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Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and

K Venkatakrishnan1, L E Friberg, D Ouellet

  • 1Clinical Pharmacology, Takeda Pharmaceuticals International Co., Cambridge, Massachusetts, USA.

Clinical Pharmacology and Therapeutics
|February 12, 2015
PubMed

Insights

Quantitative clinical pharmacology, including modeling and simulation, can improve oncology drug development success. These strategies optimize dosing for novel cancer therapies, enhancing patient benefit-risk balance.

Area of Science:

  • Oncology
  • Clinical Pharmacology
  • Biomedical Research

Background:

  • Despite advances in understanding cancer hallmarks and targeted therapies, oncology drug development success rates remain low.
  • Optimizing the benefit-risk balance of novel cancer therapeutics requires objective dose selection informed by exposure-response relationships.

Purpose of the Study:

  • To review the principles and applications of modeling and simulation (M&S) in oncology drug development.
  • To illustrate the value of integrating quantitative clinical pharmacology strategies throughout the drug development lifecycle.

Main Methods:

  • Review of existing literature on M&S in oncology drug development.
  • Discussion of quantitative clinical pharmacology principles and applications.
  • Presentation of illustrative examples across the drug development continuum.

Main Results:

  • M&S approaches offer opportunities for objective dose selection in oncology.
  • Integration of quantitative strategies enhances understanding of exposure-response relationships.
  • Value is demonstrated from preclinical through clinical evaluation phases.

Conclusions:

  • Modeling and simulation are crucial for optimizing oncology drug development.
  • Quantitative clinical pharmacology strategies improve the benefit-risk assessment of novel cancer therapies.
  • Systematic application of these methods can increase the success rates of oncology therapeutics.

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