Translational Pulmonology

by Davis A. Hartnett (Editor), Jeffrey A. Bakal (Editor), Adam E.M. Eltorai (Editor), Larisa G. Tereshchenko (Editor)

Overview

Translational research is essential to the advancement of medicine. Translational Pulmonology is an instructional guide to translational medical research serves as a practical, step-by-step roadmap for taking a biomedical device, potential therapeutic agent, or research question from idea through demonstrated clinical benefit. Fundamentally, the volume aims to help bridge the gap between current research and practice. Written by a team of expert medical, biomedical engineering, and clinical research experts in pulmonary diseases, this volume provides a clear process for understanding, designing, executing, and analyzing clinical and translational research within the field.

Product Details

ISBN-13:	9780323903912
Publisher:	Elsevier Science
Publication date:	06/12/2025
Series:	Handbook for Designing and Conducting Clinical and Translational Research
Pages:	610
Product dimensions:	8.50(w) x 10.88(h) x (d)

About the Author

Davis Hartnett, MD completed his medical degree at the Warren Alpert Medical School of Brown University and is a resident physician at Brigham and Women’s Hospital in Boston, Massachusetts in the Department of Internal Medicine. He has contributed to over 40 peer reviewed publications and over 30 academic presentations on research topics including medicolegal outcomes, healthcare access disparities, and translational medicine.

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.

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.

Larisa Tereshchenko is an Associate Professor of Medicine at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University and an Adjunct Associate Professor of Electrical Engineering and Computer Science at the Cleveland State University. She has a broad background in clinical investigation, cardiology, cardiac electrophysiology and electrocardiology, biomedical engineering, biophysics, randomized controlled trials, epidemiology, biostatistics, bioinformatics, and genomics. Over the past two decades, she has led clinical studies, including randomized controlled trials, cohort, and case-control studies, and has expertise in multicenter and multidisciplinary research leadership, the building of collaborative groups, and multicohort epidemiological studies. She is an author of more than 160 original peer-reviewed manuscripts, chapters, and reviews.

Table of Contents

Introduction
1. Introduction
2. Translational process
3. Scientific Method

Pre-Clinical
4. Overview of Preclinical Research
5. What Problem are You Solving?
6. Types of Interventions
7. Drug Discovery
8. Drug Testing
9. Device Discovery and Prototyping
10. Device Testing
11. Diagnostic Discovery
12. Other Product Types
13. Procedural Technique Development
14. Behavioral Intervention
15. Artificial Intelligence

Clinical: Fundamentals
16. Introduction to Clinical Research: What is it? Why is it Needed?
17. The Question: Types of Research Questions and how to Development 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 Feasibility

Statistical Principles
21. Common Issues in Analysis
22. Basic Statistical Principles
23. Hypotheses and Error Types
24. Power
25. Regression
26. Continuous Variable Analyses
27. Categorical Variable Analyses: Chi-square, Fisher Exact, Mantel Hanzel
28. Correlation
29. Biases
30. Basic Science Statistics
31. Sample Size
32. Statistical Software

Clinical: Study Types
33. Design Principles: Hierarchy of Study Types
34. Case Series: Design, Measures, Classic Example
35. Case-Control Study: Design, Measures, Classic Example
36. Cohort Study: Design, Measures, Classic Example
37. Cross-section Study: Design, Measures, Classic Example
38. Longitudinal Study: Design Measures, Classic Example
39. Meta-analysis: Design, Measures, Classic Example
40. Cost-effectiveness Study: Design, Measures, Classic Example
41. Diagnostic Test Evaluation: Design, Measures, Classic Example
42. Reliability Study: Design, Measures, Classic Example
43. Database Studies: Design, Measures, Classic Example
44. Surveys and Questionnaires: Design, Measures, Classic Example
45. Qualitative Methods and Mixed Methods

Clinical Trials
46. Randomized Control: Design, Measures, Classic Example
47. Historical Control: Design, Measures, Classic Example
48. Cross-Over: Design, Measures, Classic Example
49. Withdrawal Studies: Design, Measures, Classic Example
50. Factorial Design: Design, Measures, Classic Example
51. Group Allocation: Design, Measures, Classic Example
52. Hybrid Design: Design, Measures, Classic Example
53. Large, Pragmatic: Design, Measures, Classic Example
54. Equivalence and Noninferiority: Design, Measures, Classic Example
55. Adaptive: Design, Measures, Classic Example
56. Phase 0 Trials: Window of Opportunity
57. Registries
58. Phases of Clinical Trials
59. IDEAL Framework

Clinical: Preparation
60. Patient Perspectives
61. Budgeting
62. Ethics and Review Boards
63. Regulatory Considerations for New Drugs and Devices
64. Funding Approaches
65. Conflicts of Interest
66. Subject Recruitment
67. Data Management
68. Special Populations
69. Subject Adherence
70. Survival Analysis
71. Monitoring Committee in Clinical Trials

Regulatory Basics
72. FDA Overview
73. IND
74. New Drug Application
75. Devices
76. Orphan Drugs
77. Biologics
78. Combination Products
79. Foods
80. Cosmetics
81. CMC and GxP
82. Non-US Regulatory
83. Post-Market Drug Safety Monitoring
84. Post-Market Device Safety Monitoring

Clinical Implementation
85. Implementation Research
86. Design and Analysis
87. Mixed-methods Research
88. Population- and Setting-specific Implementation
89. Guideline Development

Public Health
90. Public Health
91. Epidemiology
92. Factors
93. Good Questions
94. Population- and Environmental-specific Considerations
95. Law, Policy, and Ethics
96. Healthcare Institutions and Systems
97. Public Health Institutions and Systems

Practical Resources
98. Presenting Data
99. Manuscript Preparation
100. Quality Improvement
101. Team Science and Building a Team
102. Patent Basics
103. Venture Pathways
104. SBIR/STTR
105. Sample Forms and Templates

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From the Publisher

How-to-guide for designing and conducting translational medicine research in pulmonary