Successes Achieved and Challenges Ahead in Translating Biomarkers into Clinical Applications

Abstract

Abstract. Biomarkers are important tools for identifying and stratifying diseases, predicting their progression and determining the effectiveness, safety, and doses of therapeutic interventions. This is important for common chronic diseases such as diabetic nephropathy, osteoporosis, and rheumatoid arthritis which affect large numbers of patients worldwide. This article summarizes the current knowledge of established and novel biomarkers for each of these diseases as presented at the 2008 AAPS/ACCP joint symposium "Success Achieved and Challenges Ahead in Translating Biomarkers into Clinical Applications," in Atlanta, Georgia. The advantages and disadvantages of various proteomic, metabolomic, genomic, and imaging biomarkers are discussed in relation to disease diagnosis and stratification, prognosis, drug development, and potential clinical applications. The use of biomarkers as a means to determine therapeutic interventions is also considered. In addition, we show that biomarkers may be useful for adapting therapies for individual needs by allowing the selection of patients who are most likely to respond or react adversely to a particular treatment. They may also be used to determine whether the development of a novel therapy is worth pursuing by informing crucial go/no go decisions around safety and efficacy. Indeed, regulatory bodies now suggest that effective integration of biomarkers into clinical drug development programs is likely to promote the development of novel therapeutics and more personalized medicine.

Novel Drug Metabolism Indices for Pharmacogenetic Functional Status Based on Combinatory Genotyping of CYP2C9 , CYP2C19 and CYP2D6 Genes

“…There may be several clinically relevant applications of the CYP450 combinatory drug metabolism indices [39,41]. Index scores can be easily calculated by following the allele specifications in Table 2.…”

“…Together, these novel drug metabolism indices provide a quantitative foundation upon which researchers and clinicians may build precise research analytics, enhance drug response through more informed selection, diminish side effects, increase adherence and reduce inpatient length of stay [39]. Our novel combinatory and drug-specific metabolism benchmarking models will facilitate the translation of genetic biomarker discovery and research to clinical practice by both improving and simplifying the research, analytical and translational processes [40,41]. …”

Introduction

“…The discovery process has seen radical changes over the last 5-10 years as research continues to make strides in identifying biomarkers of disease (Amur et al, 2008;Krishna et al, 2008;Tesch et al, 2010). The discovery process has seen radical changes over the last 5-10 years as research continues to make strides in identifying biomarkers of disease (Amur et al, 2008;Krishna et al, 2008;Tesch et al, 2010).…”

The role of biomarkers in the development of novel cancer therapies

“…Genomic biomarkers are adding another dimension to healthcare by enabling us to understand the germ line and somatic basis of disease development, as well as differential clinical responses to a specifi c medical treatment (8) .…”