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Perspectives from NCATS Intramural Research Fellows

Fellows at every level work closely with Division of Preclinical Innovation scientists to improve the efficiency and effectiveness of the translation process and to streamline how scientific discoveries become clinical interventions.

About NCATS Intramural Research Fellows

At the Division of Preclinical Innovation (DPI), we provide an extraordinary variety of innovative, interdisciplinary training opportunities for undergraduate, graduate and postdoctoral level trainees. Training with us delivers a unique combination of translational science skills, technologies and approaches that have launched and accelerated the successful careers of a diverse group of intramural research fellows.

Meet a Fellow

Olive Jung

Olive Jung was a predoctoral fellow in DPI’s Early Translation Branch, with a focus on advancing the search for therapies targeting central nervous disorders. As an M.D./Ph.D. candidate, she worked at NCATS to develop 3-D models of the blood–brain barrier and the human lung to sharpen clinical predictability when promising drug compounds move from the laboratory into human trials. Intramural collaboration between NCATS and other NIH institutes and centers drew Olive to NCATS for her graduate research work. In this video, she explains how NCATS’ translational science training will help her bridge translational research and clinical practice later in her medical career. Learn more about the Graduate Partnerships Program

Posted November 23, 2021 (video length: 4:30)

Vukasin Jovanovic, Ph.D.

Vukasin Jovanovic, Ph.D., is a senior postdoctoral fellow in DPI’s Stem Cell Translation Laboratory, with a focus on developing human induced pluripotent stem cells (iPSC) for clinical applications. His NCATS research led to a new method that turns iPSCs faster and more efficiently into astrocytes faster and more efficiently. Astrocytes are a key brain cell type implicated in such diseases as autism, epilepsy and Alzheimer’s disease. In this video, Vukasin explains how NCATS’ translational science training, cutting-edge technology and team-based approach are advancing his career goals and accelerating his mission to find solutions for unmet medical needs. Learn more about postdoctoral training in NCATS research groups. 

Posted November 23, 2021 (video length: 4:38)

Jordan Williams

Jordan Williams was a postbaccalaureate fellow in DPI’s Drug Metabolism and Pharmacokinetics Group, with a focus on developing research models that accurately predict in vitro how drugs will interact with the human body in clinical trials. Her NCATS pharmacokinetics team focused on accurately predicting in the laboratory how oral drugs will be taken up in the intestinal system. Collaboration, collegial teamwork and the opportunity to learn a wide range of translational science skills drove Jordan to choose NCATS as the next step in her research journey. In this video, she explains how her cross-disciplinary NCATS experience will advance her career in science communications. Learn more about the Postbaccalaureate Intramural Research Training Award Program

Posted November 23, 2021 (video length: 4:58)

Stories From NCATS Fellows

Profiles of Translational Science Interagency Fellows

Fellows in the Translational Science Interagency Fellowship program are matched with an NCATS–U.S. Food and Drug Administration (FDA) mentor pair to work on a specific project. Read about the fellows and their research:

  • Elia Lopez, Ph.D., Translational Research in Developing Predictive Toxicology for Antisense Oligonucleotides 
  • Xinh-Xinh Nguyen, Ph.D., A Microphysiological Skin Model of Atopic Dermatitis for Screening Immunomodulatory Mesenchymal Stromal Cell Therapies 
  • Keyla Tumas, Ph.D., Repurposing for Neglected Infectious Diseases: Project Lifecycle From Bench to Translational to Regulatory Science
  • Kristin A. Altwegg, Ph.D., The Bioassay as a Predictive Model of Drug Efficacy in Repurposing Drug Screen for Oncology Indications 
  • Tsung-Jen Liao, Ph.D., Incorporating in Vitro and in Silico Data to Improve Drug-Induced Liver Injury Predictive Models for Supporting FDA Review Process

Last updated on April 22, 2024