Promise and progress for functional and molecular imaging of response to targeted therapies

Renu M Stephen1, Robert J Gillies

  • 1Arizona Cancer Center, University of Arizona, 1515 N. Campbell, P.O. box: 245024, Tucson, Arizona 85724, USA. rms3@email.arizona.edu

Insights

Molecular and functional imaging offers non-invasive, longitudinal assessment of anticancer therapy response. These imaging biomarkers can improve drug development efficiency and predict treatment outcomes, justifying their cost.

Area of Science:

  • Oncology
  • Medical Imaging
  • Pharmacology

Background:

  • Biomarkers are crucial for predicting and monitoring anticancer therapy response.
  • Molecular and functional imaging are promising non-invasive biomarkers for longitudinal assessment in patients and tumors.
  • Despite their potential, imaging endpoints are underutilized in clinical trial design due to cost concerns.

Purpose of the Study:

  • To review the progress of imaging in response to novel anticancer therapies.
  • To highlight the potential of imaging biomarkers to enhance drug development efficiency.
  • To discuss the theranostic promise of imaging for predicting targeted therapy response.

Main Methods:

  • Review of current literature on molecular and functional imaging in oncology.
  • Focus on imaging modalities like Diffusion-Weighted MRI, DCE-MRI, and FDG-PET.
  • Analysis of imaging response to targeted therapies against PI3K/AKT, HIF-1alpha, and VEGF pathways.

Main Results:

  • Imaging biomarkers can improve efficiency across all phases of drug development, from discovery to Phase III.
  • Specific imaging techniques show potential for in vivo pharmacodynamics and patient enrichment.
  • Progress is being made in applying imaging to new targeted anticancer therapies.

Conclusions:

  • Molecular and functional imaging are valuable tools for anticancer drug development.
  • Integrating imaging endpoints can increase efficiency and reduce costs in clinical trials.
  • The ultimate goal is theranostic application of imaging to predict treatment response before therapy initiation.

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