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Edited by
Xiuzhen Huang, Cedars-Sinai Medical Center, Los Angeles,Jason H. Moore, Cedars-Sinai Medical Center, Los Angeles,Yu Zhang, Trinity University, Texas
Pharmacogenomics is the study of genetic factors that influence drug response. Pharmacogenomics combines pharmacology and genomics to identify genetic predictors of variability in drug response that can be used to maximize drug efficacy while minimizing drug toxicity in order to tailor drug therapy for patients, thus improving patient care and reducing healthcare costs. In this chapter we review the field of pharmacogenomics in its current state and clinical practice. Recent research, methods, and resources for pharmacogenomics are reviewed in detail. We discuss the advantages and challenges in pharmacogenomic studies. We elaborate on the barriers to clinical translation of pharmacogenetic discoveries and the efforts of various institutions and consortia to mitigate these barriers. We also discuss applications and clinical translation of pharmacogenomic research moving forward, along with social, ethical, and economic issues that require attention. We conclude by previewing the use of big data, multi-omics data, advanced computing technology, and statistical methods by scientists across disciplinary boundaries along with the efforts of government organizations, clinicians, and patients that could lead to successful and clinically translatable pharmacogenomic discoveries, ushering in an era of precision medicine.
From the long path through preclinical development, entering the regulatory field of interactions for human clinical trials can sometimes feel like you are walking into the lion’s den. This chapter guides you through an understanding of how to interact and how to prepare for FDA meetings so that they are on your side rather than fighting you. The common goals of companies and the FDA are highlighted here. Specific issues with identifying the appropriate regulatory approval pathway are discussed here with cautionary case studies. Complex new technologies which combine diagnostics and drugs, or devices and software, or AI-based dynamic software are reviewed here. The best approach to the appropriate regulatory pathway will be clear after reading this chapter. Case studies are used to show successful pathways taken by cutting-edge developments, such as cell-based therapy.
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