INTRODUCTION 1. Introduction; 2. Translational Process; 3. Scientific Method; 4. Basic Research
PRE-CLINCIAL: DISCOVERY AND DEVELOPMENT 5. Overview of Preclinical Research; 6. What problem are you Solving?; 7. Types of Interventions; 8. Drug discovery; 9. Drug Testing; 10. Device Discovery and Prototyping; 11. Device Testing; 12. Diagnostic Discovery; 13. Diagnostic Testing; 14. Procedural Technique Development; 15. Behavioral Intervention; 16. Artificial Intelligence
CLINICAL: FUNDAMENTALS 17. Introduction to clinical research: What is it? Why is it needed?; 18. The question: Types of research questions and how to develop them; 19. Study population: Who and why them?; 20. Outcome measurements: What data is being collected and why?; 21. Optimizing the Question: Balancing Significance and Feasibility; 22. Statistical Efficiency in Study Design
STATISTICAL PRINCIPLES 23. Basic statistical principles; 24. Distributions; 25. Hypotheses and error types; 26. Power; 27. Regression; 28. Continuous variable analyses: t-test, Man Whitney, Wilcoxin rank; 29. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel; 30. Analysis of variance; 31. Correlation; 32. Biases; 33. Basic science statistics; 34. Sample Size; 35. Statistical Software
CLINICAL: STUDY TYPES 36. Design principles: Hierarchy of study types; 37. Case series: Design, measures, classic example; 38. Case-control study: Design, measures, classic example; 39. Cohort study: Design, measures, classic example; 40. Cross-section study: Design, measures, classic example; 41. Longitudinal Study: Design, Measures, Classic Example; 42. Meta-analysis: Design, measures, real-world examples; 43. Cost-effectiveness study: Design, measures, classic example; 44. Diagnostic test evaluation: Design, measures, classic example; 45. Reliability study: Design, measures, classic example; 46. Database studies; 47. Surveys and questionnaires: Design, measures, classic example; 48. Qualitative methods and mixed methods; 49. Visual analytics: design, measures, classic example
CLINICAL TRIALS 50. Randomized control: Design, measures, classic example; 51. Nonrandomized control: Design, measures, classic example; 52. Historical control: Design, measures, classic example; 53. Cross-over: Design, measures, classic example; 54. Factorial design: Design, measures, classic example; 55. Large, pragmatic: Design, measures, classic example; 56. Equivalence and noninferiority: Design, measures, classic example; 57. Adaptive: Design, measures, classic example; 58. Randomization: Fixed or adaptive procedures; 59. Blinding: Who and how?; 60. Multicenter considerations; 61. Phase 0 Trials: Window of Opportunity; 62. Registries; 63. Phases of Clinical Trials; 64. IDEAL Framework
CLINICAL: PREPARATION 65. Patient Perspectives; 66. Ethics and review boards; 67. Regulatory considerations for new drugs and devices; 68. Funding approaches; 69. Conflicts of Interest; 70. Subject recruitment; 71. Data management; 72. Quality control; 73. Special Populations; 74. Report Forms: Harm and Quality of Life; 75. Subject adherence; 76. Survival analysis
REGULATORY BASICS 77. FDA overview; 78. IND; 79. New drug application; 80. Devices; 81. Radiation-Emitting Electronic Products; 82. Orphan Drugs; 83. Biologics; 84. Combination Products; 85. CMC and GxP; 86. Post-Market Drug Safety Monitoring; 87. Post-Market Device Safety Monitoring
CLINICAL IMPLEMENTATION 88. Implementation Research; 89. Design and Analysis; 90. Mixed-Methods Research; 91. Guideline Development; 92. Cooperative Group Research; 93. Digital Health
PUBLIC HEALTH 94. Public Health; 95. Epidemiology; 96. Factors; 97. Good Questions; 98. Population- and Environmental-Specific Considerations; 99. Law, Policy, and Ethics; 100. Public Health Institutions and Systems; 101. DEI (Diversity, equity, inclusion)
PRACTICAL RESOURCES102. Ethics in Scientific Publishing; 103. Presenting Data; 104. Manuscript Preparation; 105. Promoting Research; 106.
