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The right drugs at the right time for the right patient: the MD Anderson precision oncology decision support platform
Amber Johnson1, Jia Zeng1, Ann M Bailey1
1Sheikh Khalifa Al Nahyan Ben Zayed Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Abstract:
The development of resources for clinical interpretation of cancer-associated genetic alterations has significantly lagged behind the technical developments enabling their detection in a time- and cost-efficient manner. The lack of scientific and informatics decision support for oncologists can lead to no action being taken or suboptimal therapeutic choices being made, which could affect the clinical outcome of a patient as well as convoluting research findings from clinical trials. In this article, we describe the precision oncology decision support (PODS) platform developed within The Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy (IPCT) at MD Anderson Cancer Center; the platform aims to bridge the gap between molecular alteration detection and identification of appropriate treatments.
Insights
Clinical interpretation of cancer genetic alterations needs better support. The precision oncology decision support (PODS) platform bridges the gap between detecting molecular changes and choosing optimal cancer treatments.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Technical advances in detecting cancer-associated genetic alterations have outpaced the development of clinical interpretation resources.
- Lack of decision support for oncologists leads to inaction or suboptimal treatment choices, impacting patient outcomes and clinical trial research.
Purpose of the Study:
- To describe the precision oncology decision support (PODS) platform.
- To bridge the gap between molecular alteration detection and the identification of appropriate cancer therapies.
Main Methods:
- Development of the PODS platform at The Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy (IPCT).
- Focus on integrating molecular data with clinical decision-making.
Main Results:
- The PODS platform facilitates the clinical interpretation of cancer-associated genetic alterations.
- The platform aids in identifying appropriate treatments based on molecular profiles.
Conclusions:
- The PODS platform addresses the critical need for clinical decision support in precision oncology.
- Implementing PODS can improve patient outcomes and streamline cancer research by enabling evidence-based therapeutic decisions.
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