Mar 29, 2024  
Graduate Catalog 2018-2019 
    
Graduate Catalog 2018-2019 [ARCHIVED CATALOG]

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PGPM 502 Genomic Data Science and Pharmacometrics

This course covers genomic data science principles
 that include: importing, restructuring,
 sub-setting, and computational analysis of FDA
 Adverse Events Reporting System data for
 identification of genomic markers among most
 commonly reported drugs, DNA microarray data
 and/or RNA-Sequencing
datasets of patient responders and non-responders
 to pharmacotherapy. The course also introduces
 the application of predictive modeling algorithms
 to
assess and predict drug responders,
 non-responders, and patients at risk of
 adverse-drug reactions. Students will be exposed
 introduced to the Genome Analysis Toolkit for
 analyzing Germline and Somatic Mutations in the
 genome. In the second portion of the course, the
 following pharmacometric principles will be
 covered: Nonlinear-Mixed Effect Modeling (NLME)
 of blood drug concentration data,
 Physiologically-based Pharmacokinetic (PBPK)
 modeling, and Bayesian
Dosing of Therapeutic Drug Monitoring (TDM) data.
 Throughout the course, recent, relevant, and
 foundational publications will accompany lecture
 and guide discussions for clinical application in
 personalizing medicine. Data presented in this
 course will stem from published clinical studies
 and simulated data examples that include, but not
 limited to the following specialties: Oncology,
 Psychiatry, Pediatrics, Rheumatology, Surgery,
 Anesthesiology, and Family/Internal Medicine. Credit(s): 3



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