Mathematical Modeling of Protein Chromatograms

Advances in modeling techniques for the production and purification of biomolecules: A comprehensive review

In response to the growing demand for therapeutic biomolecules, there is a need for continuous and cost-effective bio-separation techniques to enhance extraction yield and efficiency. Aqueous biphasic extractive fermentation has emerged as an integrated downstream processing technique, offering selective partitioning, high productivity, and preservation of biomolecule integrity. However, the dynamic nature of this technique requires a comprehensive understanding of the underlying separation mechanisms. Unfortunately, the analysis of parameters influencing this dynamic behavior can be challenging due to limited resources and time. To address this, mathematical modeling approaches can be employed to minimize the tedious trial-and-error experimentation process. This review article presents mathematical modeling approaches for both upstream and downstream processing techniques, focusing on the production of biomolecules which can be used in pharmaceutical industries in a cost-effective manner. By leveraging mathematical models, researchers can optimize the production and purification processes, leading to improved efficiency and processing cost reduction in biomolecule production.

Predictive scaling of fiber-based protein A capture chromatography using mechanistic modeling

Protein A affinity chromatography is an important step in the purification of monoclonal antibodies (mAbs) and mAb-derived biotherapeutics. While the biopharma industry has extensive expertise in the operation of protein A chromatography, the mechanistic understanding of the adsorption/desorption processes is still limited, and scaling up and scaling down can be challenging because of complex mass transfer effects in bead-based resins. In convective media, such as fiber-based technologies, complex mass transfer effects such as film and pore diffusions do not occur which facilitates the study of the adsorption phenomena in more detail and simplifies the process scale-up. In the present study, the experimentation with small-scale fiber-based protein A affinity adsorber units using different flow rates forms the basis for modeling of mAb adsorption and elution behavior. The modeling approach combines aspects of both stoichiometric and colloidal adsorption models, and an empirical part for the pH. With this type of model, it was possible to describe the experimental chromatograms on a small scale very well. An in silico scale-up could be carried out solely with the help of system and device characterization without feedstock. The adsorption model could be transferred without adaption. Although only a limited number of runs were used for modeling, the predictions of up to 37 times larger units were accurate.

A comprehensive method for modeling and simulating ion exchange chromatography of complex mixtures

In recent years, many biological-based products have been developed, representing a significant fraction of income in the pharmaceutical market. Ion exchange chromatography is an important downstream step for the purification of target recombinant proteins present in clarified cell extracts, together with many other unknown impurities. This work develops a robust approach to model and simulate the purification of untagged heterologous proteins, so that the improved conditions to carry out an ion exchange chromatography are identified in a rational basis prior to the real purification run itself. Purification of the pneumococcal surface protein A (PspA4Pro) was used as a case study. This protein is produced by recombinant Escherichia coli and is a candidate for the manufacture of improved pneumococcal vaccines. The developed method combined experimental and computational procedures. Different anion exchange operating conditions were mapped in order to gather a broad range of representative experimental data. The equilibrium dispersive and the steric mass action equations were used to model and simulate the process. A training strategy to fit the model and separately describe the elution profiles of PspA4Pro and other proteins of the cell extract was applied. Based on the simulation results, a reduced ionic strength was applied for PspA4Pro elution, leading to increases of 14.9% and 11.5% for PspA4Pro recovery and purity, respectively, compared to the original elution profile. These results showed the potential of this method, which could be further applied to improve the performance of ion exchange chromatography in the purification of other target proteins under real process conditions.

Microbial technologies for biotherapeutics production: Key tools for advanced biopharmaceutical process development and control

Current trends in the biopharmaceutical market such as the diversification of therapies as well as the increasing time-to-market pressure will trigger the rethinking of bioprocess development and production approaches. Thereby, the importance of development time and manufacturing costs will increase, especially for microbial production. In the present review, we investigate three technological approaches which, to our opinion, will play a key role in the future of biopharmaceutical production. The first cornerstone of process development is the generation and effective utilization of platform knowledge. Building processes on well understood microbial and technological platforms allows to accelerate early-stage bioprocess development and to better condense this knowledge into multi-purpose technologies and applicable mathematical models. Second, the application of verified scale down systems and in silico models for process design and characterization will reduce the required number of large scale batches before dossier submission. Third, the broader availability of mathematical process models and the improvement of process analytical technologies will increase the applicability and acceptance of advanced control and process automation in the manufacturing scale. This will reduce process failure rates and subsequently cost of goods. Along these three aspects we give an overview of recently developed key tools and their potential integration into bioprocess development strategies.

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.

A comprehensive molecular dynamics approach to protein retention modeling in ion exchange chromatography

In downstream processing, the underlying adsorption mechanism of biomolecules to adsorbent material are still subject of extensive research. One approach to more mechanistic understanding is simulating this adsorption process and hereby the possibility to identify the parameters with strongest impact. So far this method was applied with all-atom molecular dynamics simulations of two model proteins on one cation exchanger. In this work we developed a molecular dynamics tool to simulate protein-adsorber interaction for various proteins on an anion exchanger and ran gradient elution experiments to relate the simulation results to experimental data. We were able to show that simulation results yield similar results as experimental data regarding retention behavior as well as binding orientation. We could identify arginines in case of cation exchangers and aspartic acids in case of anion exchangers as major contributors to binding.

How can measurement, monitoring, modeling and control advance cell culture in industrial biotechnology?

This report highlights the potential of measurement, monitoring, modeling and control (M(3) C) methodologies in animal and human cell culture technology. In particular, state-of-the-art of M(3) C technologies and their industrial relevance of existing technology are addressed. It is a summary of an expert panel discussion between biotechnologists and biochemical engineers with both academic and industrial backgrounds. The latest ascents in M(3) C are discussed from a cell culture perspective for industrial process development and production needs. The report concludes with a set of recommendations for targeting M(3) C research toward the industrial interests. These include issues of importance for biotherapeutics production, miniaturization of measurement techniques and modeling methods.