Process design of a fully integrated continuous biopharmaceutical process using economic and ecological impact assessment.

Continuous biomanufacturing is a promising alternative to current batch operation as it offers benefits in terms of improved productivity, product quality, and reduced footprint. This study aims to build a fully integrated continuous platform for monoclonal antibody (mAb) production incorporating novel technologies (like intensified seed expansion and continuous high cell density perfusion operations, single-pass tangential flow filtration, and single-use technologies) as well as media and buffer preparation steps. Economic assessment is performed on the basis of the total cost of goods (COGs), which is $102.2/g in the base-case scenario with a bioreactor scale of 500 L. E-factor is used as an environmental indicator and the result shows that 4865.6kg of process water and 11.1 kg of consumables are required to produce 1 kg mAbs. After the development and analysis of the benchmark process, scenario analysis is performed to assess the impacts of the bioreactor scale (60-2000 L) and upstream titers (1.12-2.08 g/L) on the process economics as well as on the environmental footprint. With the increase of bioreactor scale and mAb titer, the operating COGs per unit product decrease. Moreover, increasing the mAb titer is more favorable in terms of the ecological impacts. To investigate the production capacity, the upstream production is increased and the downstream bottlenecks are determined. It is found that only the multicolumn chromatographic (MCC) operations become the process bottleneck and the order of the MCC unit operation that becomes the process bottleneck depends on capacity utilization for that step. Finally, a new platform is built with the integration of membrane chromatography and the two designed processes are compared in terms of economic and ecological impacts.

Hybrid model development for parameter estimation and process optimization of hydrophobic interaction chromatography.

Hydrophobic Interaction Chromatography (HIC) is often employed as a polishing step to remove aggregates for the purification of therapeutic proteins in the biopharmaceutical industry. To accelerate the process development and save the costs of performing time- and resource-intensive experiments, advanced model-based process design and optimization are necessary. Due to the unclear adsorption mechanism of the salt-dependent interaction between the protein and resin, the development of an accurate mechanistic model to describe the complex HIC behavior is challenging. In this work, an isotherm derived from Wang et al. is modified by adding three extra parameters together with an equilibrium dispersive model to represent the HIC process. To reduce the development effort of isotherm equations and extract missing information from the available data, a hybrid model is constructed by combining a simple and well-known multi-component Langmuir isotherm (MCL) with a neural network (NN). It is observed that the structure of the hybrid model is of critical importance to the accuracy of the developed model. During parameter estimation, a regularization strategy is incorporated to prevent overfitting. Furthermore, the impact of NN structures and regularization rates are comprehensively investigated. One of the interesting findings was that a simple NN with one hidden layer with two nodes and sigmoid as the activation function, significantly outperforms the mechanistic model, with a 62% improvement in accuracy in calibration and 31.4% in validation. To ensure the generalizability of the developed hybrid model, an in-silico dataset is generated using the mechanistic model to test the extrapolation capability of the hybrid model. Process optimization is also carried out to find the optimal operating conditions under product quality constraints using the developed hybrid model.

A novel framework of surrogate-based feasibility analysis for establishing design space of twin-column continuous chromatography.

Multi-column periodic counter-current chromatography (PCC) has attracted wide attention for the primary capture for the purpose of achieving continuous biomanufacturing. Consequently, determining the design space of the continuous capture process is very important to facilitate process understanding and improving product quality. In this work, we proposed a novel approach to identify the design space of continuous chromatography to balance the computational complexity and model predictions. Specifically, surrogate-based feasibility analysis with adaptive sampling is applied to establish the design space of twin-column CaptureSMB process. The surrogate model is constructed based on the developed mechanistic model for the identification of the design space. The effects of process variables (including interconnected loading time, interconnected flowrate, and batch flowrate) on the design space are comprehensively examined based on an active set strategy. Besides, essential factors like recovery-regeneration time and constraints of column performance parameters (yield, productivity, and capacity utilization) are thoroughly investigated. The impact of design variables such as column length is also studied.

Heterostructure engineering of Co-doped MoS2 coupled with Mo2CTx MXene for enhanced hydrogen evolution in alkaline media.

The hydrogen evolution reaction (HER) in alkaline media is key for the cathodic reaction of electrochemical water splitting, but it suffers sluggish kinetics due to the slow water dissociation process. Here, we present a simple strategy to enhance the HER activity in alkaline media by engineering Co-doped MoS2 coupled with Mo2CTx MXene. The improved HER activity might be ascribed to the synergistic regulation of water dissociation sites and electronic conductivity. Co doping could effectively regulate the electronic structure of MoS2 and further improve the intrinsic activity of the catalyst. Mo2CTx MXene served as both the active and conductive substrate to facilitate electron transfer. As a result, the Co-MoS2/Mo2CTx nanohybrids showed dramatically enhanced HER performance with a low overpotential of 112 mV at a current density of 10 mA cm-2 and exhibited excellent long-term stability in alkaline media.