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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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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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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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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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Updated: Feb 17, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
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Panomics for Precision Medicine.

Charanjit Sandhu1, Alia Qureshi2, Andrew Emili1

  • 1Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Trends in Molecular Medicine
|December 9, 2017
PubMed
Summary
This summary is machine-generated.

The digital transformation of medicine involves analyzing vast molecular data using panomics (integrated multi-omics analysis). This approach aims to uncover hidden relationships for developing precision medicine and targeted therapies.

Keywords:
genomicsmetabolomicspanomicsprecision medicineproteomicstranscriptomics

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics
  • Proteomics
  • Metabolomics

Background:

  • High-throughput technologies generate massive datasets (genomic, transcriptomic, proteomic, metabolomic).
  • Interpreting complex molecular data is crucial for understanding health and disease.
  • Current methods face challenges in integrating multi-dimensional biological information.

Purpose of the Study:

  • To highlight the need for novel computational tools and data pipelines.
  • To introduce the concept and potential of panomics for integrated data analysis.
  • To outline the path towards precision medicine through multi-omics integration.

Main Methods:

  • Development of advanced data pipelines for handling large-scale biological data.
  • Application of computational tools for the integrated analysis of multi-omics datasets.
  • Exploration of 'panomics' as a strategy for combining diverse molecular data.

Main Results:

  • Panomics enables the discovery of non-obvious relationships within complex biological data.
  • Integrated analysis facilitates the identification of novel biomarkers.
  • This approach supports the development of targeted therapeutics.

Conclusions:

  • The integration of multi-omics data through panomics is key to advancing precision medicine.
  • Addressing inter-individual variations in treatment is a central goal.
  • Digital transformation in medicine relies on sophisticated computational approaches for data interpretation.