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Targeted Cancer Therapies02:57

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The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
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Combination Therapies and Personalized Medicine02:50

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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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Related Experiment Video

Updated: May 4, 2026

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
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Drug-diagnostics co-development in oncology.

Richard Simon1

  • 1Biometric Research Branch, National Cancer Institute , Bethesda, MD , USA.

Frontiers in Oncology
|January 7, 2014
PubMed
Summary

Genomic insights reveal disease heterogeneity, necessitating new clinical trial designs. These predictive approaches ensure new treatments benefit the right patients, improving personalized medicine.

Area of Science:

  • Genomic Medicine
  • Clinical Trial Design
  • Biostatistics

Background:

  • Clinical observations of diverse disease progression and treatment responses are now supported by genomic data.
  • Molecular characterization of diseases offers new therapeutic avenues but complicates clinical trial design and analysis.
  • In oncology, broad patient treatment with targeted therapies is unsustainable if only a few benefit.

Purpose of the Study:

  • To review prospective designs for developing novel therapeutics and predictive biomarkers.
  • To address the need for new paradigms in randomized clinical trial (RCT) design and analysis for predictive medicine.
  • To present a prediction-based analysis approach for RCTs that maintains statistical integrity.

Main Methods:

  • Review of prospective clinical trial designs, ranging from single-biomarker development to genome-wide classifier discovery and validation.
Keywords:
adaptive designclinical trial designcompanion diagnosticenrichment trialpredictive biomarker

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  • Outline of a prediction-based analysis framework for RCTs.
  • Focus on designs that integrate biomarker development with therapeutic evaluation.

    • Main Results:

    • The proposed prediction-based analysis preserves the type I error rate.
    • The approach provides a reliable, internally validated method for identifying patient subgroups likely to benefit from new treatments.
    • Designs accommodate various scenarios, from single biomarker-drug pairs to complex genome-wide predictive models.

    Conclusions:

    • Genomic heterogeneity demands innovative clinical trial designs and analysis methods.
    • Predictive medicine requires robust statistical frameworks to ensure targeted therapies are effectively evaluated and applied.
    • The outlined approach supports the development of personalized medicine by accurately predicting treatment response.