Application of microphysiological systems for nonclinical evaluation of cell therapies

Microphysiological systems (MPS) are gaining broader application in the pharmaceutical industry but have primarily been leveraged in early discovery toxicology and pharmacology studies with small molecules. The adoption of MPS offers a promising avenue to reduce animal use, improve in-vitro-to-in-vivo translation of pharmacokinetics/pharmacodynamics and toxicity correlation, and provide mechanistic understanding of model species suitability. While MPS have demonstrated utility in these areas with small molecules and biologics, MPS models in cell therapy development have not been fully explored, let alone validated. Distinguishing features of MPS, including long-term viability and physiologically relevant expression of functional enzymes, receptors, and pharmacological targets make them attractive tools for nonclinical characterization. However, there is currently limited published evidence of MPS being utilized to study the disposition, metabolism, pharmacology, and toxicity profiles of cell therapies. This review provides an industry perspective on the nonclinical application of MPS on cell therapies, first with a focus on oncology applications followed by examples in regenerative medicine.

Microphysiological systems (MPS) are advanced cell models, applied in the pharmaceutical industry to characterize novel therapies. While their application in studies of small molecule ther­apies has been very successful, the use of these models to study cell therapies has been limited. Cell therapies consist of cells and are living drugs, often with complex biological mechanisms of action, which can be very challenging to study. However, MPS have several features that make them attractive for studying cell therapies, including possibilities for longer-term studies and the ability to mimic physiologically relevant biological functions. MPS can mimic complex biological systems and processes, as such, the adoption of MPS offers a promising avenue to reduce the use of animals in the characterization of novel therapies. This review provides an industry perspective on current chal­lenges and highlights opportunities for using MPS in the development of cell therapies.

Distinct Patterns of Liver Chemistry Changes in Pediatric Acute Hepatitis of Unknown Origin and COVID-19 Patients: A Systematic Review.

In 2021 and 2022, there were noted to be clusters of pediatric acute hepatitis of unknown origin (AHUO) occurring across the globe. While there was not necessarily a global increase in cases, understanding the pattern of liver injury in AHUO is crucial to properly identify cases of this unexplained phenomenon, especially since it occurred simultaneously with a global resurgence of COVID-19. The objective of this study was to contrast the patterns in liver-relevant biochemical data from COVID-19 patients and AHUO. Studies reporting liver chemistries for cases of AHUO and COVID-19 were identified by a systematic review and search of the literature. For each case, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, direct bilirubin, and international normalized ratio (INR) levels were extracted as available. These were normalized to multiples of the upper limit of normal by patient age. There were statistically significant greater elevations of ALT and AST in patients with AHUO than in those with COVID-19. Only a subset of patients with COVID-19 had an AST or ALT greater than the normal range. INR elevation could be substantial for both conditions but was also statistically higher in the AHUO group. Liver chemistry changes were not statistically correlated with age. The pattern of liver chemistry changes between AHUO and COVID-19 have some distinctions, which suggests that AHUO is not a phenomenon driven primarily by SARS-CoV-2 infection alone. Differentiating AHUO and COVID-19 would be challenging based on patterns of liver chemistry changes alone.

The Influence of Talar Displacement on Articular Contact Mechanics: A 3D Finite Element Analysis Study Using Weightbearing Computed Tomography.

BACKGROUND: Talar displacement is considered the main predictive factor for poor outcomes and the development of post-traumatic osteoarthritis after ankle fractures. Isolated lateral talar translation, as previously studied by Ramsey and Hamilton using carbon powder imprinting, does not fully replicate the multidirectional joint subluxations seen in ankle fractures. The purpose of this study was to analyze the influence of multiple uniplanar talar displacements on tibiotalar contact mechanics utilizing weightbearing computed tomography (WBCT) and finite element analysis (FEA). METHODS: Nineteen subjects (mean age = 37.6 years) with no history of ankle surgery or injury having undergone WBCT arthrogram (n = 1) and WBCT without arthrogram (n = 18) were included. Segmentation of the WBCT images into 3D simulated models of bone and cartilage was performed. Three-dimensional (3D) multiple uniplanar talar displacements were simulated to investigate the respective influence of various uniaxial displacements (including lateral translation, anteroposterior translation, varus-valgus angulation, and external rotation) on the tibiotalar contact mechanics using FEA. Tibiotalar peak contact stress and contact area were modeled for each displacement and its gradations. RESULTS: Our modeling demonstrated that peak contact stress of the talus and tibia increased, whereas contact area decreased, with incremental displacement in all tested directions. Contact stress maps of the talus and tibia were computed for each displacement demonstrating unique patterns of pressure derangement. One millimeter of lateral translation resulted in 14% increase of peak talar contact pressure and a 3% decrease in contact area. CONCLUSION: Our model predicted that with lateral talar translation, there is less noticeable change in tibiotalar contact area compared with prior studies whereas external rotation greater than 12 degrees had the largest effect on peak contact stress predictions. LEVEL OF EVIDENCE: Level V, computational simulation study.