Slow freezing process design for human induced pluripotent stem cells by modeling intracontainer variation

Computer-aided exploration of multiobjective optimal temperature profiles in slow freezing for human induced pluripotent stem cells

Human induced pluripotent stem (hiPS) cells have demonstrated promising potential in regenerative medical therapeutics. After successful clinical trials, the demand for hiPS cells has steadily increased. Therefore, the optimization of hiPS cell freezing processes for storage and transportation is essential. Here, we presented a computer-aided exploration of multiobjective optimal temperature profiles in slow freezing for hiPS cells. This study was based on a model that calculates cell survival rates after thawing, and the model was extended to evaluate cell potentials until 24 h after seeding. To estimate parameter values for this extension, freezing experiments were performed using constant cooling rates. Using quality and productivity indicators, we evaluated 16,206 temperature profiles using our model, and a promising profile was obtained. Finally, an experimental investigation of the profile was undertaken, and the contribution of the temperature profile to both quality and productivity was confirmed.

Crystallisation Degree Analysis during Cryopreservation of Biological Tissue Applying Interval Arithmetic

This paper presents the numerical modelling of heat transfer and changes proceeding in the homogeneous sample, caused by the crystallisation phenomenon during cryopreservation by vitrification. Heat transfer was simulated in a microfluidic system in which the working fluid flowed in micro-channels. The analysed process included single-phase flow during warming, and two-phase flow during cooling. In the model under consideration, interval parameters were assumed. The base of the mathematical model is given by the Fourier equation, with a heat source including the degree of ice crystallisation. The formulated problem has been solved using the interval version of the finite difference method, with the rules of the directed interval arithmetic. The fourth order Runge-Kutta algorithm has been applied to determine the degree of crystallisation. In the final part of this paper, examples of numerical computations are presented.

Improving Cell Recovery: Freezing and Thawing Optimization of Induced Pluripotent Stem Cells

Achieving good cell recovery after cryopreservation is an essential process when working with induced pluripotent stem cells (iPSC). Optimized freezing and thawing methods are required for good cell attachment and survival. In this review, we concentrate on these two aspects, freezing and thawing, but also discuss further factors influencing cell recovery such as cell storage and transport. Whenever a problem occurs during the thawing process of iPSC, it is initially not clear what it is caused by, because there are many factors involved that can contribute to insufficient cell recovery. Thawing problems can usually be solved more quickly when a certain order of steps to be taken is followed. Under optimized conditions, iPSC should be ready for further experiments approximately 4-7 days after thawing and seeding. However, if the freezing and thawing protocols are not optimized, this time can increase up to 2-3 weeks, complicating any further experiments. Here, we suggest optimization steps and troubleshooting options for the freezing, thawing, and seeding of iPSC on feeder-free, Matrigel™-coated, cell culture plates whenever iPSC cannot be recovered in sufficient quality. This review applies to two-dimensional (2D) monolayer cell culture and to iPSC, passaged, frozen, and thawed as cell aggregates (clumps). Furthermore, we discuss usually less well-described factors such as the cell growth phase before freezing and the prevention of osmotic shock during thawing.

Numerical Study of Heat and Mass Transfer during Cryopreservation Process with Application of Directed Interval Arithmetic

In the present paper, numerical modelling of heat and mass transfer proceeding in a two-dimensional axially symmetrical articular cartilage sample subjected to a cryopreservation process is presented. In the model under consideration, interval parameters were assumed. The heat transfer process is described using the Fourier interval equation, while the cryoprotectant transport (DMSO) across the cell membrane is analyzed using a two-parameter model taking into account the simulation of the water volume in the chondrocytes and the change in DMSO concentration over time. The liquidus tracking (LT) protocol introduced by Pegg et al. was used to model the cryopreservation process. This procedure divides the heating and cooling phases into eight and seven steps, respectively, allowing precise regulation of temperature and cryoprotectant (CPA) concentration of bathing solutions. This protocol protects chondrocytes from ice crystal, osmotic stress, and electrolyte damage. The obtained interval concentrations of cryoprotectant in chondrocytes were compared with previous simulations obtained using the deterministic model and they are mostly in agreement with the simulation data.

Computational screening of cryoprotective agents for regenerative medical products using quantum chemistry and molecular dynamics simulations

Cryoprotective agents (CPAs) are essential for the cryopreservation of cells. Thus far, dimethyl sulfoxide (DMSO) has been widely used as a CPA; however, DMSO is known to be toxic to cells. The damaged cells by the toxicity can present abnormal conditions, and should not be used for regenerative medical products because the cells/products are implanted directly into human bodies. With the aim of searching for an alternative CPA to DMSO, this work presents a computational screening of CPA candidate compounds using quantum chemistry and molecular dynamics (MD) simulations. Forty compounds were evaluated in regard to the solvation free energy and partition coefficient by quantum chemistry simulation and the root mean square deviation (RMSD) of a phospholipid bilayer which composes a cell membrane by MD simulation. The solvation free energy, partition coefficient, and RMSD were defined as indicators of osmoregulatory ability, affinity with a cell membrane, and ability to spread a cell membrane, respectively. The quantum chemistry simulation elucidated that the six compounds of trimethylglycine, formamide, urea, thiourea, diethylene glycol, and dulcitol were better than DMSO in either or both of the physical properties considered. This finding is based on the inherent physical property and is thus case-independent. Further characterization with the MD simulation suggested that formamide, thiourea, and urea should be the first candidates to investigate, although the result was valid only in the simulated condition. This work serves as the first step of multi-faceted computational evaluation of multiple compounds in the search for an effective CPA compound after DMSO.

Numerical Modeling of Heat and Mass Transfer during Cryopreservation Using Interval Analysis

In the paper, the numerical analysis of heat and mass transfer proceeding in an axially symmetrical articular cartilage sample subjected to the cryopreservation process is presented. In particular, a two-dimensional (axially symmetrical) model with imprecisely defined parameters is considered. The base of the heat transfer model is given by the interval Fourier equation and supplemented by initial boundary conditions. The phenomenon of cryoprotectant transport (Me2SO) through the extracellular matrix is described by the interval mass transfer equation. The liquidus-tracking (LT) method is used to control the temperature, which avoids the formation of ice regardless of the cooling and warming rates. In the LT process, the temperature decreases/increases gradually during addition/removal of the cryoprotectant, and the articular cartilage remains on or above the liquidus line so that no ice forms, independent of the cooling/warming rate. The discussed problem is solved using the interval finite difference method with the rules of directed interval arithmetic. Examples of numerical computations are presented in the final part of the paper. The obtained results of the numerical simulation are compared with the experimental results, realized for deterministically defined parameters.

Apoptosis-based method for determining lot sizes in the filling of human-induced pluripotent stem cells

Standardization in process design and operation is needed in the commercial production of human-induced pluripotent stem (hiPS) cells. Lot sizing in the filling of hiPS cells into containers, a part of the preservation process, also needs to be standardized because of the temporal changes in cell quality during the process. Here, we present an apoptosis-based method that can determine lot sizes in the filling of hiPS cells considering temporal changes in cell quality. Two indicators were developed for (i) the cell quality change using reactive oxygen species (ROS) measurement and (ii) the cell survival and probability of filling success, which are parts of the lot-sizing problem. Using computational simulation, a map out of the optimal lot size was produced that minimized the expected production costs at a given cell demand and an acceptable change in cell quality. At a filling temperature of 4°C, the largest possible lot size was calculated as 6 L (corresponding to a filling time of 125 min). The results of a sensitivity analysis recommended cold filling or the addition of an antioxidant. The presented method is effective to determine the lot size considering the change in cell quality during filling. The study uniquely combines the experimental results with mathematical modeling and computational simulation techniques. The map out of the optimal lot size could guide the development of industrial filling processes of hiPS cells.