Chromatography bioseparation technologies and in-silico modelings for continuous production of biotherapeutics

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

A fluidized-bed-riser adsorption system for continuous bioproduct recovery from crude feedstock

In this work, a novel technique for continuous purification of biologics from a crude feedstock is demonstrated with equipment referred to as Fluidized Bed Adsorption System (FBRAS). The development and validation of such unit operations were performed utilizing lysozyme as a model protein and Relisorb™ SP405/EB as a carrier. The performance of FBRAS to carry out combined clarification and purification was evaluated by capturing of antifungal peptides directly from the lysed broth. The novel technique reduced the number of process unit operations from six to three without having an impact on purity. Overall productivity increased by 250% in comparison to the existing downstream processing routine.

Improved process design for monoclonal antibody charge variants separation with multicolumn counter-current solvent gradient purification

The multicolumn counter-current solvent gradient purification (MCSGP) method has proven effective in addressing the issue of elution profile overlap for difficult-to-separate proteins, leading to improved purity and recovery. However, during the MCSGP process, the flow rate and proportion of loaded proteins undergo changes, causing a significant discrepancy between the elution profiles of batch process design and the actual MCSGP process. This mismatch negatively impacts the purity and recovery of the target protein. To address this challenge, an improved process design (reDesign) was proposed with the first-run MCSGP to mimic the actual continuous process and obtain elution profiles that closely resemble the real ones. The reDesign was demonstrated with both a model protein mixture and a sample of monoclonal antibody (mAb) with charge variants. For model protein mixture, the reDesign-based MCSGP process (reMCSGP) showed a remarkable improvement in recovery, increasing from 83.6% to 97.8% while maintaining a purity of more than 95%. For mAb sample, the recovery of reMCSGP improved significantly to 93.9%, surpassing the performance of normal MCSGP processes at a given purity level of more than 84%. In general, the new process design strategy developed in this work could generate a more representative elution profile that closely mirrors actual conditions in continuous processes, which enhances the separation performance of MCSGP.

Surrogate-based Optimization of Capture Chromatography Platforms for the Improvement of Computational Efficiency

In this work, we discuss the use of surrogate functions and a new optimization framework to create an efficient and robust computational framework for process design. Our model process is the capture chromatography unit operation for monoclonal antibody purification, an important step in biopharmaceutical manufacturing. Simulating this unit operation involves solving a system of non-linear partial differential equations, which can have high computational cost. We implemented surrogate functions to reduce the computational time and make the framework more attractive for industrial applications. This strategy yielded accurate results with a 93% decrease in processing time. Additionally, we developed a new optimization framework to reduce the number of simulations needed to generate a solution to the optimization problem. We demonstrate the performance of our new framework, which uses MATLAB built-in tools, by comparing its performance against individual optimization algorithms for problems with integer, continuous, and mixed-integer variables.

Computational framework for the techno-economic analysis of monoclonal antibody capture chromatography platforms

We developed a computational framework that integrates commercial software components to perform customizable technoeconomic feasibility analyses. The use of multiple software packages overcomes the shortcomings of each to provide a detailed simulation that can be used for sensitivity analyses and optimizations. In this paper, the framework was used to evaluate the performance of monoclonal antibody capture processes. To this end, the simulation framework incorporated dynamic models for the affinity chromatography step that were validated with experimental breakthrough curves. The results were integrated with an Intelligen SuperPro Designer process simulation for the evaluation of key performance indicators of the operations. As proof of concept, the framework was used to perform a sensitivity analysis and optimization for a case study in which we sought to compare membrane and resin chromatography for disposable and reusable batch capture platforms. Two membranes and one resin were selected for the capture media, which yielded six process alternatives to compare. The objective functions were set to be cost of goods, process time, and buffer utilization. The results of the optimization of these process alternatives were a set of operating conditions that display tradeoffs between competing objectives. From this application exercise, we conclude that the framework can handle multiple variables and objectives, and it is adaptable to platforms with different chromatography media and operating modes. Additionally, the framework is capable of providing ad hoc analyses for decision making in a specific production context.

Downstream Processing of Medicinal Mushroom Products

Medicinal mushrooms are higher fungi that consist of ascomycetes, basidiomycetes, and imperfect fungi. They have been long used as tonic and traditional medicine in East Asia, Europe, and Africa. Contemporary pharmacological researches have revealed that they possess a wide spectrum of bioactivity due to their production of a variety of bioactive compounds. Some of them have entered into the market; some are ready for industrial trials and further commercialization, while others are in various stages of development. According to the purpose of usage, a variety of medicinal mushroom-based products have been developed, which could be roughly divided into three general categories, i.e., nutraceuticals/functional foods, nutriceuticals/dietary supplements, and pharmaceuticals. Accordingly, the downstream processing of medicinal mushroom products varies greatly. Indeed, a major characteristic of medicinal mushroom is the wide variety of secondary metabolites, due to which a broad spectrum of separation techniques must be employed. In this chapter we will present an overview of the achievements in downstream processing technology for medicinal mushroom products. Examples of separation of products such as bioactive high-molecular-weight products like polysaccharides and low-molecular-weight products like triterpenoids are given. The application of some special separation strategy, e.g., chemical reaction-assisted separation for tackling some analogs with similar physicochemical properties from medicinal mushroom, is also described.

The use of predictive models to develop chromatography-based purification processes

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Modern trends in downstream processing of biotherapeutics through continuous chromatography: The potential of Multicolumn Countercurrent Solvent Gradient Purification

Single-column (batch) preparative chromatography is the technique of choice for purification of biotherapeutics but it is often characterized by an intrinsic limitation in terms of yield-purity trade-off, especially for separations containing a larger number of product-related impurities. This drawback can be alleviated by employing multicolumn continuous chromatography. Among the different methods working in continuous mode, in this paper we will focus in particular on Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) which has been specifically designed for challenging separations of target biomolecules from their product-related impurities. The improvements come from the automatic internal recycling of the impure fractions inside the chromatographic system, which results in an increased yield without compromising the purity of the pool. In this article, steps of the manufacturing process of biopharmaceuticals will be described, as well as the advantages of continuous chromatography over batch processes, by particularly focusing on MCSGP.

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.