Translational Cardiology

Dr Jeff Bakal PhD, P.Stat. is the Program Director for Provincial Research Data Services at Alberta Health Services which operates the Alberta Strategy for Patient Oriented Research (SPOR) data platform and Health Service Statistical & Analytics Methods teams. He has over 10 years of experience working with Health Services data and Randomized Clinical Trials. He completed his PhD jointly with the Department of Mathematics and Statistics and the School of Physical Health and Education at Queen's University. He has worked on the methodology and analysis of several international studies in business strategy, ophthalmology, cardiology, geriatric medicine and the analysis of kinematic data resulting in several peer reviewed articles and conference presentations. His current interests are in developing statistical methodology for time-to-event data and the development of classification tools to assist in patient decision making processes. C. Michael Gibson, M.S., M.D. is an interventional cardiologist, cardiovascular researcher and educator who pioneered our understanding of the "open artery hypothesis" as well our understanding of the importance of restoring flow downstream in the capillary bed in the "open microvasculature hypothesis" in heart attack. Gibson has been a leading investigator in trials of thrombolytic agents, glycoprotein 2b3a inhibitor agents, thienopyridines, factor Xa inhibitors, lipid lowering agents and new devices. Gibson was named one of the world's most widely published and cited scientists of past decade in 2014 by Thomson Reuters.For years, Gibson has been chosen as one of Boston's Top Doctors & U.S. News & World Report also lists Gibson as one of America's top doctors. He has held numerous leadership positions in medicine including positions as a Coronary Care Unit Director, a Cardiac Catheterization Laboratory Director, a Chief of Cardiology and as a Vice Chairman of Medicine.Dr Adam E. M. Eltorai, MD, PhD completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University. His work has spanned the translational spectrum with a focus on medical technology innovation and development. Dr. Eltorai has published numerous articles and books.

• Section 1. INTRODUCTION1. Introduction; 2. Translational Process; 3. Scientific Method; 4. Basic ResearchSection 2: PRE-CLINCIAL: DISCOVERY & DEVELOPMENT5. Overview of Preclinical Research; 6. What problem are you Solving?; 7. Types of Structural Interventions; 8. Drug discovery; 9. Drug Testing; 10. Device Testing; 11. Diagnostic Discovery; 12. Diagnostic Testing; 13. Other product types; 14. Procedural Technique Development; 15. Behavioral InterventionSection 3: CLINICAL: FUNDAMENTALS16. Introduction to clinical research: What is it? Why is it needed?; 17. The question: Types of research questions and how to develop them; 18. Study population: Who and why them?; 19. Outcome measurements: What data is being collected and why?; 20. Optimizing the Question: Balancing Significance and FeasibilitySection 4: STATISTICAL PRINCIPLES21. Common issues in analysis; 22. Basic statistical principles; 23. Distributions; 24. Hypotheses and error types; 25. Power; 26. Regression; 27. Continuous Variable Analyses: Student's t-test, Mann-Whitney U Test, Wilcoxon Signed-Rank Test; 28. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel; 29. Analysis of variance; 30. Correlation; 31. Biases; 32. Basic science statistics; 33. Sample Size; 34. Statistical SoftwareSection 5: CLINICAL: STUDY TYPES35. Design principles: Hierarchy of study types; 36. Case series: Design, measures, classic example; 37. Case-control study: Design, measures, classic example; 38. Cohort study: Design, measures, classic example; 39. Cross-section study: Design, measures, classic example; 40. Longitudinal Study: Design, Measures, Classic Example; 41. Meta-analysis: Design, measures, classic example; 42. Cost-effectiveness study: Design, measures, classic example; 43. Diagnostic test evaluation: Design, measures, classic example; 44. Reliability study: Design, measures, classic example; 45. Database studies: Design, measures, classic example; 46. Surveys and questionnaires: Design, measures, classic example; 47. Qualitative methods and mixed methodsSection 6: CLINICAL TRIALS48. Randomized control: Design, measures, classic example; 49. Nonrandomized control: Design, measures, classic example; 50. Historical control: Design, measures, classic example; 51. Cross-over: Design, measures, classic example; 52. Withdrawal studies: Design, measures, classic example; 53. Factorial design: Design, measures, classic example; 54. Group allocation: Design, measures, classic example; 55. Hybrid design: Design, measures, classic example; 56. Large, pragmatic: Design, measures, classic example; 57. Equivalence and noninferiority: Design, measures, classic example; 58. Adaptive: Design, measures, classic example; 59. Blinding: Who and how?; 60. Phases of Clinical Trials; 61. IDEAL FrameworkSection 7: CLINICAL: PREPARATION62. Patient Perspectives; 63. Budgeting; 64. Ethics and review boards; 65. Regulatory considerations for new drugs and devices; 66. Funding approaches; 67. Conflicts of Interest; 68. Subject recruitment; 69. Data management; 70. Quality control; 71. Research in Acute Settings; 72. Special Populations; 73. Report forms: Harm and Quality of Life; 74. Subject adherence; 75. Survival analysis; 76. Monitoring committee in clinical trialsSection 8: REGULATORY BASICS77. FDA overview; 78. IND/New Drug Application; 79. Radiation-Emitting Electronic Products; 80. Orphan Drugs; 81. Combination Products; 82. CMC and GxP; 83. Non-US Regulatory; 84. Post-Market Drug Safety Monitoring; 85. Post-Market Device Safety MonitoringSection 9: CLINICAL IMPLEMENTATION86. Implementation Research; 87. Design and Analysis; 88. Mixed-Methods Research; 89. Population- and Setting-Specific Implementation; 90. Guideline DevelopmentSection 10: PUBLIC HEALTH91. Public Health; 92. Epidemiology; 93. Factors; 94. Good Questions; 95. Population- and Environmental-Specific Considerations; 96. Law, Policy, and Ethics; 97. Healthcare Institutions and Systems; 98. Public Health Institutions and SystemsSection 11: PRACTICAL RESOURCES99. Presenting Data; 100. Manuscript Preparation; 101. Promoting Research; 102. Quality Improvement; 103. Team Science and Building a Team; 104. Patent Basics; 105. SBIR/STTR