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Drug Discovery in a Multidimensional World: Systems, Patterns, and Networks

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Abstract

Despite great strides in revealing and understanding the physiological and molecular bases of cardiovascular disease, efforts to translate this understanding into needed therapeutic interventions continue to lag far behind the initial discoveries. Although pharmaceutical companies continue to increase investments into research and development, the number of drugs gaining federal approval is in decline. Many factors underlie these trends, and a vast number of technological and scientific innovations are being sought through efforts to reinvigorate drug discovery pipelines. Recent advances in molecular profiling technologies and development of sophisticated computational approaches for analyzing these data are providing new, systems-oriented approaches towards drug discovery. Unlike the traditional approach to drug discovery which is typified by a one-drug-one-target mindset, systems-oriented approaches to drug discovery leverage the parallelism and high-dimensionality of the molecular data to construct more comprehensive molecular models that aim to model broader bimolecular systems. These models offer a means to explore complex molecular states (e.g., disease) where thousands to millions of molecular entities comprising multiple molecular data types (e.g., proteomics and gene expression) can be evaluated simultaneously as components of a cohesive biomolecular system. In this paper, we discuss emerging approaches towards systems-oriented drug discovery and contrast these efforts with the traditional, unidimensional approach to drug discovery. We also highlight several applications of these system-oriented approaches across various aspects of drug discovery, including target discovery, drug repositioning and drug toxicity. When available, specific applications to cardiovascular drug discovery are highlighted and discussed.

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Acknowledgments

JTD is supported by the NLM Biomedical Informatics Training Grant (T15 LM007033) to Stanford University. AJB is supported by funding from the National Library of Medicine (R01 LM009719).

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Authors and Affiliations

  1. Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA, USA

    Joel T. Dudley & Marina Sirota

  2. Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA

    Joel T. Dudley, Marina Sirota & Atul J. Butte

  3. Lucile Packard Children’s Hospital, Palo Alto, CA, USA

    Joel T. Dudley, Marina Sirota & Atul J. Butte

  4. Pacific Biosciences, 1505 Adams Drive, Menlo Park, CA, USA

    Eric Schadt

  5. Sage Bionetworks, Palo Alto, CA, USA

    Eric Schadt

  6. Division of Cardiovascular Medicine, Stanford University School of Medicine, Falk CVRC 300 Pasteur Drive; MC5406, Stanford, 94305-5406, CA, USA

    Euan Ashley

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  1. Joel T. Dudley
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  2. Eric Schadt
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  3. Marina Sirota
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  4. Atul J. Butte
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  5. Euan Ashley
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Correspondence to Euan Ashley.

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Dudley, J.T., Schadt, E., Sirota, M. et al. Drug Discovery in a Multidimensional World: Systems, Patterns, and Networks. J. of Cardiovasc. Trans. Res. 3, 438–447 (2010). https://doi.org/10.1007/s12265-010-9214-6

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