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Combination Therapies and Personalized Medicine

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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.
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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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

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INTEGRATING COMMUNITY-LEVEL DATA RESOURCES FOR PRECISION MEDICINE RESEARCH.

William S Bush¹, Dana C Crawford, Farren Briggs

¹Department of Population and Quantitative Health Sciences, Case Western Reserve University Cleveland, OH, 44106, USA, wsb36@case.edu.

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Summary

Precision medicine is expanding beyond genomics to include environmental and social factors. New data sources allow linking community health indicators to electronic health records for better disease outcome prediction.

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Area of Science:

Health Informatics
Public Health
Precision Medicine

Background:

Precision medicine traditionally relies on molecular data like genomics.
Environmental, social, and economic factors significantly impact health but are underutilized.
Challenges in quantifying these non-molecular factors hinder clinical integration.

Framework:

Leveraging electronic health information.
Utilizing environmental exposure data.
Employing systematic geo-coding for community health assessment.

Implementation:

Assessing community-level health indicators using new electronic data sources.
Linking community data with electronic health records.
Evaluating the influence of these factors on disease outcomes.

Implications:

Enhancing the scope of precision medicine beyond molecular data.
Improving the systematic assessment and utilization of community-level health determinants.
Validating new data sources against gold standards for clinical utility.