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Current Pharmacogenomics and Personalized Medicine


ISSN (Print): 1875-6921
ISSN (Online): 1875-6913

Review Article

Impact of New Technologies on Pharmacogenomics

Author(s): Maria Isidoro-Garcia*, Almudena Sanchez-Martin and Belen Garcia-Berrocal

Volume 14, Issue 2, 2016

Page: [74 - 85] Pages: 12

DOI: 10.2174/1875692115666170214152152

Price: $65


Background: Genomic basis of drug response is the main objective of Pharmacogenomic studies. The classical paradigm of clinical treatment focused in the disease is becoming a new approach, the Personalized Medicine (PM) based on the individual patient. One important challenge of PM application is the availability of adequate and validated genetic information.

Objective: In this review, we will focus on the impact of new technologies on Pharmacogenomics, the most recent advances to be applied to Personalized Medicine and how they contribute to face arising challenges related to quality aspects, clinical validation, cost and education.

Method: Current situation of new methodologies such as single cell sequencing, long fragment reads or nanopore systems is reviewed using Pubmed in order to explore the scientific literature and to assess their contribution to boost the translation from basic pharmacogenomics to clinical practice.

Results: An overview of the most recent technological advances to be applied to pharmacogenomics is provided, including a discussion about advantages and disadvantages of the different approaches.

Conclusion: The great development of new technologies can open promising insight on pharmacogenomics, allowing to study genes involved in pharmacokinetics and pharmacodynamics and providing holistic information of drug toxicity and efficacy. The understanding of therapeutic effects, adverse events and drugs interaction is still limited by incomplete knowledge of cellular pathways, therefore inferring interacting biological molecules involved in drug response is required.

Keywords: Nanopores, personalized medicine, pharmacogenetics, pharmacogenomics, sequencing, single cell sequencing.

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