Marc D. Donohue

The majority of therapeutic monoclonal antibodies (mAbs) on the market are produced using Chinese Hamster Ovary (CHO) cells cultured at scale in chemically defined cell culture medium. Because of the high costs associated with mammalian cell cultures, obtaining high cell densities to produce high product titers is desired. These bioprocesses require high concentrations of nutrients in the basal media and periodically adding concentrated feed media to sustain cell growth and therapeutic protein productivity. Unfortunately, the desired or optimal nutrient concentrations of the feed media are often solubility limited due to precipitation of chemical complexes that form in the solution. Experimentally screening the various cell culture media configurations which contain 50 to 100 compounds can be expensive and laborious. This article lays the foundation for utilizing computational tools to understand precipitation of nutrients in cell culture media by studying the pairwise interactions between amino acids in thermodynamic models. Activity coefficient data for one amino acid in water and amino acid solubility data of two amino acids in water have been used to determine a single set of UNIFAC group interaction parameters to predict the thermodynamic behavior of the multi-component systems found in mammalian cell culture media. The data collected in this study is, to our knowledge, the largest set of ternary system amino acid solubility data reported to date. These amino acid precipitation predictions have been verified with experimentally measured ternary and quaternary amino acid solutions. Thus, we demonstrate the utility of our model as a digital twin to identify optimal cell culture media compositions by replacing empirical approaches for nutrient precipitation with computational predictions based on thermodynamics of individual media components in complex mixtures.

During the SARS-CoV-2 pandemic, a need for methods to decontaminate and reuse personal protective equipment (PPE) and medical plastics became a priority. In this investigation we aimed to develop a contamination evaluation protocol for laboratory pipette tips, after decontamination. Decontamination methods tested in this study included cleaning with a common laboratory detergent (2.5% Alconox® solution followed with steam decontamination), exposure of ozone vapor at 250 and 14400 PPM * minute, and exposure to cold atmospheric plasma (CAP). All tips (control and experimental groups) were introduced to the methods described, while tips exposed to DNA extracts of Aeromonas hydrophila (ATCC-23211) were assessed for experimental groups. Decontamination was determined by turnover ratio and log reduction in detectable genomic material on the contaminated products using real-time quantitative PCR (qPCR) assay. Our results showed, cleaning tips with lab detergents along with steam decontamination removed genetic material, resulting in the highest log reduction, compared with ozone or CAP treatments. Detergent/washing methods showed the second highest turnover ratio (95.9%) and log reduction (5.943). However, the excessive residue (post- cleaning) on the plastic, within inner filters, and tip boxes suggested that washing with lab detergents was not favorable for reuse. Ozone vapor at 14400 PPM * minute showed the highest turnover ratio (98.4%) and log reduction (4.511). CAP exposure with tips inverted (the tip end exposed closer to the plasma flame) for 1 minute showed a turnover ratio of (68.3%) and log reduction (4.002). Relatively, lower turnover ratio and log reduction of CAP could be improved by optimization, such as increasing the exposure time. Future testing would provide fine-tuned conditions for CAP-specific decontamination of plasticware. In this study we were able to provide fundamental insight into a non-traditional decontamination method for single-use plasticware that could render these products reusable.

This project determined the effect of adsorption compression on the rates of catalytic chemical reactions. It was shown that in regions of strong adsorption compression there is a dramatic increase in the rate of catalytic chemical reaction. Experiments focused on the conversion of NO to molecular nitrogen and oxygen. Data analysis techniques were developed to allow interpretation of experimental data and prediction of conditions for optimal reaction rates.

In this paper, supercritical data has been evaluated and shown to demonstrate adsorption compression. Ono-Kondo analysis of adsorption isotherms for supercritical systems (including nitrogen, methane, and carbon dioxide on activated carbon Filtrasorb 400 and on zeolite 13X) indicates adsorption compression phenomenon at high pressure end just as in subcritical systems. Experimental isotherms for adsorption of supercritical fluids are plotted in Ono-Kondo coordinates with the Henry’s constant estimated based on results of modeling as well as calorimetric and chromatographic measurements. The linear sections of the results show the range of applicability of the classical Ono-Kondo model with constant energies of interactions. The slopes of these linear sections represent values and signs of these energies: negative slopes indicate repulsive interactions in adsorbed phase due to adsorption compression. Switching interactions from attractive to repulsive with an increase in the pressure for supercritical adsorption suggests that adsorbed phase has two regions. One is an attractive region at low-pressures and the other is a repulsive region at high pressures. It can be indicated that the shape of isotherms in Ono-Kondo coordinates can help to understand adsorbate-adsorbate energies; the slope of the line in Ono-Kondo coordinates gives the sign and magnitude of the energy as a function of adsorbate density.

In previous work, lattice density functional theory equations have been recast into differential form to determine a property whose gradient is universally proportional to the diffusive flux. For color counter diffusion, this property appears as the impingement rate onto vacancies and molecules of a species whose density gradient can be influenced by diffusion. Therefore, the impingement rate of a diffusing molecule depends on the mobility of its surroundings. In order to determine the validity of this finding, molecular dynamics simulations of color counter diffusion were performed in which the mobility of the solvent was varied to determine if the flux of the diffusing species responded to the change when all other factors, such as density gradient, available volume, and temperature are held constant.

An analysis of classical approximations is performed for diffusion in fluids with density gradients. This approach gives a new diffusion equation taking into account the asymmetry of molecular mean-free paths and the velocity distribution in the flux term. It is shown that new model is consistent with Einstein's evolution equation for an asymmetric distribution of spatial displacements and with molecular dynamic simulations for hard spheres.

Hard sphere molecular dynamics simulations are used to study the mean free path of molecules traveling down a density gradient at fluid densities ranging between 0.05σ−3 and 0.7σ−3. Gradients are developed using semipermeable boundaries in the x-direction and, as a result, a net flow develops in the positive x-direction. Over the course of the simulation, the free paths of colliding molecules are calculated and it was determined that the mean free path in the positive x-direction is greater than the mean free path in the negative x-direction at each density studied. These results are compared to the mean free paths in the positive and negative y- and z-directions (in which there is no net flow) and the distribution of free paths for molecules traveling in the positive and negative x-directions gives insight into the physics of the system. In addition, the dependency of the mean free path on speed is studied and compared to kinetic theory predictions. The results have application in the modification of the classical model of diffusion for low density systems undergoing flow in which the mean free path is finite, large, and can be anisotropic.

Four types of systems with different degrees of geometric constraint and intermolecular correlations were studied to determine the differences in their thermodynamics. The average configurational internal energies of these systems were calculated using Monte Carlo simulations, and the results are compared at the same temperatures and constant average bulk density. From the energy profiles for the four systems, the effects of geometry and intermolecular correlations on the systems' phase behavior are discussed. It was observed that indirect intermolecular correlations, rather than geometric constraints, are the key to achieving a first-order phase transition.