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Published on: August 12, 2019
Translational research: A patient-centered approach to bridge the valley of death
Anish Thomas1, Parth Desai1, Nobuyuki Takahashi2
1Developmental Therapeutics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Abstract:
Animal models have evolved to be a key component of translational research of cancer, and they are now extensively used to test drug candidates, predict drug responses, and essentially drive discovery of cancer biology. However, the model-centric approach has not yielded the expected abundance of treatment advances. We propose that the focus of translational research needs to shift from animal models to human patients, and the goal should be to understand why tumor responses and outcomes are so variable between patients and how it can be predicted at the individual level and thus to generate hypotheses that are more relevant to people than to atypically sensitive animal models.
Insights
Translational cancer research must shift focus from animal models to human patients. Understanding individual tumor variability is key to predicting patient outcomes and advancing cancer treatments.
Area of Science:
- Oncology
- Translational Research
- Cancer Biology
Background:
- Animal models are crucial in cancer research for drug testing and biological discovery.
- Despite extensive use, animal models have not led to expected treatment advances.
- A model-centric approach may limit the translation of findings to human patients.
Purpose of the Study:
- To propose a shift in translational research focus from animal models to human patients.
- To emphasize understanding inter-patient tumor variability for personalized treatment prediction.
- To generate more human-relevant hypotheses in cancer research.
Main Methods:
- This study is a conceptual proposal and does not involve experimental methods.
- It advocates for a paradigm shift in research strategy.
- Focuses on analyzing patient data and clinical outcomes.
Main Results:
- The current model-centric approach has limitations in predicting human cancer response.
- Patient-level variability in tumor response and outcomes is significant.
- A human-centric approach is proposed to improve translational success.
Conclusions:
- Translational cancer research should prioritize human patient data over animal models.
- Understanding individual patient variability is essential for predicting treatment efficacy.
- Shifting focus to patients will yield more relevant discoveries and treatment advances.
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