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Per Med. 2015 Jun 1;12(3):245-257.

Integrative network modeling approaches to personalized cancer medicine.

Author information

1
Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
2
Department of Medicine Hematology & Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
3
Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Abstract

The ability to collect millions of molecular measurements from patients is a now a reality for clinical medicine. This reality has created the challenge of how to integrate these vast amounts of data into models that accurately predict complex pathophysiology and can translate this complexity into clinically actionable outputs. Integrative informatics and data-driven approaches provide a framework for analyzing large-scale datasets and combining them into multiscale models that can be used to determine the key drivers of disease and identify optimal therapies for treating tumors. In this perspective we discuss how an integrative modeling approach is being used to inform individual treatment decisions, highlighting a recent case report that illustrates the challenges and opportunities for personalized oncology.

KEYWORDS:

drug repositioning; genomics; multiple myeloma; multiscale modeling; networks; personalized medicine

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