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Multiscale tumor spatiokinetic model for intraperitoneal therapy.

Jessie L-S Au1, Peng Guo, Yue Gao

  • 1College of Pharmacy, The Ohio State University, Columbus, Ohio, 43210, USA, jau@optimumtx.com.

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|February 27, 2014
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Summary

A new multiscale computational model predicts intraperitoneal chemotherapy drug concentrations in peritoneal tumors. This model accounts for drug properties, tumor heterogeneity, and physiological factors, aiding therapeutic optimization.

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Area of Science:

  • Computational modeling
  • Pharmacokinetics
  • Cancer therapy

Background:

  • Intraperitoneal (IP) chemotherapy requires understanding drug distribution in peritoneal tumors.
  • Tumor heterogeneity and physiological factors significantly impact drug delivery and efficacy.

Purpose of the Study:

  • To establish a multiscale computational model for predicting drug concentrations in peritoneal tumors during IP chemotherapy.
  • To investigate the influence of drug properties, transport mechanisms, tumor heterogeneities, and physiological factors on drug spatiokinetics.

Main Methods:

  • Developed a multiscale model integrating drug transport and clearance across tumor, IP cavity, and organism scales.
  • Utilized the finite element method to solve nonlinear partial differential equations for fluid and solute transport.
  • Incorporated literature-derived and experimental parameters for paclitaxel, including tumor diffusivity and vessel permeability.

Main Results:

  • The model accurately depicted time- and spatial-dependent drug concentrations within peritoneal tumors.
  • It accounted for intratumoral heterogeneity and diffusive/convective drug transport.
  • Model predictions showed good agreement with experimental data for paclitaxel distribution in mice.

Conclusions:

  • The multiscale computational model serves as a valuable tool for quantifying the impact of various factors on IP therapeutic concentrations.
  • It can guide the optimization of drug properties, treatment strategies, and patient-specific therapies for peritoneal tumors.