Course subject: Pharmacy (PHARM)

This course provides an introduction to basic principles in medical chemistry such as physiochemical properties, drug design and pharmacological actions. A brief overview of the theory and application of computer aided drug design principles will provide a basic understanding of the "in silico" drug design concepts. The student will develop an understanding toward the concepts of peptide/petidomimetic design as therapeutic agents. A series of case studies on clinical drugs will be presented with major emphasis on their design, synthesis, reaction mechanisms and structure-activity relationship studies. A section of the course will address the pathophysiology and pharmacology of diseases affecting the central nervous system. In addition, learning activities and assignments include a term paper submission and in class presentation of current topics in medicinal chemistry.

Surface active compounds, more commonly known as surfactants are found in nearly every aspect of day to day life, including motor oils, pharmaceuticals, cosmetics, detergents, and paints and inks to name a few. This course will introduce the student to the structures of classical and emerging classes of surfactants and their fundamental properties that make these systems so useful. The self-assembly of these compounds into micelles will be discussed in detail using both thermodynamic and kinetic modules and modern methods of characterizing these systems will be examined. The application of surfactants in a variety of industries will be introduced. The capstone activity of this course will entail a critical analysis of a relevant recent journal article, and presentation to the class.

This course provides an introduction to modern spectroscopic methods with emphasis on pharmaceutical analysis. First few lectures will cover the theory and application of UV-Vis and IR spectroscopy. A review of NMR spectroscopy will focus on commonly used techniques such as 1H NMR and 13C NMR and their application. The student will get a practical experience in spectroscopic methods for structural elucidation by using UVS-VIS, IR and NMR spectrometers. In addition, a section will address the theory and application of mass spectrometry. Examples of drug molecules/pharmaceuticals and their spectroscopic characteristics will be discussed. In addition, learning activities and assignments include problem sets and structural elucidation of an unknown organic molecule.

This course provides statistical hands-on knowledge for the implementation of nonlinear mixed effects (NLME) models in the analysis of population pharmacokinetic data. In order to provide a foundation for NLME, the content builds from simple to multiple linear regression models and to linear mixed effects models. Exploratory and descriptive analyses as well as model implementation will be taught in R and Phoenix.

This course will discuss specialized topics that are of mutual interest to the research of faculty members and graduate students in the field of Pharmacy Practice. Topics could include, for example, pharmacy education; rural pharmacy practice; geriatrics and aging; pharmacoepidemiology; the role of technology in primary care; chronic disease management; expanded scope of practice; collaborative practice in different settings; health services design and care delivery; among others. This course may be presented in any of the following formats, reading based, lecture based, project based, or online learning.

This course will provide students with an overview of the rationale and stages involved in the conduct of a formal systematic review and meta-analysis of a well-defined clinical/health research question. The overarching aim is to provide students with the tools to critically appraise and conduct a systematic review and meta-analysis. Students will largely work in pairs to progress through each step involved (with feedback from instructors at each stage) and to produce a final systematic review and meta-analysis to be presented/submitted at the end of the course. Course Objectives: 1. To demonstrate an understanding of the rationale underlying a systematic review and meta-analysis and relevance to clinical care and health policy; 2. To critically appraise a systematic review; 3. To develop a focused research question amenable to a systematic review; 4. To develop and implement a comprehensive and systematic literature search strategy; 5. To determine and apply procedures for including/excluding potential studies for a systematic review and meta-analysis; 6. To develop and implement a data abstraction process and study database; 7. To demonstrate an understanding of the fundamental statistical/biostatistical issues relevant to the conduct of a formal systematic review and meta-analysis. 8. To perform statistical analyses for a systematic review and meta-analysis and complete/present a final report demonstrating all stages involved. Students will need to meet with Course Coordinators and provide of appropriate previous experience with linear and/or logistic regression techniques.

This course prepares PhD in Pharmacy students to present their research objectives and proposal methods in written and oral form suitable to a PhD program and involves the preparation of a written research proposal and oral defence of the proposal. The written and oral proposal will be considered by an examination committee that normally includes the student's Thesis Advisory Committee plus an independent Chair. This course is only available for the first Thesis Proposal taken within the Pharmacy Program.

The formulation of chemicals into products for specific purposes dates back to the stone age. Formulated products are now part of everyday life and include pharmaceuticals, cosmetics, personal care products, detergents, agricultural products, etc. This course will examine the chemical formulation of various consumer products with an emphasis on pharmaceutical formulations; major components used in formulations, surface chemistry, and molecular interactions will be discussed. Analytical methods for testing formulations, raw materials, and environmental and sustainability considerations will also be discussed.

This course provides an opportunity for students to design experiments and carry out independent research projects in the area of neurodegenerative disorders. Student projects are aimed to study the pathophysiology of Alzheimer¿s disease and related neurodegenerative disorders by various techniques such as designing novel small molecules and peptides by computational chemistry. Furthermore, the interactions between small molecules/peptides with misfolded proteins/peptides will be evaluated by biochemical and biophysical techniques with emphasis on fluorescence spectroscopy and ligand-protein kinetic studies. Microscopy techniques including transmission electron microscopy (TEM) analysis will be studied. Students will be trained in using the computational chemistry software Discovery Studio Structure-Based-Design. Individual student projects may include compound characterization by nuclear magnetic resonance spectroscopy (NMR), high performance-liquid chromatography (HPLC) and liquid chromatography mass spectrometry (LC-MS) techniques. Students are expected to spend between 10-11 weeks in the research lab working on their assigned projects. Course re-requisite include completion and proof of safety training including WHMIS, workplace violence training and safety orientation.

Students will build on the foundational knowledge and skills developed in PHARM 651 Advanced Principles of Medication Management 1.

Students will identify and critique papers from the primary drug literature. Skills related to critical appraisal and evidence-based practice will be developed. Students will have the opportunity to develop communications skills related to presenting scientific literature.

This course is designed to teach students the fundamentals of planning, conducting, and communicating the analysis of quantitative data within the context of applied health research. Students will learn quantitative data analysis through hands-on experience using different sources of data (e.g., clinical trial, cross-sectional survey, prospective cohort, etc.). Topics will include descriptive statistics, t-Test, ANOVA, linear regression, logistic regression, poisson regression, and proportional hazards regression. Several techniques to adjust for confounding will be covered. Students will learn to apply their analytic skills using SAS.