title: Multiscale tumor spatiokinetic model for intraperitoneal therapy.
abstract: This study established a multiscale computational model for intraperitoneal (IP) chemotherapy, to depict the time-dependent and spatial-dependent drug concentrations in peritoneal tumors as functions of drug properties (size, binding, diffusivity, permeability), transport mechanisms (diffusion, convection), spatial-dependent tumor heterogeneities (vessel density, cell density, pressure gradient), and physiological properties (peritoneal pressure, peritoneal fluid volume). Equations linked drug transport and clearance on three scales (tumor, IP cavity, whole organism). Paclitaxel was the test compound. The required model parameters (tumor diffusivity, tumor hydraulic conductivity, vessel permeability and surface area, microvascular hydrostatic pressure, drug association with cells) were obtained from literature reports, calculation, and/or experimental measurements. Drug concentration-time profiles in peritoneal fluid and plasma were the boundary conditions for tumor domain and blood vessels, respectively. The finite element method was used to numerically solve the nonlinear partial differential equations for fluid and solute transport. The resulting multiscale model accounted for intratumoral spatial heterogeneity, depicted diffusive and convective drug transport in tumor interstitium and across blood vessels, and provided drug flux and concentration as a function of time and spatial position in the tumor. Comparison of model-predicted tumor spatiokinetics with experimental results (autoradiographic data of 3H-paclitaxel in IP ovarian tumors in mice, 6 h posttreatment) showed good agreement (1% deviation for area under curve and 23% deviations for individual data points, which were several-fold lower compared to the experimental intertumor variations). The computational multiscale model provides a tool to quantify the effects of drug-, tumor-, and host-dependent variables on the concentrations and residence time of IP therapeutics in tumors.
authors.affiliation: College of Pharmacy, The Ohio State University, Columbus, Ohio, 43210, USA, jau@optimumtx.com.
authors.forename: Jessie L-S
authors.initials: JL
authors.lastname: Au
authors.forename: Peng
authors.initials: P
authors.lastname: Guo
authors.forename: Yue
authors.initials: Y
authors.lastname: Gao
authors.forename: Ze
authors.initials: Z
authors.lastname: Lu
authors.forename: Michael G
authors.initials: MG
authors.lastname: Wientjes
authors.forename: Max
authors.initials: M
authors.lastname: Tsai
authors.forename: M Guillaume
authors.initials: MG
authors.lastname: Wientjes
mesh_terms: D000465:Algorithms; D000818:Animals; D000970:Antineoplastic Agents / Q000008:administration & dosage* / Q000493:pharmacokinetics*; D001202:Ascitic Fluid / Q000378:metabolism; D003198:Computer Simulation; D004058:Diffusion; D007274:Injections, Intraperitoneal / Q000379:methods*; D007408:Intestinal Absorption; D051379:Mice; D008807:Mice, Inbred BALB C; D008954:Models, Biological; D009369:Neoplasms / Q000188:drug therapy / Q000378:metabolism; D014018:Tissue Distribution
chemical_list: D000970:Antineoplastic Agents