# Clinical Trans Valid: The Center for Advancing Point of Care Technologies in Heart, Lung, Blood and Sleep Diseases

> **NIH NIH U54** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2021 · $172,584

## Abstract

PROJECT SUMMARY/ABSTRACT – CLINICAL TRANSLATION AND VALIDATION CORE 
American healthcare is rapidly evolving to a state where efficiency and quality in health care are 
co-dominant drivers. Point-of-care technologies (POCT) are an important tool for providers and 
patients to receive immediate feedback on critical health issues. In acute care settings, caregivers 
need real-time POCT to guide treatment in rapidly changing circumstances; and in the outpatient 
setting providers are seeking ways to engage patients with preventative measures and implement 
precision medicine. The goal of CAPCaT is to develop and optimize novel POCT to improve the 
diagnosis and management of heart, lung, blood and sleep (HLBS) diseases. The Clinical 
Translation and Validation (CTV) core will be responsible for validating the prototypes and 
establishing the feasibility of adoption of these devices in settings appropriate to the specific 
technology being tested. Therefore, we will maintain a broad array of services necessary to 
facilitate clinical research, and support the specific needs of individual projects.

## Key facts

- **NIH application ID:** 10222764
- **Project number:** 5U54HL143541-04
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** David D. McManus
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $172,584
- **Award type:** 5
- **Project period:** 2018-08-22 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10222764

## Citation

> US National Institutes of Health, RePORTER application 10222764, Clinical Trans Valid: The Center for Advancing Point of Care Technologies in Heart, Lung, Blood and Sleep Diseases (5U54HL143541-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10222764. Licensed CC0.

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