Translational Medicine in CNS Drug Development, Volume 29, is the first book of its kind to offer a comprehensive overview of the latest developments in translational medicine and biomarker techniques. With extensive coverage on all aspects of biomarkers and personalized medicine, and numerous chapters devoted to the best strategies for developing drugs that target specific disorders, this book presents an essential reference for researchers in neuroscience and pharmacology who need the most up-to-date techniques for the successful development of drugs to treat central nervous system disorders.
Despite increases in the number of individuals suffering from CNS-related disorders, the development and approval of drugs for their treatment have been hampered by inefficiencies in advancing compounds from preclinical discovery to the clinic. However, in the past decades, game-changing strides have been made in our understanding of the pathophysiology of CNS disorders and the relationship of drug exposure in plasma and CNS to pharmacodynamic measures in both animals and humans.
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1. Translating animal models of obesity and diabetes to the clinic 2. Biomarker-guided drug development for better defined early patient studies and clinical trial efficiency 3. Modeling and simulation in the translational pharmacology of cns drugs 4. Functional measurements of central nervous system drug effects in early human drug development 5. Experimental medicine approaches in cns drug development 6. New approaches in translational medicine for phase i clinical trials of cns drugs 7. Translational approaches for antidepressant drug development 8. Biomarker opportunities to enrich clinical trial populations for drug development in schizophrenia and depression 9. Applications of neuroimaging biomarkers in cns drug development 10. Pet occupancy and competition in translational medicine and cns drug development 11. Stable isotope labeling kinetics in cns translational medicine: introduction to silk technology 12. Applications of neurophysiological biomarkers in cns drug development: focus on psychoses 13. Heart rate variability as a translational biomarker for emotional and cognitive deficits 14. Drug discovery in psychiatry: time for human genome-guided solutions 15. Use of cognition to guide decisions about the safety and efficacy of drugs in early-phase clinical trials 16. Digital biomarkers in clinical drug development 17. Lessons learned from public private partnerships and consortia: the adni paradigm 18. Regulatory perspectives on the use of biomarkers and personalized medicine in cns drug development: the fda viewpoint 19. Regulatory considerations for the use of biomarkers and personalized medicine in cns drug development: a european perspective 20. Regulatory science objectives and biomarker qualification through public-private partnerships are critical to delivering innovative treatments for cns diseases 21. The assessment of cognition in translational medicine: a contrast between the approaches used in alzheimer's disease and major depressive disorder 22. Translational medicine strategies in drug development for neurodevelopmental disorders 23. Translational medicine strategies in drug development for mood disorders 24. Translational medicine strategies in alzheimer's disease drug development 25. Experimental medicine models in generalized anxiety disorder and social anxiety disorder 26. Translational medicine strategies in ptsd drug development 27. Unmet medical needs in the treatment of depression and the clinical development of a differentiated antidepressant: a translational line of evidence 28. Translating neurobiology into practice in tobacco, alcohol, drug, and behavioral addictions 29. Translational medicine strategies for drug development for impulsive aggression 30. Hypothesizing major depression as a subset of reward deficiency syndrome (rds) linked to polymorphic reward genes: considerations for translational medicine approaches for future drug development 31. Traveling through the storm: leveraging virtual patient monitoring and artificial intelligence to observe, predict, and affect patient behavior in cns drug development