Parallel anticancer drug development and molecular stratification to qualify predictive biomarkers: dealing with

Victor Moreno Garcia1, Philippe A Cassier, Johann de Bono

  • 1Drug Development Unit, The Royal Marsden National Health Service Foundation Trust, Sutton, Surrey, United Kingdom.

Cancer Discovery
|May 16, 2012
PubMed

Insights

Anticancer drug development is slow and costly. This study proposes a parallel process for predictive biomarker and drug development to improve efficiency and reduce risks in clinical trials.

Area of Science:

  • Oncology
  • Pharmacology
  • Biomarker Discovery

Background:

  • Current anticancer drug development models are inefficient, costly, and prone to late-stage failures.
  • The traditional approach, developed decades ago for chemotherapy, struggles with modern targeted therapies.
  • High attrition rates in late-stage clinical trials represent a significant financial and temporal burden.

Purpose of the Study:

  • To address the inefficiencies and high risks in current anticancer drug development.
  • To propose a novel, more efficient parallel process for developing predictive biomarkers and anticancer drugs concurrently.
  • To overcome obstacles hindering progress in molecularly targeted drug development.

Main Methods:

  • Incorporating a Pharmacologic Audit Trail with pharmacokinetic and pharmacodynamic data.
  • Utilizing molecular biomarker-based patient selection in early clinical trials.
  • Leveraging novel technologies like next-generation sequencing and circulating tumor-cell isolation.

Main Results:

  • The proposed parallel process aims to accelerate the qualification of predictive biomarkers.
  • It seeks to reduce the costs and time associated with developing certified clinical assays.
  • This approach is designed to mitigate the risks of late drug attrition.

Conclusions:

  • A parallel development process for predictive biomarkers and anticancer drugs is essential for modern oncology.
  • This strategy can enhance the efficiency and success rate of bringing targeted therapies to patients.
  • Addressing concerns about cost and time is critical for implementing biomarker-driven clinical trials.

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