Chapter title |
The Impact of Pharmacogenomics in Personalized Medicine.
|
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Chapter number | 110 |
Book title |
Current Applications of Pharmaceutical Biotechnology
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Published in |
Advances in biochemical engineering biotechnology, September 2019
|
DOI | 10.1007/10_2019_110 |
Pubmed ID | |
Book ISBNs |
978-3-03-040463-5, 978-3-03-040464-2
|
Authors |
Singh, Dev Bukhsh, Dev Bukhsh Singh |
Abstract |
Recent advances in Pharmacogenomics have made it possible to understand the reasons behind the different response of a drug. Discovery of genetic variants and its association with the varying response of drug provide the basis for recommending a drug and its dose to an individual patient. Genetic makeup-based prescription, design, and implementation of therapy not only improve the outcome of treatments but also reduce the risk of toxicity and other adverse effects. A better understanding of individual variations and their effect on drug response, metabolism excretion, and toxicity will replace the trial-and-error approach of treatment. Evidence of the clinical utility of pharmacogenetics testing is only available for a few medications, and FDA labels only require pharmacogenetics testing for a small number of drugs. Although there is a great promise, there are not many examples where Pharmacogenomics impacts clinical utility. Some genetic variants related to different diseases have been reported, and many have not been studied yet. The information related to the outcome of treatment with a particular drug and a genetic variant can be used to release a warning/label for the use of that drug. There are many limitations in the way of implementing the goal of personalized medicine. Future advances in the field of genomics, diagnosis approaches, data analysis, clinical decision-making, and sustainable business model for personalization of therapy can speed up the individualization of therapy based on genetic makeup. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 89 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 12 | 13% |
Student > Bachelor | 12 | 13% |
Student > Ph. D. Student | 6 | 7% |
Other | 5 | 6% |
Researcher | 5 | 6% |
Other | 14 | 16% |
Unknown | 35 | 39% |
Readers by discipline | Count | As % |
---|---|---|
Pharmacology, Toxicology and Pharmaceutical Science | 13 | 15% |
Biochemistry, Genetics and Molecular Biology | 12 | 13% |
Medicine and Dentistry | 5 | 6% |
Business, Management and Accounting | 4 | 4% |
Agricultural and Biological Sciences | 3 | 3% |
Other | 12 | 13% |
Unknown | 40 | 45% |