Clinical pharmacology and therapeutics
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Clin. Pharmacol. Ther. · Mar 2016
EditorialBig Data Transforms Discovery-Utilization Therapeutics Continuum.
Enabling omic technologies adopt a holistic view to produce unprecedented insights into the molecular underpinnings of health and disease, in part, by generating massive high-dimensional biological data. Leveraging these systems-level insights as an engine driving the healthcare evolution is maximized through integration with medical, demographic, and environmental datasets from individuals to populations. Big data analytics has accordingly emerged to add value to the technical aspects of storage, transfer, and analysis required for merging vast arrays of omic-, clinical-, and eco-datasets. In turn, this new field at the interface of biology, medicine, and information science is systematically transforming modern therapeutics across discovery, development, regulation, and utilization.
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Clin. Pharmacol. Ther. · Mar 2016
ReviewLeveraging big data to transform target selection and drug discovery.
The advances of genomics, sequencing, and high throughput technologies have led to the creation of large volumes of diverse datasets for drug discovery. Analyzing these datasets to better understand disease and discover new drugs is becoming more common. ⋯ The past few years have witnessed successful use of big data in many sectors across the whole drug discovery pipeline. In this review, we will highlight the state of the art in leveraging big data to identify new targets, drug indications, and drug response biomarkers in this era of precision medicine.
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The concept of precision medicine has entered broad public consciousness, spurred by a string of targeted drug approvals, highlighted by the availability of personal gene sequences, and accompanied by some remarkable claims about the future of medicine. It is likely that precision medicines will require precision drug development programs. What might such programs look like?
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Clin. Pharmacol. Ther. · Feb 2016
Integrated patient and tumor genetic testing for individualized cancer therapy.
Tumor genome analysis is transforming cancer treatment by enabling identification of specific oncogenic drivers and selection of effective targeted agents. Meanwhile, patient genome analysis is being employed across therapeutic areas to inform selection of appropriate drugs and doses for treatment safety. Integration of patient genome analysis concurrent with preemptive tumor genetic testing will enable oncologists to make informed treatment decisions to select the right dose of the right drug for each patient and their tumor.