Identification of novel inhibitory metabolites and impact verification on growth and protein synthesis in mammalian cells.

Mammalian cells consume large amount of nutrients during growth and production. However, endogenous metabolic inefficiencies often prevent cells to fully utilize nutrients to support growth and protein production. Instead, significant fraction of fed nutrients is diverted into extracellular accumulation of waste by-products and metabolites, further inhibiting proliferation and protein synthesis. In this study, an LC-MS/MS based metabolomics pipeline was used to screen Chinese hamster ovary (CHO) extracellular metabolites. Six out of eight identified inhibitory metabolites, caused by the inefficient cell metabolism, were not previously studied in CHO cells: aconitic acid, 2-hydroxyisocaproic acid, methylsuccinic acid, cytidine monophosphate, trigonelline, and n-acetyl putrescine. When supplemented back into a fed-batch culture, significant reduction in cellular growth was observed in the presence of each metabolite and all the identified metabolites were shown to impact the glycosylation of a model secreted antibody, with seven of these also reducing CHO cellular productivity (titer) and all eight inhibiting the formation of mono-galactosylated biantennary (G1F) and biantennary galactosylated (G2F) N-glycans. These inhibitory metabolites further impact the metabolism of cells, leading to a significant reduction in CHO cellular growth and specific productivity in fed-batch culture (maximum reductions of 27.2% and 40.6% respectively). In-depth pathway analysis revealed that these metabolites are produced when cells utilize major energy sources such as glucose and select amino acids (tryptophan, arginine, isoleucine, and leucine) for growth, maintenance, and protein production. Furthermore, these novel inhibitory metabolites were observed to accumulate in multiple CHO cell lines (CHO-K1 and CHO-GS) as well as HEK293 cell line. This study provides a robust and holistic methodology to incorporate global metabolomic analysis into cell culture studies for elucidation and structural verification of novel metabolites that participate in key metabolic pathways to growth, production, and post-translational modification in biopharmaceutical production.

Effects of process parameters on tablet critical quality attributes in continuous direct compression: a case study of integrating data-driven statistical models and mechanistic compaction models.

Continuous manufacturing of oral-dosage drug products is increasing the need for rigorous process understanding both from a process design and control perspective. The purpose of this study is to develop a methodology that analyzes the effects of upstream process parameters on continuous tablet compaction and then correlates associated upstream variables to the final tablet attributes (e.g. relative density and hardness). The impact of three process parameters (system throughput, blender speed, and compaction force) on tablet attributes is investigated using a full factorial experimental design. As expected, the compaction force was found to be the most significant process parameter. However, importantly, throughput was discovered to have a non-negligible impact which was previously unaccounted for. This impact is proposed to be related to differing levels of powder pre-compression. An empirical model for this relationship is regressed and incorporated into a flowsheet model. The flowsheet model is then used to develop an in silico design space which is compared favorably to that built from experiments. Moreover, in the future, the in silico design space based on the validated flowsheet model can provide better manufacturing flexibility and make control strategy development simpler.

A Thermodynamic Balance Model for Liquid Film Drying Kinetics of a Tablet Film Coating and Drying Process.

A tablet film coating and drying process was assessed by an experimentally validated thermodynamic balance model. Mass conservation equations were derived for the process air and the aqueous coating solution. Thermodynamic behavior of the solution was described by evaporation at the tablet surface and penetration into the tablet. Energy balance equations including heat loss to the atmosphere were coupled to the mass conservation equation. Experimental data using the ConsiGma™ coater (GEA, Belgium) were used for both parameter estimation and model validation. The results showed the proposed model can investigate primitive outlet variables and further internal variables representing evaporation and penetration. A sensitivity analysis revealed that evaporation depended more on the input parameters while penetration hinges on the tablet properties, particularly on the tablet volume affecting the tablet porosity.

Assessment of spatial heterogeneity in continuous twin screw wet granulation process using three-compartmental population balance model.

In this study, a novel three-compartmental population balance model (PBM) for a continuous twin screw wet granulation process is developed, combining the techniques of PBM and regression process modeling. The developed model links screw configuration, screw speed, and blend throughput with granule properties to predict the granule size distribution (GSD) and volume-average granule diameter. The granulator screw barrel was divided into three compartments along barrel length: wetting compartment, mixing compartment, and steady growth compartment. Different granulation mechanisms are assumed in each compartment. The proposed model therefore considers spatial heterogeneity, improving model prediction accuracy. An industrial data set containing 14 experiments is applied for model development. Three validation experiments show that the three-compartmental PBM can accurately predict granule diameter and size distribution at randomly selected operating conditions. Sixteen combinations of aggregation and breakage kernels are investigated in predicting the experimental GSD to best judge the granulation mechanism. The three-compartmental model is compared with a one-compartmental model in predicting granule diameter at different experimental conditions to demonstrate its advantage. The influence of the screw configuration, screw speed and blend throughput on the volume-average granule diameter is analyzed based on the developed model.

Modeling and simulation of continuous powder blending applied to a continuous direct compression process.

Continuous manufacturing techniques are increasingly being adopted in the pharmaceutical industry and powder blending is a key operation for solid-dosage tablets. A modeling methodology involving axial and radial tanks-in-series flowsheet models is developed to describe the residence time distribution (RTD) and blend uniformity of a commercial powder blending system. Process data for a six-component formulation processed in a continuous direct compression line (GEA Pharma Systems) is used to test the methodology. Impulse tests were used to generate experimental RTDs which are used along with parameter estimation to determine the number of axial tanks in the flowsheet. The weighted residual from the parameter estimation was less than the χ2 value at a 95% confidence indicating a good fit between the model and measured data. In-silico impulse tests showed the tanks-in-series modeling methodology could successfully describe the RTD behavior of the blenders along with blend uniformity through the use of radial tanks. The simulation output for both impulse weight percentage and blend uniformity were within the experimentally observed variance.