Translational Research, MSTR

The Master of Science in Translational Research (MSTR) provides students with in-depth instruction in the fundamental skills, methodology and principles necessary to become a well-trained translational investigator. The program is designed to meet this objective through the provision of didactic course work, a formal mentorship program, laboratory training, a professional development core, and specific ongoing guidance with hands-on exposure to protocol and grant development. The MSTR is housed within the Institute for Translational Medicine and Therapeutics (ITMAT) which supports research at the interface of basic and clinical research focusing on developing new and safer therapeutics.

The MSTR is designed to facilitate training and research particularly from proof of concept in cellular and animal model systems across the translational divide to proof of concept and dose selection in humans. Student projects and career goals align across this continuum. Students enroll in a core set of courses and also choose elective coursework to focus in on specific areas of translational science.

Curriculum

Students must complete 12 course units and achieve a B- or higher in each course for the degree.

Competencies
Complete the mininimum CU from each of the following pillars:
Research Methods3
Proposal Development and Study Design
Master of Science in Translational Research LAB
Analytical Skills2
Introduction to Biostatistics
Disease Measurement
Responsible Conduct of Research1
Scientific & Ethical Conduct
Scientific Writing1
Data Manuscript Writing
Grantsmanship for Career Development Awards
Writing an NIH Grant
Thesis2
Thesis I
Thesis II
Electives3
Select 3 CU guided by research area of interest.
Total Course Units12

Discovery 

Electives
Discovery-based elective2
Immunology for CAMB
Vaccines and Immune Therapeutics
Introduction to Bioinformatics
Genomics
Pharmacogenetics
DIYtranscriptomics
Data Science for Biomedical Informatics

Bioinformatics/Biomedical Informatics

Supplemental Core
MTR 5350Introduction to Bioinformatics1
or BMIN 5030 Data Science for Biomedical Informatics
Electives
Students choose 2 CU of electives.2
Database and Data Integration in Biomedical Research
Advanced Methods and Health Applications in Machine Learning
Human Factors
Natural Language Processing for Health
Biomedical Informatics Methods for Learning Health Systems
Statistics for Genomics and Biomedical Informatics
Modern Data Mining
Methods for Statistical Genetics and Genomics in Complex Human Disease

Entrepreneurial Science

Electives
Entrepreneurial Science-based elective3

 Translational Therapeutics and Regulatory Science

Electives
Translational Therapeutics-based elective2
Introduction to Drug Development
Fundamentals of FDA Regulation
Clinical Trials
Clinical Trial Management
Cell and Gene Therapy
Manufacturing Novel Therapies & Imaging Agents
New Trends in Medicine and Vaccine Discovery
Applied Regulatory Processes of Vaccines and Biologics

The degree and major requirements displayed are intended as a guide for students entering in the Fall of 2026 and later. Students should consult with their academic program regarding final certifications and requirements for graduation.