Paradigm Shift In Bio Pharmaceutical Rd

The biopharmaceutical industry is currently undergoing a transformation driven primarily by the need to move from its proven blockbuster model to a new stratified medicine or nichebuster model [ 1] . This paradigm shift has been anticipated in white papers such as IBM .s Pharma 2010 report [2] and will have to be accompanied by serious efforts to streamline operations and to address research and development (R&D) productivity issues as described and quantified by DiMasi [3] and DiMasi et al. [4] . In its Critical Path initiative [5], the U.S. Food and Drug Administration (FDA) is guiding industry toward use of biomarkers [ 6] that will address efficacy and safety issues and hold the promise of increased R&D productivity [7]. In the excellent biomarker review paper by Trusheim et al. [1], clinical biomarkers are defined as biomarkers that associate a medical treatment to a patient subpopulation that has historically exhibited a differential and substantial clinical response. Clinical biomarkers can be based on "genotypes, proteins, metabonomic patterns, histology, medical imaging, physician clinical observations, or even self-reported patient surveys. A clinical biomarker is not defined by its technology or biological basis, but rather by its reliable, predictive correlation to differential patient responses." It is generally believed that "biomarker-enabled" drug development will lead to better and earlier decision making and that clinical biomarkers will pave the way toward targeted therapeutics combining "precision drugs" for stratified patient populations with diagnostic tests designed to identify not only "responders" (who will benefit) but also patient cohorts at risk for adverse side effects. Biomarker-enabled R&D is evolving into a new discipline with a strong patient focus. Organizations who believe in biomarker-enabled R&D are investing in tools and make the necessary organizational changes to implement the new concepts and associated processes. Among biomarkers, imaging biomarkers have received particular attention because of the noninvasive nature of imaging technologies and the obvious link to diagnostic procedures and clinical care. Imaging technologies are used increasingly as core technologies in biophar-maceutical R&D in both the preclinical and clinical phases of the R&D process.

Disease areas most affected by this paradigm shift are cardiology, oncology, and neurology. Below we discuss in more detail how biomarker-related data types and their increasing volumes are challenging existing information technology (IT) infrastructures, and how IT architectures have to be enhanced and modified to integrate genomic, imaging, and other biomarker data.

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