PRE-CLINCIAL: DISCOVERY & DEVELOPMENT<br>1. Defining the problem to solve<br>2. Types of problems<br>3. Drug discovery<br>4. Device discovery<br>5. Device classification<br>6. Other product types<br>7. Drug safety <br>8. Device prototyping <br>9. Device testing<br><br>CLINICAL: FUNDAMENTALS<br>10. Introduction to clinical research: What is it? Why is it needed?<br>11. The question: Types of research questions and how to develop them<br>12. Study population: Who and why them?<br>13. Outcome measurements: What data is being collected and why?<br><br>STATISTICAL PRINCIPLES<br>14. Presenting data<br>15. Common issues in analysis<br>16. Basic statistical principles<br>17. Distributions<br>18. Hypotheses and error types<br>19. Power<br>20. Regression<br>21. Continuous variable analyses: t-test, Man Whitney, Wilcoxin rank<br>22. Categorical variable analyses: Chi-square, fisher exact, Mantel hanzel<br>23. Analysis of variance<br>24. Correlation<br>25. Biases<br>26. Basic science statistics<br>27. Sample forms and templates<br><br>CLINICAL: STUDY TYPES<br>28. Design principles: Hierarchy of study types<br>29. Case series: Design, measures, classic example<br>30. Case-control study: Design, measures, classic example<br>31. Cohort study: Design, measures, classic example<br>32. Cross-section study: Design, measures, classic example<br>33. Clinical trials: Design, measures, classic example<br>34. Meta-analysis: Design, measures, classic example<br>35. Cost-effectiveness study: Design, measures, classic example<br>36. Diagnostic test evaluation: Design, measures, classic example <br>37. Reliability study: Design, measures, classic example<br>38. Database studies: Design, measures, classic example<br>39. Surveys and questionnaires: Design, measures, classic example<br>40. Qualitative methods and mixed methods<br><br>CLINICAL TRIALS<br>41. Randomized control: Design, measures, classic example<br>42. Nonrandomized control: Design, measures, classic example<br>43. Historical control: Design, measures, classic example<br>44. Cross-over: Design, measures, classic example<br>45. Withdrawal studies: Design, measures, classic example<br>46. Factorial design: Design, measures, classic example<br>47. Group allocation: Design, measures, classic example<br>48. Hybrid design: Design, measures, classic example<br>49. Large, pragmatic: Design, measures, classic example<br>50. Equivalence and noninferiority: Design, measures, classic example<br>51. Adaptive: Design, measures, classic example<br>52. Randomization: Fixed or adaptive procedures<br>53. Blinding: Who and how?<br>54. Multicenter considerations<br>55. IDEAL Framework<br><br>CLINICAL: PREPARATION<br>56. Optimizing the question: Balancing significance and feasibility<br>57. Meaningful outcome measurements<br>58. Sample size<br>59. Budgeting<br>60. Ethics and review boards<br>61. Regulatory considerations for new drugs and devices<br>62. Funding approaches<br>63. Subject recruitment<br>64. Data management<br>65. Quality control<br>66. Report forms: Harm and Quality of Life<br>67. Subject adherence<br>68. Survival analysis<br>69. Monitoring committee in clinical trials<br><br>REGULATORY<br>70. FDA overview<br>71. New drug application<br>72. Device pathways<br>73. Non-US regulatory<br>74. Post-Market Drug Safety Monitoring<br>75. Post-Market Device Safety Monitoring