regulatory framework first. This skill assists in designing systems that handle eCRF creation, EDC, safety reporting, and CDISC compliance for early-phase trials.