Roadmap for developing and validating therapeutically

drug “repurposing”, entirely from studies and to validate these in an animal model.It is even more remarkable that this straightforward model seamlessly incorporates genome-wide complexity and thus fundamentally differs from previous multiscale combinatorial approaches that reduce drug repositioning to prioritized molecular mechanisms.The basis for this shift toward computational integrative approaches has precedence in scalar theories of biological information and is aptly warranted for exploitation in drug repurposing.In 1957, Francis Crick introduced a theory of information flow across biological scales from different molecular sequences: his “central dogma of molecular biology [that] deals with the detailed residue-by-residue transfer of sequential information.” (3).In the process of validation of a biomarker assay, a key point is the validation of the methodology.Here we discuss the challenges for the technical validation of immunohistochemical and gene expression assays to detect tumour biomarkers and provide suggestions of pragmatic solutions to address these challenges.

Here we discuss the basis of this shift toward genomic computational integrative approaches that has precedence in scalar theories of biological information and is aptly warranted for exploitation in drug repurposing.“…Biomarkers are the defining facet of translational cancer research; however, there is a great deal of confusion about the actual definition of what a biomarker is and what its characteristics are.Arguably, the most widely accepted definition is the one put forward by the Biomarkers Definitions Working Group, which defines a biomarker as "a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention" [].While personalised cancer medicine holds great promise, targeting therapies to the biological characteristics of patients is limited by the number of validated biomarkers currently available.The implementation of biomarkers has undergone many challenges with few biomarkers reaching cancer patients in the clinic.Several biomarkers have been reported to be associated with survival in breast cancer over the past decades.Unfortunately, it is often difficult to distinguish between the prognostic and predictive values of these proposed markers and independent validations are frequently lacking.The European Medicines Agency (EMA) has approved 48 drugs since 1995 which address indications in one or more of these cancer diseases; however, only 18 of these therapies are correlated with companion diagnostics (CDxs), based on the use of 5 biomarkers [2].Currently, the traditional ‘one size fits all' development of cancer agents leads only to statistically significant but marginal clinical benefit; so, employing biomarkers to better select patients for therapies underpins the personalised or precision medicine approach to identify reliably those patients who will derive benefit from treatment.In 2014, there were approximately 800 cancer agents in phase II or III clinical trials in the United States [3]; many of these drugs are intended to target specific biological pathways; validated biomarkers are required to identify those tumours in which these drugs are likely to be active.Therefore, there is an urgent need to develop a system which is more efficient in introducing biomarkers into clinical practice.

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