Fluid Dynamic Modeling to Support the Development of Flow-Based Hepatocyte Culture Systems for Metabolism Studies

A review of complex in vitro cell culture stressing the importance of fluid flow and illustrated by organ on a chip liver models

The translation of new technology from development into widespread commercial use is a complex and time-consuming process that requires significant investment. This review looks at some important market needs for more complex in vitro models, the technical difficulties that must be overcome, particularly those connected with introducing fluid flow using microfluidics, and also illustrates the economic benefits of more accurate models for drug toxicity. Beyond the strong ethical arguments for replacing the use of animals in drug safety testing and medical research, the author believes that financial benefits of adopting the new in vitro technology are becoming clear and will drive the adoption by industry.

Design considerations of benchtop fluid flow bioreactors for bio-engineered tissue equivalents in vitro

One of the major aims of bio-engineering tissue equivalents in vitro is to create physiologically relevant culture conditions to accurately recreate the cellular microenvironment. This often includes incorporation of factors such as the extracellular matrix, co-culture of multiple cell types and three-dimensional culture techniques. These advanced techniques can recapitulate some of the properties of tissue in vivo, however fluid flow is a key aspect that is often absent. Fluid flow can be introduced into cell and tissue culture using bioreactors, which are becoming increasingly common as we seek to produce increasingly accurate tissue models. Bespoke technology is continuously being developed to tailor systems for specific applications and to allow compatibility with a range of culture techniques. For effective perfusion of a tissue culture many parameters can be controlled, ranging from impacts of the fluid flow such as increased shear stress and mass transport, to potentially unwanted side effects such as temperature fluctuations. A thorough understanding of these properties and their implications on the culture model can aid with a more accurate interpretation of results. Improved and more complete characterisation of bioreactor properties will also lead to greater accuracy when reporting culture conditions in protocols, aiding experimental reproducibility, and allowing more precise comparison of results between different systems. In this review we provide an analysis of the different factors involved in the development of benchtop flow bioreactors and their potential biological impacts across a range of applications.

In Vitro–In Silico Modeling of Caffeine and Diclofenac Permeation in Static and Fluidic Systems with a 16HBE Lung Cell Barrier

Static in vitro permeation experiments are commonly used to gain insights into the permeation properties of drug substances but exhibit limitations due to missing physiologic cell stimuli. Thus, fluidic systems integrating stimuli, such as physicochemical fluxes, have been developed. However, as fluidic in vitro studies display higher complexity compared to static systems, analysis of experimental readouts is challenging. Here, the integration of in silico tools holds the potential to evaluate fluidic experiments and to investigate specific simulation scenarios. This study aimed to develop in silico models that describe and predict the permeation and disposition of two model substances in a static and fluidic in vitro system. For this, in vitro permeation studies with a 16HBE cellular barrier under both static and fluidic conditions were performed over 72 h. In silico models were implemented and employed to describe and predict concentration–time profiles of caffeine and diclofenac in various experimental setups. For both substances, in silico modeling identified reduced apparent permeabilities in the fluidic compared to the static cellular setting. The developed in vitro–in silico modeling framework can be expanded further, integrating additional cell tissues in the fluidic system, and can be employed in future studies to model pharmacokinetic and pharmacodynamic drug behavior.

Towards the Experimentally-Informed In Silico Nozzle Design Optimization for Extrusion-Based Bioprinting of Shear-Thinning Hydrogels

Research in bioprinting is booming due to its potential in addressing several manufacturing challenges in regenerative medicine. However, there are still many hurdles to overcome to guarantee cell survival and good printability. For the 3D extrusion-based bioprinting, cell viability is amongst one of the lowest of all the bioprinting techniques and is strongly influenced by various factors including the shear stress in the print nozzle. The goal of this study is to quantify, by means of in silico modeling, the mechanical environment experienced by the bioink during the printing process. Two ubiquitous nozzle shapes, conical and blunted, were considered, as well as three common hydrogels with material properties spanning from almost Newtonian to highly shear-thinning materials following the power-law behavior: Alginate-Gelatin, Alginate and PF127. Comprehensive in silico testing of all combinations of nozzle geometry variations and hydrogels was achieved by combining a design of experiments approach (DoE) with a computational fluid dynamics (CFD) of the printing process, analyzed through a machine learning approach named Gaussian Process. Available experimental results were used to validate the CFD model and justify the use of shear stress as a surrogate for cell survival in this study. The lower and middle nozzle radius, lower nozzle length and the material properties, alone and combined, were identified as the major influencing factors affecting shear stress, and therefore cell viability, during printing. These results were successfully compared with those of reported experiments testing viability for different nozzle geometry parameters under constant flow rate or constant pressure. The in silico 3D bioprinting platform developed in this study offers the potential to assist and accelerate further development of 3D bioprinting.

Mechanical Stimulation: A Crucial Element of Organ-on-Chip Models

Organ-on-chip (OOC) systems recapitulate key biological processes and responses in vitro exhibited by cells, tissues, and organs in vivo. Accordingly, these models of both health and disease hold great promise for improving fundamental research, drug development, personalized medicine, and testing of pharmaceuticals, food substances, pollutants etc. Cells within the body are exposed to biomechanical stimuli, the nature of which is tissue specific and may change with disease or injury. These biomechanical stimuli regulate cell behavior and can amplify, annul, or even reverse the response to a given biochemical cue or drug candidate. As such, the application of an appropriate physiological or pathological biomechanical environment is essential for the successful recapitulation of in vivo behavior in OOC models. Here we review the current range of commercially available OOC platforms which incorporate active biomechanical stimulation. We highlight recent findings demonstrating the importance of including mechanical stimuli in models used for drug development and outline emerging factors which regulate the cellular response to the biomechanical environment. We explore the incorporation of mechanical stimuli in different organ models and identify areas where further research and development is required. Challenges associated with the integration of mechanics alongside other OOC requirements including scaling to increase throughput and diagnostic imaging are discussed. In summary, compelling evidence demonstrates that the incorporation of biomechanical stimuli in these OOC or microphysiological systems is key to fully replicating in vivo physiology in health and disease.

Small-Scale Fluidized Bed Bioreactor for Long-Term Dynamic Culture of 3D Cell Constructs and in vitro Testing

With the increasing interest in three-dimensional (3D) cell constructs that better represent native tissues, comes the need to also invest in devices, i.e., bioreactors, that provide a controlled dynamic environment similar to the perfusion mechanism observed in vivo. Here a laboratory-scale fluidized bed bioreactor (sFBB) was designed for hydrogel (i.e., alginate) encapsulated cells to generate a dynamic culture system that produced a homogenous milieu and host substantial biomass for long-term evolution of tissue-like structures and “per cell” performance analysis. The bioreactor design, conceptualized through scale-down empirical similarity rules, was initially validated through computational fluid dynamics analysis for the distributor capacity of homogenously dispersing the flow with an average fluid velocity of 4.596 × 10^–4 m/s. Experimental tests then demonstrated a consistent fluidization of hydrogel spheres, while maintaining shape and integrity (606.9 ± 99.3 μm diameter and 0.96 shape factor). It also induced mass transfer in and out of the hydrogel at a faster rate than static conditions. Finally, the sFBB sustained culture of alginate encapsulated hepatoblastoma cells for 12 days promoting proliferation into highly viable (>97%) cell spheroids at a high final density of 27.3 ± 0.78 million cells/mL beads. This was reproducible across multiple units set up in parallel and operating simultaneously. The sFBB prototype constitutes a simple and robust tool to generate 3D cell constructs, expandable into a multi-unit setup for simultaneous observations and for future development and biological evaluation of in vitro tissue models and their responses to different agents, increasing the complexity and speed of R&D processes.

Inlet flow rate of perfusion bioreactors affects fluid flow dynamics, but not oxygen concentration in 3D-printed scaffolds for bone tissue engineering: Computational analysis and experimental validation

Fluid flow dynamics and oxygen-concentration in 3D-printed scaffolds within perfusion bioreactors are sensitive to controllable bioreactor parameters such as inlet flow rate. Here we aimed to determine fluid flow dynamics, oxygen-concentration, and cell proliferation and distribution in 3D-printed scaffolds as a result of different inlet flow rates of perfusion bioreactors using experiments and finite element modeling. Pre-osteoblasts were treated with 1 h pulsating fluid flow with low (0.8 Pa; PFF^low) or high peak shear stress (6.5 Pa; PFF^high), and nitric oxide (NO) production was measured to validate shear stress sensitivity. Computational analysis was performed to determine fluid flow between 3D-scaffold-strands at three inlet flow rates (0.02, 0.1, 0.5 ml/min) during 5 days. MC3T3-E1 pre-osteoblast proliferation, matrix production, and oxygen-consumption in response to fluid flow in 3D-printed scaffolds inside a perfusion bioreactor were experimentally assessed. PFF^high more strongly stimulated NO production by pre-osteoblasts than PFF^low. 3D-simulation demonstrated that dependent on inlet flow rate, fluid velocity reached a maximum (50-1200 μm/s) between scaffold-strands, and fluid shear stress (0.5-4 mPa) and wall shear stress (0.5-20 mPa) on scaffold-strands surfaces. At all inlet flow rates, gauge fluid pressure and oxygen-concentration were similar. The simulated cell proliferation and distribution, and oxygen-concentration data were in good agreement with the experimental results. In conclusion, varying a perfusion bioreactor's inlet flow rate locally affects fluid velocity, fluid shear stress, and wall shear stress inside 3D-printed scaffolds, but not gauge fluid pressure, and oxygen-concentration, which seems crucial for optimized bone tissue engineering strategies using bioreactors, scaffolds, and cells.

Mathematical modelling of fluid flow and solute transport to define operating parameters for in vitro perfusion cell culture systems

In recent years, there has been a move away from the use of static in vitro two-dimensional cell culture models for testing the chemical safety and efficacy of drugs. Such models are increasingly being replaced by more physiologically relevant cell culture systems featuring dynamic flow and/or three-dimensional structures of cells. While it is acknowledged that such systems provide a more realistic environment within which to test drugs, progress is being hindered by a lack of understanding of the physical and chemical environment that the cells are exposed to. Mathematical and computational modelling may be exploited in this regard to unravel the dependency of the cell response on spatio-temporal differences in chemical and mechanical cues, thereby assisting with the understanding and design of these systems. In this paper, we present a mathematical modelling framework that characterizes the fluid flow and solute transport in perfusion bioreactors featuring an inlet and an outlet. To demonstrate the utility of our model, we simulated the fluid dynamics and solute concentration profiles for a variety of different flow rates, inlet solute concentrations and cell types within a specific commercial bioreactor chamber. Our subsequent analysis has elucidated the basic relationship between inlet flow rate and cell surface flow speed, shear stress and solute concentrations, allowing us to derive simple but useful relationships that enable prediction of the behaviour of the system under a variety of experimental conditions, prior to experimentation. We describe how the model may used by experimentalists to define operating parameters for their particular perfusion cell culture systems and highlight some operating conditions that should be avoided. Finally, we critically comment on the limitations of mathematical and computational modelling in this field, and the challenges associated with the adoption of such methods.

Liver Bioreactor Design Issues of Fluid Flow and Zonation, Fibrosis, and Mechanics: A Computational Perspective

Tissue engineering, with the goal of repairing or replacing damaged tissue and organs, has continued to make dramatic science-based advances since its origins in the late 1980’s and early 1990’s. Such advances are always multi-disciplinary in nature, from basic biology and chemistry through physics and mathematics to various engineering and computer fields. This review will focus its attention on two topics critical for tissue engineering liver development: (a) fluid flow, zonation, and drug screening, and (b) biomechanics, tissue stiffness, and fibrosis, all within the context of 3D structures. First, a general overview of various bioreactor designs developed to investigate fluid transport and tissue biomechanics is given. This includes a mention of computational fluid dynamic methods used to optimize and validate these designs. Thereafter, the perspective provided by computer simulations of flow, reactive transport, and biomechanics responses at the scale of the liver lobule and liver tissue is outlined, in addition to how bioreactor-measured properties can be utilized in these models. Here, the fundamental issues of tortuosity and upscaling are highlighted, as well as the role of disease and fibrosis in these issues. Some idealized simulations of the effects of fibrosis on lobule drug transport and mechanics responses are provided to further illustrate these concepts. This review concludes with an outline of some practical applications of tissue engineering advances and how efficient computational upscaling techniques, such as dual continuum modeling, might be used to quantify the transition of bioreactor results to the full liver scale.

The role of fit-for-purpose assays within tiered testing approaches: A case study evaluating prioritized estrogen-active compounds in an in vitro human uterotrophic assay

Chemical risk assessment relies on toxicity tests that require significant numbers of animals, time and costs. For the >30,000 chemicals in commerce, the current scale of animal testing is insufficient to address chemical safety concerns as regulatory and product stewardship considerations evolve to require more comprehensive understanding of potential biological effects, conditions of use, and associated exposures. We demonstrate the use of a multi-level new approach methodology (NAMs) strategy for hazard- and risk-based prioritization to reduce animal testing. A Level 1/2 chemical prioritization based on estrogen receptor (ER) activity and metabolic activation using ToxCast data was used to select 112 chemicals for testing in a Level 3 human uterine cell estrogen response assay (IKA assay). The Level 3 data were coupled with quantitative in vitro to in vivo extrapolation (Q-IVIVE) to support bioactivity determination (as a surrogate for hazard) in a tissue-specific context. Assay AC₅₀s and Q-IVIVE were used to estimate human equivalent doses (HEDs), and HEDs were compared to rodent uterotrophic assay in vivo-derived points of departure (PODs). For substances active both in vitro and in vivo, IKA assay-derived HEDs were lower or equivalent to in vivo PODs for 19/23 compounds (83%). Activity exposure relationships were calculated, and the IKA assay was as or more protective of human health than the rodent uterotrophic assay for all IKA-positive compounds. This study demonstrates the utility of biologically relevant fit-for-purpose assays and supports the use of a multi-level strategy for chemical risk assessment.

Exploring donor demographics effects on hepatocyte yield and viability: Results of whole human liver isolation from one center

Due to the growth of cell-based therapeutic alternatives addressing the shortage of livers for transplant, there is necessity for a reliable source of human hepatocytes. In addition, pharmaceutical research often requires human hepatocytes to assess new drug therapies during development or to achieve FDA approval. Whole human livers producing large quantities of cells from the same donor are ideal, enhancing reproducibility for all purposes, while also allowing for capturing variances in drug-metabolism across different demographics for pharmaceutical testing and development but are limited in availability and quality for research purposes. The present study investigates the effect of donor and liver procurement factors of 16 human livers on cell viability and yield, showing that typical exclusion criteria for transplant still produce viable hepatocytes with significant yields. Although limited in number of data points, which should be taken into consideration, the conclusions of this study could be utilized as indications, allowing for expansion of liver selection criteria for hepatocyte isolation and provide the necessary quality hepatocytes in large quantities for the growing pharmaceutical, biomedical, and therapeutic research fields.

A novel dynamic multicellular co-culture system for studying individual blood-brain barrier cell types in brain diseases and cytotoxicity testing

Blood brain barrier (BBB) cells play key roles in the physiology and pathology of the central nervous system (CNS). BBB dysfunction is implicated in many neurodegenerative diseases, including Alzheimer’s disease (AD). The BBB consists of capillary endothelial cells, pericytes encircling the endothelium and surrounding astrocytes extending their processes towards it. Although there have been many attempts to develop in vitro BBB models, the complex interaction between these cell types makes it extremely difficult to determine their individual contribution to neurotoxicity in vivo. Thus, we developed and optimised an in vitro multicellular co-culture model within the Kirkstall Quasi Vivo System. The main aim was to determine the optimal environment to culture human brain primary endothelial cells, pericytes and astrocytes whilst maintaining cellular communication without formation of a barrier in order to assess the contribution of each cell type to the overall response. As a proof of concept for the present system, the effects of amyloid-beta 25-35 peptide (Aβ25-35), a hallmark of AD, were explored. This multicellular system will be a valuable tool for future studies on the specific roles of individual BBB cell type (while making connection with each other through medium) in CNS disorders as well as in cytotoxicity tests.

Hepatocyte CYP2B6 Can Be Expressed in Cell Culture Systems by Exerting Physiological Levels of Shear: Implications for ADME Testing

Cytochrome 2B6 (CYP2B6) has substantial clinical effects on morbidity and mortality and its effects on drug metabolism should be part of hepatotoxicity screening. Examples of CYP2B6's impacts include its linkage to mortality during cyclophosphamide therapy and its role in determining hepatotoxicity and CNS toxicity during efavirenz therapy for HIV infection. CYP2B6 is key to metabolism of many common drugs from opioids to antidepressants, anesthetics, and anticonvulsants. But CYP2B6 has been extremely difficult to express in cell culture, and as a result, it has been largely deemphasized in preclinical toxicity studies. It has now been shown that CYP2B6 expression can be supported for extended periods of time using suspension culture techniques that exert physiological levels of shear. New understanding of CYP2B6 has identified five clinically significant genetic polymorphisms that have a high incidence in many populations and that convey a substantial dynamic range of activity. We propose that, with the use of culture devices exerting physiological shear levels, CYP2B6 dependent drug testing, including definition of polymorphisms and application of specific inhibitors, should be a standard part of preclinical absorption, distribution, metabolism, and excretion (ADME) testing.

Drug discovery strategies in the field of tumor energy metabolism: Limitations by metabolic flexibility and metabolic resistance to chemotherapy

The search for new drugs capable of blocking the metabolic vulnerabilities of human tumors has now entered the clinical evaluation stage, but several projects already failed in phase I or phase II. In particular, very promising in vitro studies could not be translated in vivo at preclinical stage and beyond. This was the case for most glycolysis inhibitors that demonstrated systemic toxicity. A more recent example is the inhibition of glutamine catabolism in lung adenocarcinoma that failed in vivo despite a strong addiction of several cancer cell lines to glutamine in vitro. Such contradictory findings raised several questions concerning the optimization of drug discovery strategies in the field of cancer metabolism. For instance, the cell culture models in 2D or 3D might already show strong limitations to mimic the tumor micro- and macro-environment. The microenvironment of tumors is composed of cancer cells of variegated metabolic profiles, supporting local metabolic exchanges and symbiosis, but also of immune cells and stroma that further interact with and reshape cancer cell metabolism. The macroenvironment includes the different tissues of the organism, capable of exchanging signals and fueling the tumor 'a distance'. Moreover, most metabolic targets were identified from their increased expression in tumor transcriptomic studies, or from targeted analyses looking at the metabolic impact of particular oncogenes or tumor suppressors on selected metabolic pathways. Still, very few targets were identified from in vivo analyses of tumor metabolism in patients because such studies are difficult and adequate imaging methods are only currently being developed for that purpose. For instance, perfusion of patients with [¹³C]-glucose allows deciphering the metabolomics of tumors and opens a new area in the search for effective targets. Metabolic imaging with positron emission tomography and other techniques that do not involve [¹³C] can also be used to evaluate tumor metabolism and to follow the efficiency of a treatment at a preclinical or clinical stage. Relevant descriptors of tumor metabolism are now required to better stratify patients for the development of personalized metabolic medicine. In this review, we discuss the current limitations in basic research and drug discovery in the field of cancer metabolism to foster the need for more clinically relevant target identification and validation. We discuss the design of adapted drug screening assays and compound efficacy evaluation methods for the discovery of innovative anti-cancer therapeutic approaches at the level of tumor energetics. This article is part of a Special Issue entitled Mitochondria in Cancer, edited by Giuseppe Gasparre, Rodrigue Rossignol and Pierre Sonveaux.