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Illuminating the Numbers: Integrating Mathematical Models to Optimize Photomedicine Dosimetry and Combination Therapies.

Publication ,  Journal Article
Spring, BQ; Lang, RT; Kercher, EM; Rizvi, I; Wenham, RM; Conejo-Garcia, JR; Hasan, T; Gatenby, RA; Enderling, H
Published in: Front Phys
April 2019

Cancer photomedicine offers unique mechanisms for inducing local tumor damage with the potential to stimulate local and systemic anti-tumor immunity. Optically-active nanomedicine offers these features as well as spatiotemporal control of tumor-focused drug release to realize synergistic combination therapies. Achieving quantitative dosimetry is a major challenge, and dosimetry is fundamental to photomedicine for personalizing and tailoring therapeutic regimens to specific patients and anatomical locations. The challenge of dosimetry is perhaps greater for photomedicine than many standard therapies given the complexity of light delivery and light-tissue interactions as well as the resulting photochemistry responsible for tumor damage and drug-release, in addition to the usual intricacies of therapeutic agent delivery. An emerging multidisciplinary approach in oncology utilizes mathematical and computational models to iteratively and quantitively analyze complex dosimetry, and biological response parameters. These models are parameterized by preclinical and clinical observations and then tested against previously unseen data. Such calibrated and validated models can be deployed to simulate treatment doses, protocols, and combinations that have not yet been experimentally or clinically evaluated and can provide testable optimal treatment outcomes in a practical workflow. Here, we foresee the utility of these computational approaches to guide adaptive therapy, and how mathematical models might be further developed and integrated as a novel methodology to guide precision photomedicine.

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Published In

Front Phys

DOI

ISSN

2296-424X

Publication Date

April 2019

Volume

7

Location

Switzerland

Related Subject Headings

  • 51 Physical sciences
  • 49 Mathematical sciences
 

Citation

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Spring, B. Q., Lang, R. T., Kercher, E. M., Rizvi, I., Wenham, R. M., Conejo-Garcia, J. R., … Enderling, H. (2019). Illuminating the Numbers: Integrating Mathematical Models to Optimize Photomedicine Dosimetry and Combination Therapies. Front Phys, 7. https://doi.org/10.3389/fphy.2019.00046
Spring, Bryan Q., Ryan T. Lang, Eric M. Kercher, Imran Rizvi, Robert M. Wenham, José R. Conejo-Garcia, Tayyaba Hasan, Robert A. Gatenby, and Heiko Enderling. “Illuminating the Numbers: Integrating Mathematical Models to Optimize Photomedicine Dosimetry and Combination Therapies.Front Phys 7 (April 2019). https://doi.org/10.3389/fphy.2019.00046.
Spring BQ, Lang RT, Kercher EM, Rizvi I, Wenham RM, Conejo-Garcia JR, et al. Illuminating the Numbers: Integrating Mathematical Models to Optimize Photomedicine Dosimetry and Combination Therapies. Front Phys. 2019 Apr;7.
Spring, Bryan Q., et al. “Illuminating the Numbers: Integrating Mathematical Models to Optimize Photomedicine Dosimetry and Combination Therapies.Front Phys, vol. 7, Apr. 2019. Pubmed, doi:10.3389/fphy.2019.00046.
Spring BQ, Lang RT, Kercher EM, Rizvi I, Wenham RM, Conejo-Garcia JR, Hasan T, Gatenby RA, Enderling H. Illuminating the Numbers: Integrating Mathematical Models to Optimize Photomedicine Dosimetry and Combination Therapies. Front Phys. 2019 Apr;7.

Published In

Front Phys

DOI

ISSN

2296-424X

Publication Date

April 2019

Volume

7

Location

Switzerland

Related Subject Headings

  • 51 Physical sciences
  • 49 Mathematical sciences