Tissue transport affects how treatment scheduling increases the efficacy of chemotherapeutic drugs.

A method to predict the effect of tissue transport on the scheduling of chemotherapeutic treatment could increase efficacy. Many drugs with desirable pharmacokinetic properties fail in vivo due to poor transport through tissue. To predict the effect of treatment schedule on drug efficacy we developed an in silico method that integrates diffusion through tissue and cell binding into a pharmacokinetic model. The model was evaluated with an array of theoretical drugs that had different rates of diffusivity, binding, and clearance. The efficacy of each drug, quantified as the fraction of cells killed, was calculated for twenty dosage schedules. Simulations showed that efficacy strongly depended on tissue transport, with a range of 0.00 to 99.99%, despite each drug having equal plasma areas under the curve (AUC). For most drugs, schedules that increased exposure also increased efficacy. Drugs with fast clearance benefited the most from increasing the number of doses and this was most effective for those with intermediary binding. All drugs with slow diffusivity were ineffective. For a subset of drugs, increasing the number of doses decreased efficacy. This phenomenon was unexpected because, when considering uptake into tissue, sustained plasma levels from multiple doses are generally assumed to be more effective. This counterintuitive decrease in efficacy was caused by drug retention within tumor tissue. These results established a set of rules that suggests how transport parameters affect the efficacy of drugs at different schedules. The two most predominant rules are (1) multiple doses improve efficacy for drugs with fast clearance, fast diffusivity and low to intermediate cell binding; and (2) one dose is most effective for drugs with slow clearance, slow diffusivity or strong cell binding. Understanding the role of tissue transport when determining drug treatment schedules would improve the outcome of preclinical animal experiments and early clinical trials.

Microfluidic Device to Quantify the Behavior of Therapeutic Bacteria in Three-Dimensional Tumor Tissue.

Microfluidic devices enable precise quantification of the interactions between anti-cancer bacteria and tumor tissue. Direct observation of bacterial movement and gene expression in tissue is difficult with either monolayers of cells or tumor-bearing mice. Quantification of these interactions is necessary to understand the inherent mechanisms of bacterial targeting and to develop modified organisms with enhanced therapeutic properties. Here we describe the procedures for designing, printing, and assembling microfluidic tumor-on-a-chip devices. We also describe the procedures for inserting three-dimensional tumor-cell masses, exposure to bacteria, and analyzing the resultant images.

Persistent enhancement of bacterial motility increases tumor penetration.

Motile bacteria can overcome the transport limitations that hinder many cancer therapies. Active bacteria can penetrate through tissue to deliver treatment to resistant tumor regions. Bacterial therapy has had limited success, however, because this motility is heterogeneous, and within a population many individuals are non-motile. In human trials, heterogeneity led to poor dispersion and incomplete tumor colonization. To address these problems, a swarm-plate selection method was developed to increase swimming velocity. Video microscopy was used to measure the velocity distribution of selected bacteria and a microfluidic tumor-on-a-chip device was used to measure penetration through tumor cell masses. Selection on swarm plates increased average velocity fourfold, from 4.9 to 18.7 µm/s (P < 0.05) and decreased the number of non-motile individuals from 51% to 3% (P < 0.05). The selected phenotype was both robust and stable. Repeating the selection process consistently increased velocity and eliminated non-motile individuals. When selected strains were cryopreserved and subcultured for 30.1 doublings, the high-motility phenotype was preserved. In the microfluidic device, selected Salmonella penetrated deeper into cell masses than unselected controls. By 10 h after inoculation, control bacteria accumulated in the front 30% of cell masses, closest to the flow channel. In contrast, selected Salmonella accumulated in the back 30% of cell masses, farthest from the channel. Selection increased the average penetration distance from 150 to 400 µm (P < 0.05). This technique provides a simple and rapid method to generate high-motility Salmonella that has increased penetration and potential for greater tumor dispersion and clinical efficacy.