Pharmacodynamic endpoints as clinical trial objectives to answer important questions in oncology drug development

Ralph E Parchment1, James H Doroshow2

  • 1Clinical Pharmacodynamics Program, Applied/Developmental Research Directorate, Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD.

Seminars in Oncology
|September 25, 2016
PubMed

Insights

Clinical pharmacodynamics (PD) guides targeted therapy development by using biomarkers to optimize biologically effective doses (BED) and schedules, maximizing efficacy and minimizing toxicity in cancer treatment.

Area of Science:

  • Oncology
  • Pharmacology
  • Clinical Trial Design

Background:

  • Understanding the molecular interactions between cancer and drugs is complex.
  • Clinical pharmacodynamics (PD) offers valuable insights into developmental therapeutics.

Purpose of the Study:

  • To provide an overview of clinical PD applications in drug development.
  • To outline a framework for integrating PD analyses into clinical trial design.
  • To highlight the role of PD in optimizing targeted therapies and improving patient outcomes.

Main Methods:

  • Utilizing agent-specific mechanism of action (MOA) PD biomarkers.
  • Developing pharmacodynamics-guided biologically effective dosage regimens (PD-BEDR).
  • Employing MOA-based PD biomarker analyses for patient selection and drug combination design.
  • Incorporating PD analyses in early-phase (Phase 0, I/II) clinical trials for MOA confirmation, dose optimization, and proof-of-concept.

Main Results:

  • Clinical PD enables the determination of the biologically effective dose (BED) and schedule for targeted agents.
  • PD biomarkers can guide the development of personalized dosage regimens (PD-BEDR) to enhance efficacy and reduce toxicity.
  • MOA-based PD analyses serve as diagnostic tools for patient selection and inform novel drug combination strategies.
  • PD analyses are crucial in clinical trials for validating MOA, optimizing dosage, and correlating molecular changes with clinical outcomes.

Conclusions:

  • Clinical pharmacodynamics is essential for advancing targeted cancer therapies.
  • Integrating PD into trial design and utilizing PD biomarkers can lead to more effective and safer treatments.
  • Technological advancements in PD data collection are critical for future progress in precision oncology.

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