Computational Modeling of Fed-Batch Cell Culture Bioreactor: Hybrid Agent-Based Approach

Quality assessment of flax advanced breeding lines varying in seed coat color and their potential use in the food and industrial applications

BACKGROUND

With the increasing consumer awareness of the strong relationship between food and health, flax became a promising functional food due to its bioactive nutraceutical composition. Intra-specific crosses of eight contrasting flax genotypes were performed previously, and within segregating F6 progeny families, we investigated a close-up composition of phytochemicals derived from whole seeds.

RESULTS

The considerable genetic variation among the flax F6 families suggested that intra-specific hybridization is essential in flax breeding to obtain and broaden genetic variability and largely affirmed the opportunity for selecting promising lines. Also, significant variations in the targeted metabolite contents and antioxidant properties were observed among brown and yellow-seeded families. Notably, brown-seeded families expressed the highest average values of saturated fatty acids, protein, fiber, tocopherol, phenolics, SDG, and SECO lignans. Yellow-seeded families represented the highest average content of unsaturated fatty acids and mucilage. The cultivation year significantly affects flaxseed's composition and functional properties, presumably due to temperature, humidity, and sunshine time differences. Interestingly, the seeds obtained in warmer conditions were more potent and had more chemical constituents. The favorable genetic correlations among all evaluated traits suggest the possibility of joint genetic selection for several nutritional and phytochemical characteristics in flax. The current study highlights the importance and utilization of 19 top families as their seeds and oil play imperative roles in the pharmaceuticals and food industries. The antioxidant capacity of the seeds showed that families 84B, 23B, 35Y, 95Y, 30B, 88B, and 78B serve as a natural source of dietary antioxidants beneficial to human health. To increase the oxidative stability of the flaxseed oil, the quality evaluation identified some families with low levels of linolenic acid.

CONCLUSIONS

These findings are essential to improving flaxseed's nutritional quality and therapeutic properties through a bulk breeding program.

A genome-scale nutrient minimization forecast algorithm for controlling essential amino acid levels in CHO cell cultures

Mammalian cell culture processes rely heavily on empirical knowledge in which process control remains a challenge due to the limited characterization/understanding of cell metabolism and inability to predict the cell behaviors. This study facilitates control of Chinese hamster ovary (CHO) processes through a forecast-based feeding approach that predicts multiple essential amino acids levels in the culture from easily acquired viable cell density data. Multiple cell growth behavior forecast extrapolation approaches are considered with logistic curve fitting found to be the most effective. Next, the nutrient-minimized CHO genome-scale model is combined with the growth forecast model to generate essential amino acid forecast profiles of multiple CHO batch cultures. Comparison of the forecast with the measurements suggests that this algorithm can accurately predict the concentration of most essential amino acids from cell density measurement with error mitigated by incorporating off-line amino acids concentration measurements. Finally, the forecast algorithm is applied to CHO fed-batch cultures to support amino acid feeding control to control the concentration of essential amino acids below 1-2 mM for lysine, leucine, and valine as a model over a 9-day fed batch culture while maintaining comparable growth behavior to an empirical-based culture. In turn, glycine production was elevated, alanine reduced and lactate production slightly lower in control cultures due to metabolic shifts in branched-chain amino acid degradation. With the advantage of requiring minimal measurement inputs while providing valuable and in-advance information of the system based on growth measurements, this genome model-based amino acid forecast algorithm represent a powerful and cost-effective tool to facilitate enhanced control over CHO and other mammalian cell-based bioprocesses.

Digital Twins in Pharmaceutical and Biopharmaceutical Manufacturing: A Literature Review

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current status of DT development and its application in pharmaceutical and biopharmaceutical manufacturing. State-of-the-art Process Analytical Technology (PAT) developments, process modeling approaches, and data integration studies are reviewed. Challenges and opportunities for future research in this field are also discussed.

Forecasting and control of lactate bifurcation in Chinese hamster ovary cell culture processes

Biomanufacturing exhibits inherent variability that can lead to variation in performance attributes and batch failure. To help ensure process consistency and product quality the development of predictive models and integrated control strategies is a promising approach. In this study, a feedback controller was developed to limit excessive lactate production, a widespread metabolic phenomenon that is negatively associated with culture performance and product quality. The controller was developed by applying machine learning strategies to historical process development data, resulting in a forecast model that could identify whether a run would result in lactate consumption or accumulation. In addition, this exercise identified a correlation between increased amino acid consumption and low observed lactate production leading to the mechanistic hypothesis that there is a deficiency in the link between glycolysis and the tricarboxylic acid cycle. Using the correlative process parameters to build mechanistic insight and applying this to predictive models of lactate concentration, a dynamic model predictive controller (MPC) for lactate was designed. This MPC was implemented experimentally on a process known to exhibit high lactate accumulation and successfully drove the cell cultures towards a lactate consuming state. In addition, an increase in specific titer productivity was observed when compared with non-MPC controlled reactors.

Computational Model-Based Analysis of Strategies to Enhance Scaffold Vascularization

Stable and extensive blood vessel networks are required for cell function and survival in engineered tissues. A number of different strategies are currently being investigated to enhance biomaterial vascularization with screening primarily through extensive in vitro and in vivo experiments. In this article, we describe an agent-based model (ABM) developed to evaluate various strategies in silico, including design of optimal biomaterial structure, delivery of angiogenic factors, and application of prevascularized biomaterials. The model predictions are evaluated using experimental data. The ABM developed provides insight into different strategies currently applied for scaffold vascularization and will enable researchers to rapidly screen new hypotheses and explore alternative strategies for enhancing vascularization.