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Related Concept Videos

Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Personalized medicine is advancing due to breakthroughs in genomic technologies.
  • Cognitive computing offers new ways to analyze complex biological data.
  • Physicians need tools to interpret vast amounts of genomic information.

Purpose of the Study:

  • To explore the integration of genomic data with cognitive computing for clinical applications.
  • To highlight the role of cognitive systems in personalized medicine.

Main Methods:

  • Review of current genomic technologies and cognitive computing platforms.
  • Focus on Watson for Genomics (WG) as a case study.
  • Integration of omic data with existing medical knowledge bases.

Main Results:

  • Cognitive systems can process and interpret large-scale genomic datasets.
  • Watson for Genomics assists in analyzing patient-specific genomic profiles.
  • This facilitates more informed clinical decision-making.

Conclusions:

  • The convergence of genomics and AI is paving the way for widespread personalized medicine.
  • Cognitive computing tools are essential for unlocking the potential of genomic data in healthcare.
  • Physician support systems are crucial for the effective implementation of genomic insights.