Abstract

Progress in understanding biological circuits, advances in enabling technologies including the high-throughput platforms of genomics, proteomics and metabolomics, the evolution in drug target discovery and the development of companion diagnostics set the healthcare enterprise on the verge of personalized disease management [1]. This revolution in clinical care is dependent on molecular diagnostics that predict and prevent disease, enabling the diagnosis and treatment of individual patients and populations [2]. Diagnostic biomarkers are quantifiable disease characteristics that provide information about underlying molecular processes to define disease progression or predict treatment response. Familiar diagnostic biomarkers include traditional measurements (heart rate and blood pressure), imaging techniques (chest x-ray and mammograms) and protein measurements (PSA and CEA). The revolution in biology and high-throughput technology has provided an opportunity to develop a new generation of companion and complementary diagnostics, including single-nucleotide polymorphism analysis, genomic and proteomic profiling, epigenetic profiling and gene expression profiling [3]. In turn, these diagnostics increase disease-specific sensitivity and specificity, contributing to the accuracy of personalized disease management. This advancing wave of innovation has induced the next generation of biotechnology to capture the use of companion diagnostics for the application of specific therapeutic agents to the clinical care of individuals and populations [4]. Yet, as pointed out in this issue by Milne et al., the potential of biomarker technologies, in the form of companion and complementary diagnostics, to revolutionize clinical care has not been fully realized, reflecting a disconnect between the emergence of discovery technologies and models for their validation, early adoption and application across disease populations [5]. These limitations in the validation of molecular diagnostics have raised considerations regarding approval and marketing by regulatory agencies. Moreover, as highlighted in this issue by Cohen et al., the paucity of biomarker validation serves as a considerable obstacle to the adoption of companion diagnostics by healthcare providers and payors [6]. The evolving regulatory and reimbursement environments, in conjunction with the central importance of analytic validation and clinical qualification, has resulted in barriers to adoption that have restricted the full impact of companion diagnostics in clinical practice [5,6]. The emergence of analytic technologies for evaluating nucleic acids and proteins, which are associated with the deconvolution of the human genome, provided the technological push to develop molecular biomarkers for disease management [7]. Conversely, Companion diagnostics at the intersection of personalized medicine and healthcare delivery

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