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Combination Therapies and Personalized Medicine

Combination Therapies and Personalized Medicine

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.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

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Strategy for Biobanking of Ovarian Cancer Organoids: Addressing the Interpatient Heterogeneity across Histological Subtypes and Disease Stages

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Personalized medicine: hope or hype?

Keyan Salari¹, Hugh Watkins, Euan A Ashley

¹Department of Genetics, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 94305, USA.

European Heart Journal

|June 5, 2012

Summary

Personalized medicine leverages genomic data for better patient care. Advances in genome sequencing enable tailored treatments in pharmacogenomics, common disease risk assessment, and rare disease diagnosis.

Area of Science:

Genomics
Personalized Medicine
Clinical Genetics

Background:

Personalized medicine traditionally relied on family history and self-reported race/ethnicity.
Declining costs of genome sequencing increase the availability of specific genomic information.

Purpose of the Study:

To review the utility and limitations of personal genomic data.
To explore applications in pharmacogenomics, common disease risk, and rare disease identification.

Main Methods:

Review of current literature and clinical applications.
Analysis of genomic data interpretation and clinical decision-making.

Main Results:

Genetic tests for monogenic disorders are already clinically useful.

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Improved understanding of genetic associations with drug response and disease is emerging.

Personal genomic data offers potential to enhance risk assessment and diagnosis.

Conclusions:

The era of personalized medicine is approaching, driven by accessible genomic data.
Clinical utility hinges on interpreting and applying genomic information effectively.
Genomic data integration promises to improve patient management and outcomes.