Programs and Initiatives

REDCap Services
CRISPI provides comprehensive REDCap services that enable investigators and research teams to efficiently design, implement, and manage secure, high-quality data collection solutions throughout the research lifecycle. As a collaborative partner within the REDCap Consortium, CRISPI works closely with Vanderbilt University Medical Center (VUMC), the creators of REDCap, to stay aligned with platform advancements, best practices, and emerging capabilities that benefit the NIH research community.

Our team partners with researchers from project planning through deployment, offering expert guidance in database design, electronic data capture workflows, survey development, longitudinal study configuration, data quality assurance, and regulatory best practices. In addition to secure REDCap hosting, CRISPI provides hands-on project development, user training, and ongoing technical support to help research teams maximize the platform's capabilities.

Whether supporting investigator-initiated studies, multi-site collaborations, or enterprise research programs, CRISPI delivers reliable REDCap solutions that improve data integrity, streamline study operations, and accelerate research productivity. For more information send an email to redcap@nih.gov.

Coming Soon: 21 CFR Part 11 Support
CRISPI REDCap is expanding to support applicable research workflows governed by 21 CFR Part 11, including the use of electronic records and electronic signatures.
Additional information about availability and implementation will be provided as the service progresses.

• CRISPI REDCap Access: This page provides secure access to the CRISPI REDCap platform for managing clinical research data and workflows. Authorized login credentials are required. [NIH Only]

NIH CHIRP: Secure AI Innovation for Research
NIH CHIRP (Chatbot for the NIH Intramural Research Program) is a secure generative artificial intelligence (AI) environment designed to help NIH researchers and staff explore and apply advanced large language model (LLM) technologies within the NIH environment.

As part of the CRISPI (Clinical Research Informatics Supporting Principal Investigators) initiatives, CHIRP represents a significant advancement in modern clinical research informatics. By providing investigators with secure, enterprise-ready AI capabilities, CRISPI helps enable responsible AI adoption, enhance research productivity, and accelerate innovation across the NIH research community.

CHIRP is available via NIH VPN access at https://chirp.od.nih.gov [NIH Only].

Overview
The Clinical Data Warehouse (CDW) is a collaborative initiative with the NIH Clinical Center (CC) and the Center for Information Technology (CIT) that enables researchers to securely explore and analyze clinical research data within a centralized environment.

The platform supports next-generation, cloud-enabled research. These data resources allow investigators to conduct retrospective analyses, develop advanced analytical workflows, and explore innovative computational approaches to biomedical research.

Through this secure research environment, investigators can access diverse clinical data while maintaining strict data governance, privacy protections, and responsible data use practices.

Research Capabilities
The CDW environment enables researchers to work with large clinical datasets while exploring advanced analytical approaches, including:

• Artificial Intelligence and Machine Learning for biomedical data analysis
• Natural Language Processing (NLP) to extract insights from clinical notes
• Large-scale retrospective data analysis
• Collaborative research across teams and institutions

By integrating multiple data types into a single platform, the CDW supports research that can lead to new clinical insights and improved understanding of complex diseases.

Overview
The Clinical Research Dashboard is an upcoming tool designed to provide a consolidated, real-time overview of clinical research protocols across the NIH Intramural Research Program (IRP). By bringing together information from multiple sources into a single platform, the dashboard streamlines access to key protocol data and reduces the need for researchers and leadership to consult multiple systems.

Overview
The Clinical AI Pilot is a high-performance computing (HPC) and artificial intelligence (AI) system designed to support advanced clinical data processing and analysis. Building on the long-standing capabilities of Biowulf, NIH’s HPC cluster established in 1999, the pilot leverages supercomputing resources to enable cutting-edge biomedical research.

Key Capabilities

Medical Imaging Analysis
The Clinical AI Pilot processes large datasets of computerized tomography (CT) and magnetic resonance imaging (MRI) brain scans of stroke patients. This includes a simulated real-time processing component, allowing researchers to model workflows as if data were arriving live, supporting rapid evaluation of AI-driven tools.

Machine Learning & AI Models
The system supports advanced machine learning applications for clinical imaging. Researchers can implement auto-segmentation algorithms, disease detection models, and image analysis pipelines to extract meaningful insights from complex imaging data.

High-Performance Computing for Scalable Research
By leveraging Biowulf’s HPC resources, the Clinical AI Pilot can handle large-scale, computationally intensive tasks, enabling experiments and analyses that would be impossible on standard computing systems.

Overview
Terra is a cloud-native platform tailored for genomics research that enables biomedical researchers to access data, run analysis tools, collaborate with research teams, and share datasets in a secure and scalable environment.

The platform provides researchers with the computational infrastructure needed to analyze large-scale genomic and biomedical data without requiring local computing resources. Through Terra, researchers can work with advanced analysis tools, manage complex datasets, and collaborate with colleagues across institutions.

Terra is part of a broader collaborative ecosystem that includes AnVIL (Analysis, Visualization, and Informatics Lab-space) and the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH). Together, these efforts support the biomedical research community by providing powerful cloud-based resources for genomic data analysis and discovery.