Evidence map›Paper›PMID 31123672›Full record

ArticleFrontiers in physics2019

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

Bryan Q Spring, Ryan T Lang, Eric M Kercher, Imran Rizvi, Robert M Wenham, José R Conejo-Garcia, Tayyaba Hasan, Robert A Gatenby, Heiko Enderling

Abstract read
In one paragraph

Article in Frontiers in physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Bryan Q SpringTranslational Biophotonics Cluster, Northeastern University, Boston, MA, United States.
Ryan T LangTranslational Biophotonics Cluster, Northeastern University, Boston, MA, United States.
Eric M KercherTranslational Biophotonics Cluster, Northeastern University, Boston, MA, United States.
Imran RizviJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, Chapel Hill, NC, United States.
Robert M WenhamDepartment of Gynecologic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States.
José R Conejo-GarciaDepartment of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States.
Tayyaba HasanWellman Center for Photomedicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
Robert A GatenbyDepartment of Diagnostic Imaging and Interventional Radiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States.
Heiko EnderlingDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States.

Funding

Vascular Leukocytes Influence the Tumor MicroenvironmentR01CA124515 · NCI · WISTAR INSTITUTE · PI Jose R Conejo-Garcia · 2007 to 2026
$7.1M
Initiation and Evolution of the Ovarian Cancer MicroenvironmentR01CA157664 · NCI · WISTAR INSTITUTE · PI CONEJO-GARCIA, JOSE R · 2011 to 2020
$3.8M
Targeting Determinants of OvCa Metastases in Engineered 3D Microfluidic PlatformsR00CA175292 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RIZVI, IMRAN · 2016 to 2019
$746k
Online monitoring and image-guided treatment of chemoresistant micrometastasesK22CA181611 · NCI · NORTHEASTERN UNIVERSITY · PI SPRING, BRYAN QUILTY · 2015 to 2017
$559k
NCI NIH HHS K22 CA181611NCI NIH HHS R00 CA175292NCI NIH HHS R01 CA124515NCI NIH HHS R01 CA157664
6 · The paper itself

Abstract

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.

Indexed as

cancercombination therapycomputational modelingimmunotherapymathematical oncologyphotodynamic therapyphotomedicine

Identifiers

PMID31123672
PMCPMC6529192

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.