Modeling and prediction of excipient and pH drifts during ultrafiltration/diafiltration of monoclonal antibody biotherapeutic for high concentration formulations

Membrane technology for the purification of RNA and DNA therapeutics

Nucleic acid therapeutics have the potential to revolutionize the biopharmaceutical industry, providing highly effective vaccines and novel treatments for cancers and genetic disorders. The successful commercialization of these therapeutics will require development of manufacturing strategies specifically tailored to the purification of nucleic acids. Membrane technologies already play a critical role in the downstream processing of nucleic acid therapeutics, ranging from clarification to concentration to selective purification. This review provides an overview of how membrane systems are currently used for nucleic acid purification, while highlighting areas of future need and opportunity, including adoption of membranes in continuous bioprocessing.

Application of Formulation Principles to Stability Issues Encountered During Processing, Manufacturing, and Storage of Drug Substance and Drug Product Protein Therapeutics

The field of formulation and stabilization of protein therapeutics has become rather extensive. However, most of the focus has been on stabilization of the final drug product. Yet, proteins experience stress and degradation through the manufacturing process, starting with fermentaition. This review describes how formulation principles can be applied to stabilize biopharmaceutical proteins during bioprocessing and manufacturing, considering each unit operation involved in prepration of the drug substance. In addition, the impact of the container on stabilty is discussed as well.

Predicting Formulation Conditions During Ultrafiltration and Dilution to Drug Substance Using a Donnan Model with Homology-Model Based Protein Charge

In the manufacturing of therapeutic monoclonal antibodies (mAbs), the final steps of the purification process are typically ultrafiltration/diafiltration (UF/DF), dilution, and conditioning. These steps are developed such that the final drug substance (DS) is formulated to the desired mAb, buffer, and excipient concentrations. To develop these processes, process and formulation development scientists often perform experiments to account for the Gibbs-Donnan and volume-exclusion effects during UF/DF, which affect the output pH and buffer concentration of the UF/DF process. This work describes the development of an in silico model for predicting the DS pH and buffer concentration after accounting for the Gibbs-Donnan and volume-exclusion effects during the UF/DF operation and the subsequent dilution and conditioning steps. The model was validated using statistical analysis to compare model predictions against experimental results for nine molecules of varying protein concentrations and formulations. In addition, our results showed that the structure-based in silico approach used to calculate the protein charge was more accurate than a sequence-based approach. Finally, we used the model to gain fundamental insights about the Gibbs-Donnan effect by highlighting the role of the protein charge concentration (the protein concentration multiplied with protein charge at the formulation pH) on the Gibbs-Donnan effect. Overall, this work demonstrates that the Gibbs-Donnan and volume-exclusions effects can be predicted using an in silico model, potentially alleviating the need for experiments.

Continuous integrated manufacturing for biopharmaceuticals: A new paradigm or an empty promise?

Continuous integrated bioprocessing has elicited considerable interest from the biopharma industry for the many purported benefits it promises. Today many major biopharma manufacturers around the world are engaged in the development of continuous process platforms for their products. In spite of great potential, the path toward continuous integrated bioprocessing remains unclear for the biologics industry due to legacy infrastructure, process integration challenges, vague regulatory guidelines, and a diverging focus toward novel therapies. In this article, we present a review and perspective on this topic. We explore the status of the implementation of continuous integrated bioprocessing among biopharmaceutical manufacturers. We also present some of the key hurdles that manufacturers are likely to face during this implementation. Finally, we hypothesize that the real impact of continuous manufacturing is likely to come when the cost of manufacturing is a substantial portion of the cost of product development, such as in the case of biosimilar manufacturing and emerging economies.

Current evidence in high throughput ultrafiltration toward the purification of monoclonal antibodies (mAbs) and biotechnological protein-type molecules

Pressure-driven membrane-based technologies, such as microfiltration (MF), ultrafiltration (UF), and nanofiltration (NF), have been successfully implemented in recovering different types of biomolecules and high-value-added compounds from various streams. Especially, UF membranes meet the requirements for separating specific bioproducts in downstream processes, e.g. monoclonal antibodies (mAbs), which are recognized as proteins produced mainly by plasma cells. According to the importance and functionality of the mAbs, their recovery is a current challenge with these bioseparations. Nevertheless, mAbs recovery using UF-assisted processes has been smartly performed over the last decade. To the best of our knowledge, there are no reviews of the reported developments using UF technology toward mAbs separation. Therefore, the goal of this paper is to collect and elucidate ongoing research studies implemented for the featured separation of mAbs and other biotechnological protein-type molecules (e.g. adenovirus serotype, extracellular vesicles, red fluorescent protein, cyanovirin-N, among others) via ultrafiltration-aided systems. The literature evidence (e.g. research papers, patents, etc.) has been analyzed and discussed according to the purpose of the study. Importantly, the relevant findings and novel approaches are discussed in detail. To finalize this document, the advantages, drawbacks, and guidelines in applying membrane-based techniques for such a recovery are presented.

White paper on high-throughput process development for integrated continuous biomanufacturing

Continuous manufacturing is an indicator of a maturing industry, as can be seen by the example of the petrochemical industry. Patent expiry promotes a price competition between manufacturing companies, and more efficient and cheaper processes are needed to achieve lower production costs. Over the last decade, continuous biomanufacturing has had significant breakthroughs, with regulatory agencies encouraging the industry to implement this processing mode. Process development is resource and time consuming and, although it is increasingly becoming less expensive and faster through high-throughput process development (HTPD) implementation, reliable HTPD technology for integrated and continuous biomanufacturing is still lacking and is considered to be an emerging field. Therefore, this paper aims to illustrate the major gaps in HTPD and to discuss the major needs and possible solutions to achieve an end-to-end Integrated Continuous Biomanufacturing, as discussed in the context of the 2019 Integrated Continuous Biomanufacturing conference. The current HTPD state-of-the-art for several unit operations is discussed, as well as the emerging technologies which will expedite a shift to continuous biomanufacturing.

Near Infrared Spectroscopy as a PAT tool for monitoring and control of protein and excipient concentration in ultrafiltration of highly concentrated antibody formulations

Excipient concentrations are critical quality attributes of monoclonal antibody (mAb) drug products and affect their safety and efficacy. In manufacturing processes, mAb products are formulated into the buffer containing the desired excipients using ultrafiltration (UF) and diafiltration (DF). Control of excipient concentrations is a challenge during high concentration UF due to electrostatic interactions which lead to excipient concentration drifts. This challenge is of increasing importance due to the growing preference towards high concentration subcutaneous drug formulations over conventional intravenous formulations in the biotherapeutic industry. Excipient concentrations are currently measured using offline RP-HPLC which is time-consuming and not suited for real time control. We propose a novel process analytical technology (PAT) tool for monitoring and control of mAb and excipients in high concentration UF using Near Infrared Spectroscopy (NIRS). The NIRS is able to monitor concentrations within ±1% for mAb and ±2% for two common excipients, L-histidine and acetate. A Python-based controller uses real time concentration data to deliver concentrated excipient stock solutions to the UF reservoir whenever the excipient concentrations drift out of range. The PAT control system is able to achieve the target formulation without manual intervention or at-line analysis and is well-suited for implementation in mAb manufacturing platforms.

A mechanistic model to account for the Donnan and volume exclusion effects in ultrafiltration/diafiltration process of protein formulations

Ultrafiltration/diafiltration (UF/DF) is a typical step in protein drug manufacturing process to concentrate and exchange the protein solution into a desired formulation. However, significant offset of pH and composition from the target formulation have been frequently observed after UF/DF, posing challenges to the stability, performance, and consistency of the final drug product. Such shift can often be attributed to the Donnan and volume exclusion effects. In order to predict and compensate for those effects, a mechanistic model is developed based on the protein charge, mass and charge balances, as well as the equilibrium condition across the membrane. The integrated UF/DF model can be used to predict both the dynamic behavior and the final outcome of the process. Examples of the modeling results for the pH and composition variation during the UF/DF operations are presented for two monoclonal antibody proteins. The model predictions are in good agreement with a comprehensive experimental data set that covers different process steps, protein concentrations, solution matrices, and process scales. The results show that significant pH and excipient concentration shifts are more likely to occur for high protein concentration and low ionic strength matrices. As a special example, a self-buffering protein formulation shows unique pH behavior during DF, which could also be captured with the dynamic model. The capability of the model in predicting the performance of UF/DF process as a function of protein characteristics and formulation conditions makes it a useful tool to improve process understanding and facilitate process development.

Hybrid Modeling for Simultaneous Prediction of Flux, Rejection Factor and Concentration in Two-Component Crossflow Ultrafiltration

Ultrafiltration is a powerful method used in virtually every pharmaceutical bioprocess. Depending on the process stage, the product-to-impurity ratio differs. The impact of impurities on the process depends on various factors. Solely mechanistic models are currently not sufficient to entirely describe these complex interactions. We have established two hybrid models for predicting the flux evolution, the protein rejection factor and two components’ concentration during crossflow ultrafiltration. The hybrid models were compared to the standard mechanistic modeling approach based on the stagnant film theory. The hybrid models accurately predicted the flux and concentration over a wide range of process parameters and product-to-impurity ratios based on a minimum set of training experiments. Incorporating both components into the modeling approach was essential to yielding precise results. The stagnant film model exhibited larger errors and no predictions regarding the impurity could be made, since it is based on the main product only. Further, the developed hybrid models exhibit excellent interpolation properties and enable both multi-step ahead flux predictions as well as time-resolved impurity forecasts, which is considered to be a critical quality attribute in many bioprocesses. Therefore, the developed hybrid models present the basis for next generation bioprocessing when implemented as soft sensors for real-time monitoring of processes.