By Claudio Carini, Sandeep M Menon, Mark Chang
The way forward for scientific examine and health and wellbeing Care: From Empirical to Precision Medicine
Clinical and Statistical concerns in custom-made Medicine explores contemporary advances relating to biomarkers and their translation into medical improvement. major clinicians, biostatisticians, regulators, advertisement execs, and researchers tackle the possibilities and demanding situations in effectively utilising biomarkers in drug discovery and preclinical and scientific development.
Robust Biomarkers for Drug improvement and ailment Treatment
The first 4 chapters talk about biomarker improvement from a scientific point of view. assurance levels from an advent to biomarkers to advances in RNAi displays, epigenetics, and infrequent illnesses as ambitions for custom-made medication techniques. next chapters study the statistical issues in utilising a customized drugs method, together with multiplicity in pharmacogenomics. The final bankruptcy assesses the regulatory matters interested by utilizing biomarkers.
Improve sufferer Care and decrease charges and facet Effects
Despite the significant volume of literature on biomarkers, there's no accomplished publication that integrates the scientific and statistical elements. This booklet is likely one of the first to include either the scientific and statistical points of biomarkers within the customized drugs paradigm. overlaying a large spectrum of customized medicine-related issues, it provides cutting-edge strategies for advancing the appliance of biomarkers in drug discovery and improvement.
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Extra info for Clinical and Statistical Considerations in Personalized Medicine
Proteomics offers a unique perspective on the disease process because proteins and their enzymatic functions determine the phenotypic diversity that can arise from a set of common genes (Rifai and Gerszten, 2006). Since posttranslational modifications help regulate the structure, function, localization, maturation, and turnover of proteins and because the entire complement of expressed proteins in their various forms can rapidly change in response to environmental stimuli, the proteome represents the unique collection of proteins that reflects the state of the cell or group of cells at a specific time and space, in a particular context under particular stimuli making the proteome highly dynamic, contrary to the genome (Rifai and Gerszten, 2006).
The most obvious and often quoted use of patient stratification is to select only patients who would be expected to respond to a given investigational drug based on the mechanism of action of the specific drug. The drug’s statistically significant benefits, in this targeted subset of patients, could be shown in a smaller and shorter clinical trial than those needed for randomly selected patients. Under some circumstances, stratification of responders could also be performed retrospectively on the data collected to demonstrate efficacy of a compound in a subpopulation.
APP-Tg mouse for Alzheimer’s disease; TNF-alpha Tg mouse for rheumatoid arthritis and IBD, knock-out, and knock-in) of disease or condition. , small molecules or biologics) and bind them such a way that a desirable biological effect is inflicted. Druggable genome comprises only a fraction of the entire genome hence many key proteins remain “undrugged” either because they are unknown or knowable or they cannot be targeted by current therapeutics. 32 Clinical and Statistical Considerations in Personalized Medicine This in fact provides an opportunity to develop novel therapies that can target the genes and their products that are currently outside of reach with current therapies and reveal novel disease-specific targets or molecular pathways as well as biomarkers to monitor drug efficacy and patient response to treatments.
Clinical and Statistical Considerations in Personalized Medicine by Claudio Carini, Sandeep M Menon, Mark Chang