An end-to-end pipeline for succinic acid production at an industrially relevant scale using Issatchenkia orientalis.

Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34-90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

Advances in bioreactor control for production of biotherapeutic products.

Advanced control strategies are well established in chemical, pharmaceutical, and food processing industries. Over the past decade, the application of these strategies is being explored for control of bioreactors for manufacturing of biotherapeutics. Most of the industrial bioreactor control strategies apply classical control techniques, with the control system designed for the facility at hand. However, with the recent progress in sensors, machinery, and industrial internet of things, and advancements in deeper understanding of the biological processes, coupled with the requirement of flexible production, the need to develop a robust and advanced process control system that can ease process intensification has emerged. This has further fuelled the development of advanced monitoring approaches, modeling techniques, process analytical technologies, and soft sensors. It is seen that proper application of these concepts can significantly improve bioreactor process performance, productivity, and reproducibility. This review is on the recent advancements in bioreactor control and its related aspects along with the associated challenges. This study also offers an insight into the future prospects for development of control strategies that can be designed for industrial-scale production of biotherapeutic products.

Artificial intelligence and machine learning applications in biopharmaceutical manufacturing.

Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biotherapeutics and the shift toward Industry 4.0, spurring the rise of integrated process platforms and continuous processes that require intelligent, automated supervision. This review summarizes AI-ML applications in biopharmaceutical manufacturing, with a focus on the most used AI-ML algorithms, including multivariate data analysis, artificial neural networks, and reinforcement learning. Perspectives on the future growth of AI-ML applications in the area and the challenges of implementing these techniques at manufacturing scale are also presented.

Bioprocess Control: Current Progress and Future Perspectives.

Typical bioprocess comprises of different unit operations wherein a near optimal environment is required for cells to grow, divide, and synthesize the desired product. However, bioprocess control caters to unique challenges that arise due to non-linearity, variability, and complexity of biotech processes. This article presents a review of modern control strategies employed in bioprocessing. Conventional control strategies (open loop, closed loop) along with modern control schemes such as fuzzy logic, model predictive control, adaptive control and neural network-based control are illustrated, and their effectiveness is highlighted. Furthermore, it is elucidated that bioprocess control is more than just automation, and includes aspects such as system architecture, software applications, hardware, and interfaces, all of which are optimized and compiled as per demand. This needs to be accomplished while keeping process requirement, production cost, market value of product, regulatory constraints, and data acquisition requirements in our purview. This article aims to offer an overview of the current best practices in bioprocess control, monitoring, and automation.

Economic assessment of continuous processing for manufacturing of biotherapeutics.

Continuous processing offers a promising approach to revolutionize biotherapeutics manufacturing as reflected in recent years. The current study offers a comparative economic assessment of batch and continuous processing for the production of biotherapeutic products. Granulocyte-colony stimulating factor (GCSF), a protein expressed in E. coli, and an IgG1 monoclonal antibody, were chosen as representatives of microbial and mammalian derived products for this assessment. Economic indicators-cost of goods (COGs), net present value (NPV), and payback time have been estimated for the assessment. For the case of GCSF, conversion from batch to integrated continuous manufacturing induced a $COGs/g reduction of 83% and 73% at clinical and commercial scales, respectively. For the case of mAb therapeutic, a 68% and 35% reduction in $COGs/g on translation from batch to continuous process was projected for clinical and commercial scales, respectively. Upstream mAb titer was also found to have a significant impact on the process economics. With increasing mAb titer, the $COG/g decreases in both operating modes. With titer increasing from 2 to 8 g/L, the $COG/g of batch process was reduced by 53%, and that of the continuous process was reduced by 63%. Cost savings in both the cases were attributed to increased productivity, efficient equipment and facility utilization, smaller facility footprint, and reduction in utilization of consumables like resin media and buffers actualized by the continuous processing platform. The current study quantifies the economic benefits associated with continuous processing and highlights its potential in reducing the manufacturing cost of biotherapeutics.

Energetic assessment of fixation of CO2 and subsequent biofuel production using B. cereus SM1 isolated from sewage treatment plant.

The ongoing work on global warming resulting from green house gases (GHGs) has led to explore the possibility of bacterial strains which can fix carbon dioxide (CO2) and can generate value-added products. The present work is an effort in this direction and has carried out an exhaustive batch experiments for the fixation of CO2 using B. Cereus SM1 isolated from sewage treatment plant (STP). The work has incorporated 5-day batch run for gaseous phase inlet CO2 concentration of 13 ± 1 % (%v/v). 84.6 (±5.76) % of CO2 removal was obtained in the gaseous phase at mentioned CO2 concentration (%v/v). Energetic requirement for CO2 fixation was assessed by varying Fe[II] ion concentration (0-200 ppm) on the per-day basis. The cell lysate obtained from CO2 fixation studies (Fe[II] ion = 100 ppm) was analyzed using Fourier transformation infrared spectroscopy (FTIR) and gas chromatography-mass spectroscopy (GC-MS). This analysis confirmed the presence of fatty acids and hydrocarbon as valuable products. The hydrocarbons were found in the range of C11-C22 which is equivalent to light oil. The obtained fatty acids were found in the range of C11-C19. The possibility of fatty acid conversion to biodiesel was explored by carrying out the transesterification reaction. The yield of biodiesel was obtained as 86.5 (±0.048) % under the transesterification reaction conditions. Results of this research work can provide the valuable information in the implementation of biomitigation of CO2 at real scenario.