Reproducing the human mucosal environment ex vivo

Abstract

The medical management of inflammatory bowel disease (IBD) remains problematic with a pressing need for innovation in drug development as well as delivery of personalized therapies. Both the disease's inherent pathophysiologic complexity and heterogeneity in its etiology conspire in making it difficult to accurately model for either the purposes of basic research or drug development. Multiple attempts at creating meaningful experimental models have fallen short of adequately recapitulating the disease and most do not capture any aspect of the cause or the effects of patient heterogeneity that underlays most of the difficulties faced by physicians and their patients. In vivo animal models, tissue culture systems, and more recent synthetic biology approaches are all too simplistically reductionist for the task. However, ex vivo culture platforms utilizing patient biopsies offer a system that more closely mimics end-stage disease processes that can be studied in detail and subjected to experimental manipulations. Recent studies describe further optimization of mucosal explant cultures in order to increase tissue viability and maintain a polarized epithelial layer. Current applications of the platform include studies of the interplay between the epithelial, immune and stromal compartment of the intestinal tissue, investigation of host-microbial interactions, preclinical evaluation of candidate drugs and uncovering mechanisms of action of established or emerging treatments for IBD. Patient explant-based assays offer an advanced biological system in IBD that recapitulates disease complexity and reflects the heterogeneity of the patient population. In its current stage of development, the system can be utilized for drug testing prior to the costlier and time-consuming evaluation by clinical trials. Further refinement of the technology and establishment of assay readouts that correlate with therapeutic outcomes will yield a powerful tool for personalized medicine approaches in which individual patient responses to available treatments are assessed a priori, thus reducing the need for trial and error within the clinical setting.