Genomic Biomarkers For Pharmaceutical Development

Genomic Biomarkers for Pharmaceutical Development: Advancing Personalized Health Care provides an in-depth review of the state of translational science across all stages of pharmaceutical development with a special focus on personalized health care. This book provides a complete picture of biomarker development and validation in a pharmaceutical setting while addressing the inherent challenges of targeting the appropriate indications, biomarker robustness, regulatory hurdles, commercialization and much more. It features case studies devoted to the applications of pharmacogenomics, toxicogenomics, and other genetic technologies as they support drug discovery and development. With chapters written by international authorities in industry and academia, this work is a truly unique presentation of the thoughts and approaches that lead to the development of personalized medicine. Intended for all those involved in clinical translational research, this book is the ideal resource for scientists searching for the applications, strategies and successful approaches of translational science in pharmaceutical development. Provides case studies in applications of pharmacodynamic and predictive markers in drug development in oncology, autoimmunity, respiratory diseases and infectious diseases Shows how to identify potential new therapeutic targets in different diseases and provides examples of potential new disease indications for life cycle management of drugs Authored by leading international experts from industry and academia

Although we have seen increased spending on drug research and development, the submission of new drug applications to the US Food and Drug Administration (FDA) has steadily decreased over the past 15 years. Meanwhile, toxicology is celebrating the ten-year anniversary of the introduction of toxicogenomics, a field that was anticipated to change our way of conducting toxicology with enhanced safety assessment. Despite the excitement, and a decade of further technical advancement, the anticipated benefits have been slow to reach the clinical bedside. The failure to translate toxicogenomics to drug development faster, illustrates the need for further innovations in its methodology as well as in its technology. This review introduces the concept of toxicogenomics, summarizes the prominent applications of this relatively young discipline in drug development, and provides a future perspective of advancement in this field.

Despite the large and ever-growing investment in pharmaceutical R&D, the number of innovative new medicines that meet significant unmet medical needs has been stagnant, if not declining. There are many potential reasons for this low return on pharmaceutical R&D investment, but one likely cause is the low probability of the success of clinical trials, particularly in early clinical development. Translational science, which we define as identifying the ‘right’ patient for the ‘right’ drug at the ‘right’ dose, promises to improve not only the odds of success of clinical development, but perhaps more importantly, to get the right drug to the right patient, thereby sparing those patients who may be less likely to benefit from a new therapeutic. We believe that this goal can be achieved by putting the patient first, i.e., by investing in understanding of disease heterogeneity at the molecular level, and then tailoring new therapeutics to subsets of patients. Using examples from the literature and our own experience, we describe current and emerging translational approaches that employ genomic and genetic methods in the areas of cancer, inflammation, and metabolic and infectious disease to this end. We use simple simulations to demonstrate how such translational strategies can significantly reduce the size of clinical trials or increase the likelihood of success of early phase trials. We end by discussing genomic approaches to understand adverse drug reactions.

Early characterization of toxicity and efficacy would significantly impact the overall productivity of pharmaceutical R&D and reduce drug candidate attrition and failure. By describing the available platforms and weighing their relative advantages and disadvantages, including microarray data analysis, Genomics in Drug Discovery and Development introduces readers to the biomarker, pharmacogenomic, and toxicogenomics toolbox. The authors provide a valuable resource for pharmaceutical discovery scientists, preclinical drug safety department personnel, regulatory personnel, discovery toxicologists, and safety scientists, drug development professionals, and pharmaceutical scientists.

This book continues the legacy of a well-established reference within the pharmaceutical industry – providing perspective, covering recent developments in technologies that have enabled the expanded use of biomarkers, and discussing biomarker characterization and validation and applications throughout drug discovery and development. Explains where proper use of biomarkers can substantively impact drug development timelines and costs, enable selection of better compounds and reduce late stage attrition, and facilitate personalized medicine Helps readers get a better understanding of biomarkers and how to use them, for example which are accepted by regulators and which still non-validated and exploratory Updates developments in genomic sequencing, and application of large data sets into pre-clinical and clinical testing; and adds new material on data mining, economics, and decision making, personal genetic tools, and wearable monitoring Includes case studies of biomarkers that have helped and hindered decision making Reviews of the first edition: "If you are interested in biomarkers, and it is difficult to imagine anyone reading this who wouldn't be, then this book is for you." (ISSX) and "...provides a good introduction for those new to the area, and yet it can also serve as a detailed reference manual for those practically involved in biomarker implementation." (ChemMedChem)

This chapter presents the processes required for the translation of a biomarker discovery from the research laboratory into a validated diagnostic for clinical application. To fully investigate the topic of assay validation, a brief review of the current regulatory guidance will be discussed, and thereafter this is used as the framework for topics surrounding assay validation. The time-sensitive stages in the assay development process and agreement with clinical development timelines are critical to delivering a viable clinic-ready assay. Methods to best maneuver this are presented to help emphasize the necessary level of validation for use of an assay in a clinical setting. Each pertinent stage is then described, and key focus areas are highlighted. For certain stages of the development process, such as cut-point determination, multiple vs. single analyte, classifier training/testing, and precision determination, various statistical arguments are presented to illustrate common misconceptions or potential pitfalls.

The goal of personalized healthcare in the treatment of cancer is to reduce the attrition of novel oncology drugs and improve patient outcomes. The discovery and application of novel biomarkers is essential for the successful implementation of personalized healthcare for cancer patients. This chapter focuses on the types of biomarkers that can be utilized clinically to guide treatment decisions in multiple cancer indications, including pharmacodynamic, predictive, prognostic, resistance, and surrogate biomarkers. Furthermore, multiple distinct examples highlight how the successful implementation of these biomarkers into clinical practice has benefited particular subsets of patients. Although these successful examples represent important first steps in using simple biomarkers to predict patient response, significant challenges still exist in prospectively identifying or co-developing biomarkers as companion diagnostics. The roles next generation sequencing and innovative biomarker-driven clinical trial design may play in overcoming these challenges are discussed.

Autoimmune diseases constitute a wide range of mostly complex and multifactorial disorders that are difficult to treat. Increasing insight in the pathogenesis of autoimmune diseases has led to development of targeted therapies aimed at regulating key components of the disease pathways. In particular, the advent of biologic therapeutics has led to significant advances in the treatment of autoimmune diseases. However, the multifactorial nature of the different clinical entities, reflected by the uniqueness of an individual’s genetic make-up and environmental factors, create a high degree of molecular and clinical heterogeneity within a clinically defined disease. Consequently, targeted therapies are not efficacious for all patients diagnosed with such a disease, and selection of therapies is still conducted on a trial-and-error basis. With the rapid advances in modern genomics and genetics technology, there has been some encouraging progress made in the last several years in developing genomic biomarkers as pharmacodynamics markers to evaluate target neutralization for dose selection in pivotal trials, and to identify and evaluate potential predictive markers for efficacy in targeted therapies. This chapter provides highlights and case studies in this field.