Fluxomics: The integration of metabolic flux analysis (MFA) with multivariate data analysis (MVDA) to identify key process parameters for CHO cell culture

An integrated 13C-metabolic flux analysis (MFA)/fluxomics approach was conducted to characterize fed-batch, concentrated fed-batch, and perfusion modes of operation. While both the concentrated fed-batch and perfusion processes were independently represented by one metabolic quasi-steady-state, fed-batch metabolism was characterized by multiple. Intracellular flux maps were developed for all three operational modes. To elucidate the phenotype of peak specific productivity, the stationary phase of fed-batch was characterized by 13C-MFA. The metabolic network included glycolysis, the pentose-phosphate pathway, citric acid cycle, and various anaplerotic reactions. Anabolic demands for biomass, host cell protein (HCP), and IgG were accounted for. To identify potential rate limitations and catabolic metabolite contributions, a stoichiometric model was created, considering the aforementioned anabolic demands relative to the observed specific consumption rates. Additionally, to foster a more holistic understanding of fed-batch, specific consumption/production rates were determined for all phases of fed-batch, from inoculation to harvest. Multiple feeding strategies, inoculation densities, and CHO cell lines were evaluated for the fed-batch process. Incorporating the intracellular flux networks from all three operational modes, multivariate data analysis (MVDA) was then employed to statistically determine the correlation of metabolic fluxes with final titer/specific productivity. For fed-batch, fluxes with temporal resolution were included. Interestingly, some of the best predictors of final titer (top 5% among all variables) were fluxes measured in the first two days of culture. One such example was specific productivity, a variable generally not considered at such an early stage. Conversely, specific lactate production over the first two days of culture, while typically at its maximum, hardly correlated (positively or negatively) with final titer at all. We will discuss the impact of using fluxomics, made possible through the integration of MVDA with MFA, to assess and identify key process parameters for antibody production

Reversible Masking Using Low-Molecular-Weight Neutral Lipids to Achieve Optimal-Targeted Delivery

Intravenous injection of therapeutics is required to effectively treat or cure metastatic cancer, certain cardiovascular diseases, and other acquired or inherited diseases. Using this route of delivery allows potential uptake in all disease targets that are accessed by the bloodstream. However, normal tissues and organs also have the potential for uptake of therapeutic agents. Therefore, investigators have used targeted delivery to attempt delivery solely to the target cells; however, use of ligands on the surface of delivery vehicles to target specific cell surface receptors is not sufficient to avoid nonspecific uptake. PEGylation has been used for decades to try to avoid nonspecific uptake but suffers from many problems known as “The PEGylation Dilemma.” We have solved this dilemma by replacing PEGylation with reversible masking using low-molecular-weight neutral lipids in order to achieve optimal-targeted delivery solely to target cells. Our paper will focus on this topic

Application of metabolomics and fluxomics to increase productivity and predict product quality

Process development is routinely performed at different scales, amongst different clones, and with different optimization goals. In this work, we examine how these variables impact and relate to cell metabolism in fed-batch process, with the goal of increasing productivity and tuning product quality. Three unique CHO clones producing different IgGs were evaluated at the 250mL, 2L, and 500L scales. The impact on cell metabolism from clonal variation, reactor designs, and batch time was quantified in this work. Likewise, metabolism in turn influences final product titers and product quality profiles. To comprehensively understand this influence, over 500 extracellular metabolite time-course profiles were considered by empirical modeling, including principal component analysis (PCA) and orthogonal partial least squares (OPLS) models. Through empirical modeling, we examined the impact of metabolism on final titer. With the objective of increasing final titer, the model identified a cluster of six metabolites (out of 500+) with a shared pathway at the interface of amino acid and glycerophospholipid metabolism. The expression of these clustered metabolites correlated strongly with final product titer at multiple stages of the fed-batch run. In addition to these findings, we will share how metabolism correlated with product quality. As development batches often have different initial cell densities and growth kinetics, we also converted all supernatant metabolite expression profiles into specific consumption rates. This enabled a less biased and more straightforward comparison between batches. Likewise, a unique model comparison was enabled, one based upon metabolite concentrations (metabolomics) and one based upon metabolite fluxes (fluxomics). Both will be presented at this conference

Maximizing viral titer yield at harvest through metabolic process analytical technology (PAT)

This work pertains to the optimization of enterovirus production using MRC5 cultured on microcarriers within a bioreactor. This enterovirus, like other lytic viruses, has a rapid decay rate within a production batch, such that a 30% loss of potency is observed per day. Therefore, to maximize the yield of infectious product from the bioreactor, harvest needs to be timed to maximize the amount of viral production while minimizing the decay. Viral potency assays have slow turnaround times relative to a production batch, making an online process analytical technology (PAT) critical to maximize titers. In pursuit of an online method for tracking viral titer, three different PAT-enabled streams were investigated: dissolved oxygen (DO), viable cell volume (VCV), and oxygen uptake rate (OUR). DO monitoring was the simplest and leverages the ubiquitous DO trends of production, however it remains scale and gassing strategy dependent. Dual-frequency capacitance measurements were utilized to calculate VCV and thereby quantify the magnitude and timing of massive cell lysis that was correlated in time with peak viral potency. OUR, which quantifies the amount of oxygen being consumed per cellular volume, leverages both capacitance and DO measurements (in addition to oxygen mass balances pertaining to the gassing strategy) to provide a holistic scale-independent metabolic PAT readout. The sharp increase we observe in OUR prior to its decline due to cell lysis appears to be related to increased oxygen demand during viral production—this sharp increase precedes peak viral potency and peak specific productivity in our process. Data generated by our PAT tools—DO, VCV, OUR— were compared to potency and specific productivity trends across 22 batches. In this talk, we will discuss the utility and application of the tools, repeatability of our models across datasets, and the strengths and weaknesses of each model. Please click Download on the upper right corner to see the full abstract

Computational methods for cell culture media optimization and product quality control

Biologics development leading to approval can take decades. Acceleration of this timeline is necessary to bring safe and efficacious drugs to patients as early as possible. One research focus to reduce development time is the cell culture process development and optimization. In this study, we will present two computational strategies that cover: (1) enhancing cell culture media by amino acid optimization using Orthogonal-Partial Least Squares (OPLS) regression, and (2) modulating protein glycosylation by altering small molecule compound concentrations based on the Concentration Impact Factor. Disproportionate nutrient balance in cell culture medium can have a negative impact on cell culture performance. In our study, OPLS regression was used to explain cell growth and monoclonal antibody (mAb) production dynamics from Chinese Hamster Ovary (CHO) cells as a function of amino acid (AA) stoichiometric balances. The OPLS model was trained on metabolic data from 24 concurrent 14-day fed-batch cultures. Metabolic fluxes and respective stoichiometric balances were then generated by calculating the difference between the theoretical biomass demand of each AA and the actual AA usage towards mAb production and experimental consumption. As a result, highly weighted stoichiometric balances represented those AA that could potentially enhance the previous feed medium and aim to achieve a higher intracellular catabolic activity. Accordingly, we used our computational model to generate varied amino acid additions to either a platform feed or a low nutrient feed by means of a 16-run mixture design. The experimental results showed that addition of model generated key AA resulted in a ~55% increase in peak cell density and ~90% increase in mAb production, respectively. Appropriately glycosylated therapeutic mAb are critical for the proper molecular folding, stability, and in-vivo efficacy of the expressed proteins. Cell culture process conditions and medium compositions have been demonstrated to affect the expression of various glycosylation species. In this study, we evaluated a set of selected small compound for their potential in modifying glycosylation levels in mAb expressed in three different proprietary CHO cell lines. These small molecule compounds were first tested on one cell line to establish a baseline. To quantitate the glycosylation modifications, we have developed a mathematical correlation of a dimensionless number, termed Concentration Impact factor (Cf), to describe the degree changes in glycosylation species. Using the Cf algorithm established for the 1st cell line, we subsequently tested with other two cell lines, and were able to modulate and confirmed the level of glycan expression. This indicates that Cf correlation may serve as a tool to provide early assessment of final glycosylation profiles and levels on therapeutic proteins due to small molecule supplementations. Overall, the two computational methods presented here are aimed to enhance biologics development speed as well as ensure product quality control

A novel therapeutic strategy for pancreatic neoplasia using a novel RNAi platform targeting PDX-1

Bi-functional shRNA (bi-shRNA), a novel RNA interference (RNAi) effector platform targeting PDX-1 utilizing a systemic DOTAP-Cholesterol delivery vehicle, was studied in three mouse models of progressive pancreatic neoplasia. Species-specific bi-functional PDX-1 shRNA (bi-shRNAPDX-1) lipoplexes inhibited insulin expression and secretion while also substantially inhibiting proliferation of mouse and human cell lines via disruption of cell cycle proteins in vitro. Three cycles of either bi-shRNA<sup>mousePDX-1</sup> or shRNA<sup>mousePDX-1</sup> lipoplexes administered intravenously prevented death from hyperinsulinemia and hypoglycemia in a lethal insulinoma mouse model. Three cycles of shRNA<sup>mousePDX-1</sup> lipoplexes reversed hyperinsulinemia and hypoglycemia in an immune-competent mouse model of pancreatic neoplasia. Moreover, three cycles of the bi-shRNA<sup>humanPDX-1</sup> lipoplexes resulted in near complete ablation of tumor volume and considerably improved survival in a human PANC-1 implanted SCID-mouse model. Human pancreatic neoplasia specimens also stained strongly for PDX-1 expression. Together, these data support the clinical development of a novel therapeutic strategy using systemic bi-shRNA<sup>PDX-1</sup> lipoplexes against pancreatic neoplasia

Physical function limitation among gay and bisexual men aged ≥55years with and without HIV: findings from the Australian Positive and Peers Longevity Evaluation Study (APPLES)

Background. As people living with HIV now have a life expectancy approaching that of the general population, clinical care focuses increasingly on the management and prevention of comorbidities and conditions associated with aging. We aimed to assess the prevalence of physical function (PF) limitation among gay and bisexual men (GBM) and determine whether HIV is associated with severe PF limitation in this population. Methods. We analysed cross-sectional data from GBM aged ≥55 years in the Australian Positive and Peers Longevity Evaluation Study who completed a self-administered survey on health and lifestyle factors. PF was measured using the Medical Outcomes Study–Physical Functioning scale. Factors associated with severe PF limitation were assessed using logistic regression. Results. The survey was completed by 381 men: 186 without HIV and 195 with HIV. Median age was 64.3 years for GBM without HIV and 62.1 years for GBM with HIV. Compared with men without HIV, those with HIV had higher proportions of severe (13.3% vs 8.1%) and moderate-to-severe (26.7% vs 24.2%) PF limitation. Severe PF limitation commonly involved difficulty with vigorous activity (95% with severe PF limitation described being limited a lot), climbing several flights of stairs (68.4% limited a lot), bending, kneeling or stooping (60.5% limited a lot), and walking 1 km (55.0% limited a lot). In a model adjusted for age, body mass index, typical duration of physical activity, psychological distress, and number of comorbidities, we found a significant association between HIV and severe PF limitation (adjusted odds ratio 3.3 vs not having HIV, 95% confidence interval 1.3–8.7). Conclusions. The biological mechanisms underlying this association require further investigation, particularly given the growing age of the HIV population and inevitable increase in the burden of PF limitation