Simulation of ex vivo bone marrow culture: Application to chronic myeloid leukaemia growth model

Personalized Volumetric Tissue Generation by Enhancing Multiscale Mass Transport through 3D Printed Scaffolds in Perfused Bioreactors

Engineered tissues provide an alternative to graft material, circumventing the use of donor tissue such as autografts or allografts and non-physiological synthetic implants. However, their lack of vasculature limits the growth of volumetric tissue more than several millimeters thick which limits their success post-implantation. Perfused bioreactors enhance nutrient mass transport inside lab-grown tissue but remain poorly customizable to support the culture of personalized implants. Here, a multiscale framework of computational fluid dynamics (CFD), additive manufacturing, and a perfusion bioreactor system are presented to engineer personalized volumetric tissue in the laboratory. First, microscale 3D printed scaffold pore geometries are designed and 3D printed to characterize media perfusion through CFD and experimental fluid testing rigs. Then, perfusion bioreactors are custom-designed to combine 3D printed scaffolds with flow-focusing inserts in patient-specific shapes as simulated using macroscale CFD. Finally, these computationally optimized bioreactor-scaffold assemblies are additively manufactured and cultured with pre-osteoblast cells for 7, 20, and 24 days to achieve tissue growth in the shape of human calcaneus bones of 13 mL volume and 1 cm thickness. This framework enables an intelligent model-based design of 3D printed scaffolds and perfusion bioreactors which enhances nutrient transport for long-term volumetric tissue growth in personalized implant shapes. The novel methods described here are readily applicable for use with different cell types, biomaterials, and scaffold microstructures to research therapeutic solutions for a wide range of tissues.

Modeling the impact of fluid flow on resveratrol release from electrospun fibers

Using electrospun fibers to deliver therapeutic agents has gained significant attention in various applications including cancer treatment and tissue regeneration. However, the effect of fluid flow and uptake by cells on the concentration profile is not well understood. In this study, we evaluated the release of lipophilic resveratrol from poly(ε-caprolactone) (PCL)-gelatin (GT) electrospun fibers experimentally and by using computational fluid dynamics (CFD). Resveratrol containing PCL-GT electrospun fibers were formed and used in a custom-built tubular bioreactor, to assess flow effect on concentration profile over 5 days. CFD model was developed to simulate release in both static cultures and under fluid flow conditions. Resveratrol stability in the culture medium and uptake by human umbilical vein endothelial cells and K562 cells over 3 days were used in the model. The concentration profile as a function of time was simulated and validated by experiments. The effects of inlet velocity, cellular uptake rate, bioreactor's length, and surrounding tissue porosity were assessed. The release profile was mainly affected by cellular uptake and the presence of porous media. The model suggests that the perfusion velocity might not have a significant effect relative to the cellular uptake rate and porosity of the surrounding tissue.

Stem cell biomanufacturing under uncertainty: A case study in optimizing red blood cell production

As breakthrough cellular therapy discoveries are translated into reliable, commercializable applications, effective stem cell biomanufacturing requires systematically developing and optimizing bioprocess design and operation. This article proposes a rigorous computational framework for stem cell biomanufacturing under uncertainty. Our mathematical tool kit incorporates: high‐fidelity modeling, single variate and multivariate sensitivity analysis, global topological superstructure optimization, and robust optimization. The advantages of the proposed bioprocess optimization framework using, as a case study, a dual hollow fiber bioreactor producing red blood cells from progenitor cells were quantitatively demonstrated. The optimization phase reduces the cost by a factor of 4, and the price of insuring process performance against uncertainty is approximately 15% over the nominal optimal solution. Mathematical modeling and optimization can guide decision making; the possible commercial impact of this cellular therapy using the disruptive technology paradigm was quantitatively evaluated. © 2017 American Institute of Chemical Engineers AIChE J, 64: 3011–3022, 2018

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design.

Towards unravelling the kinetics of an acute myeloid leukaemia model system under oxidative and starvation stress: a comparison between two- and three-dimensional cultures

A great challenge when conducting ex vivo studies of leukaemia is the construction of an appropriate experimental platform that would recapitulate the bone marrow (BM) environment. Such a 3D scaffold system has been previously developed in our group [1]. Additionally to the BM architectural characteristics, parameters such as oxygen and glucose concentration are crucial as their value could differ between patients as well as within the same patient at different stages of treatment, consequently affecting the resistance of leukaemia to chemotherapy. The effect of oxidative and glucose stress-at levels close to human physiologic ones-on the proliferation and metabolic evolution of an AML model system (K-562 cell line) in conventional 2D cultures as well as in 3D scaffolds were studied. We observed that the K-562 cell line can proliferate and remain alive for 2 weeks in medium with glucose close to physiological levels both in 20 and 5% O2. We report interesting differences on the cellular response to the environmental, i.e., oxidative and/or nutritional stress stimuli in 2D and 3D. Higher adaptation to oxidative stress under non-starving conditions is observed in the 3D system. The glucose level in the medium has more impact on the cellular proliferation in the 3D compared to the 2D system. These differences can be of significant importance both when applying chemotherapy in vitro and also when constructing mathematical tools for optimisation of disease treatment.