| Author | : Sunil Badve |
| File Size | : 45,7 Mb |
| Publisher | : Springer |
| Language | : English |
| Release Date | : 06 December 2018 |
| ISBN | : 9783319952284 |
| Pages | : 642 pages |
Predictive Biomarkers in Oncology by Sunil Badve Book PDF Summary
“Precision/personalized or stratified medicine” refers to the tailoring of medical treatment or drug administration to the individual characteristics of each patient treatment. It does not literally mean that a pharmaceutical company makes a drug for an individual patient for consumption and treatment but rather means the ability to stratify (or classify) individuals into sub-populations that differ in their responsiveness to a specific drug. A marker that provides information on the likely response to therapy, i.e., either in terms of tumor shrinkage or survival of the patient is termed “predictive biomarker”. Despite their promise in precision medicine and the explosion of knowledge in this area, there is not a single source on this subject that puts all this evidence together in a concise or richly illustrated and easy to understand manner. This book provides a collection of ingeniously organized, well-illustrated and up-to-date authoritative chapters divided into five sections that are clear and easy to understand. Section one provides an overview of biomarkers, introduces the basic terminologies, definitions, technologies, tools and concepts associated with this subject in the form of illustrations/graphics, photographs and concise texts. Several recent biomarker endeavors that have been initiated and funded by the National Cancer Institute, National Institutes of Health, FDA and other International organizations are presented. Section two involves the signaling pathways controlling cell growth and differentiation altered in cancer. This section analyzes how predictive biomarkers are altered (expressed or amplified) across cancer types. Section three explores how predictive biomarkers play a role in patient stratification and tailored treatment in relationship to specific cancers. In addition, it includes discussion on the various precision medicine initiatives that are going on across the globe (e.g. TARGET, NCI-MATCH, BATTLE, SHIVA, etc.). Section four discusses: (a) how pharmaceutical companies validate predictive biomarker assays and accompanying companion diagnostics either internally or externally with partner companies such as central laboratories or clinical research organizations, and (b) how predictive biomarker tests fall under the oversight of US FDA, Centers for Medicare & Medicaid Services (CMS) and state laws. Section five wraps up novel agents and targets that are being used as targets for cancer therapeutics. The biomarkers associated with these protocols will also be presented. Throughout the book, sidebars, special interest boxes and illustrations are used to explain terms that are either newly introduced, uncommon, or specialized. Predictive Biomarkers in Oncology will serve as a definitive guide for practicing pathologists, oncologists, basic researchers, and personnel in the pharmaceutical or diagnostic industry interested in learning how “predictive biomarkers” are used in precision cancer therapy.