- A National IPS Cell Network with Deep Phenotyping for Translational Research
- Disseminating Curative Biological Therapies for Rare Pediatric Diseases
- Early Check: A Collaborative Innovation to Facilitate Pre-Symptomatic Clinical Trials in Newborns
- Leveraging Existing Registry Resources to Facilitate Clinical Trials
- Improving Patient-Reported Outcome Data for Research Through Seamless Integration of the PROMIS Toolkit into EHR Workflows
- Strengthening Translational Research in Diverse Enrollment (STRIDE)
- Transformative Computational Infrastructures for Cell-Based Biomarker Diagnostics
A National IPS Cell Network with Deep Phenotyping for Translational Research
Boston University Medical Campus
Principal Investigators: Nelson Kotton, M.D., Andrew A. Wilson, M.D., Chad Cowan, Ph.D., Yoav Gilad, Ph.D., and Edward E. Morrisey, Ph.D.
Grant Number: 1-U01TR001810-01
Collaborating Institutions: Harvard Medical School, University of Chicago, University of Pennsylvania
The discovery of inducible pluripotent stem cells (iPSCs) provides an unprecedented opportunity for any scientist to derive an inexhaustible supply of patient-derived primary cells. These cells containing each patient's own genetic background can now be applied for in vitro human disease modeling, drug screening of personalized therapeutics and the development of future regenerative cell-based therapies. This proposal creates a CTSA Program iPSC Network led by teams who have championed an `Open Source Biology' approach, freely sharing iPSC lines and their reprogramming reagents with more than 500 labs to date across the globe. Its goals are to make patient-derived iPSCs together with the tools and expertise for their genetic manipulation available to the greater research community on a large scale to realize their promise for extending understanding of disease and developing potential therapies.
Learn more about this project in the NIH RePORTER.
Disseminating Curative Biological Therapies for Rare Pediatric Diseases
Boston Children’s Hospital (Harvard University)
Principal Investigators: David A. Williams, M.D., Donald B. Kohn, M.D. and Lilith Reeves, M.S.
Grant Number: 1-U01TR001814-01
Collaborating Institutions: University of California, Los Angeles, University of Cincinnati
This project will develop a network of pediatric centers with unique expertise and experience in translation of gene therapies. The overall goal is to support investigators across CTSA Program institutions to more rapidly translate complex gene therapies to early phase investigator-initiated pediatric clinical trials. The Disseminating Curative Biological Therapies for Rare Pediatric Diseases Collaborative Consortium will offer key services and expert advice in order to enhance enrollment on gene therapy clinical trials nationally.
Learn more about this project in the NIH RePORTER.
Early Check: A Collaborative Innovation to Facilitate Pre-Symptomatic Clinical Trials in Newborns
Duke University
Principal Investigators: Alex Randall Kemper, M.D., Donald B. Bailey, Ph.D., Cynthia Powell, M.D., M.S. and Nancy M.P. King, J.D.
Grant Number: 1-U01TR001792-01
Collaboration Institutions: Duke University, Wake Forest University Health Sciences
Health problems included in state newborn screening programs must have strong evidence of benefit before they are included in screening. But for many rare disorders, evidence of benefit is difficult to gather, especially if the treatment must be provided before symptoms appear. This project will establish a voluntary newborn screening research program to study the benefits of screening for rare disorders so that policy makers will have the evidence they need to make good decisions about newborn screening policy.
Learn more about this project in the NIH RePORTER.
Leveraging Existing Registry Resources to Facilitate Clinical Trials
Duke University
Principal Investigators: Jennifer S. Li, M.D., Jeffrey P. Jacobs, M.D. and H. Scott Baldwin, M.D.
Grant Number: 1-U01TR001803-01
Collaborating Institutions: Johns Hopkins University, Vanderbilt University Medical Center
Clinical trials are resource-intensive and costly. Consequently many patient populations remain understudied with limited evidence to guide clinical practice. One mechanism to improve the evidence base is to leverage existing registry resources to conduct simple, efficient and low cost trials. This proposal will demonstrate the benefits of the “trial within a registry” approach in a vulnerable and understudied patient population, neonates undergoing heart surgery with cardiopulmonary bypass. Doing so, the infrastructure for a national registry-based trials network in children undergoing heart surgery, and concomitantly develop a model for efficient and cost-effective trials in other understudied diseases and conditions will be established.
Learn more about this project in the NIH RePORTER.
Improving Patient-Reported Outcome Data for Research Through Seamless Integration of the PROMIS Toolkit into EHR Workflows
Northwestern University
Principal Investigator: Justin B. Starren, M.D., Ph.D.
Grant Number: 1-U01TR001806-01
Collaborating Institutions: Harvard Medical School, University of Alabama at Birmingham, University of Chicago, University of Florida, University of Kentucky, University of Illinois at Chicago, University of Southern California, University of Utah
Patient-reported outcomes (PROs) reflect the experience of health and healthcare as reported directly by the patient. There is increasing evidence that capturing PROs will be an essential component of quality measurement, quality improvement and patient engagement in care and research. The Patient-Reported Outcomes Measurement Information System (PROMIS) toolset is a PRO survey system that utilizes computer adaptive testing to provide precise measurements with a minimum number of questions, often shortening conventional PRO surveys by 10-fold or more. The goal of this project is to develop and evaluate a suite of software tools that will allow all CTSA Program sites to integrate PROMIS tools directly into their electronic health records.
Learn more about this project in the NIH RePORTER.
Strengthening Translational Research in Diverse Enrollment (STRIDE)
University of Massachusetts Medical School, Worcester
Principal Investigators: Stephenie Lemon, Ph.D., Jeroan J. Allison, M.D., M.P.H., Kenneth S. Saag, M.D., M.Sc. and Paul Harris, Ph.D.
Grant Number: 1-U01TR001812-01
Collaborating Institutions: University of Alabama at Birmingham, Vanderbilt University Medical Center
The goal of STRIDE (Strengthening Translational Research in Diverse Enrollment) is to develop, test, and disseminate an integrated multi-level, culturally sensitive intervention to engage African Americans and Latinos in translational research. African Americans and Latinos are not adequately represented in translational research, particularly given the widespread health disparities experienced by these groups. This study aims to develop, test and make widely available a multi-level intervention that is culturally and literacy appropriate to address this critical issue.
Learn more about this project in the NIH RePORTER.
Transformative Computational Infrastructures for Cell-Based Biomarker Diagnostics
J. Craig Venter Institute, Inc. (University of California, San Diego)
Principal Investigators: Richard H. Scheuermann, Ph.D., and Yu “Max” Qian, Ph.D.
Grant Number: 1-U01TR001801-01
Collaborating Institutions: Stanford University, University of California-Irvine
Flow cytometry analysis is widely used for single cell phenotyping in the translational research lab to explore the mechanisms of normal and abnormal biological processes and in the clinical diagnostic lab for the identification and classification of blood-borne malignancies. However, the current practice for cytometry data analysis using “manual gating” based on two-dimensional data plots is subjective, labor-intensive and unreliable, especially when using more complex high content staining panels. The goal of this project is to develop, validate and disseminate a user-friendly computational infrastructure for cytometry data analysis for both diagnostic and discovery applications that could help overcome the current limitations of manual analysis and provide for more efficient, objective, accurate and reproducible analysis of cytometry data.