Enhancing protein A productivity and resin utilization within integrated or intensified processes

A modular and multi-functional purification strategy that enables a common framework for manufacturing scale integrated and continuous biomanufacturing

Biopharmaceutical manufacture is transitioning from batch to integrated and continuous biomanufacturing (ICB). The common framework for most ICB, potentially enables a global biomanufacturing ecosystem utilizing modular and multi-function manufacturing equipment. Integrating unit operation hardware and software from multiple suppliers, complex supply chains enabled by multiple customized single-use flow paths, and large volume buffer production/storage make this ICB vision difficult to achieve with commercially available manufacturing equipment. Thus, we developed SymphonX™, a downstream processing skid with advanced buffer management capabilities, a single disposable generic flow path design that provides plug-and-play flexibility across all downstream unit operations and a single interface to reduce operational risk. Designed for multi-product and multi-process cGMP facilities, SymphonX™ can perform stand-alone batch processing or ICB. This study utilized an Apollo™ X CHO-DG44 mAb-expressing cell line in a steady-state perfusion bioreactor, harvesting product continuously with a cell retention device and connected SymphonX™ purification skids. The downstream process used the same chemistry (resins, buffer composition, membrane composition) as our historical batch processing platform, with SymphonX™ in-line conditioning and buffer concentrates. We used surge vessels between unit operations, single-column chromatography (protein A, cation and anion exchange) and two-tank batch virus inactivation. After the first polishing step (cation exchange), we continuously pooled product for 6 days. These 6 day pools were processed in batch-mode from anion exchange to bulk drug substance. This manufacturing scale proof-of-concept ICB produced 0.54 kg/day of drug substance with consistent product quality attributes and demonstrated successful bioburden control for unit-operations undergoing continuous operation.

Reviewing the process intensification landscape through the introduction of a novel, multitiered classification for downstream processing

A demand for process intensification in biomanufacturing has increased over the past decade due to the ever-expanding market for biopharmaceuticals. This is largely driven by factors such as a surge in biosimilars as patents expire, an aging population, and a rise in chronic diseases. With these market demands, pressure upon biomanufacturers to produce quality products with rapid turnaround escalates proportionally. Process intensification in biomanufacturing has been well received and accepted across industry based on the demonstration of its benefits of improved productivity and efficiency, while also reducing the cost of goods. However, while these benefits have been shown empirically, the challenges of adopting process intensification into industry remain, from smaller independent start-up to big pharma. Traditionally, moving from batch to a process intensification scheme has been viewed as an "all or nothing" approach involving continuous bioprocessing, in which the factors of complexity and significant capital costs hinder its adoption. In addition, the literature is crowded with a variety of terms used to describe process intensification (continuous, periodic counter-current, connected, intensified, steady-state, etc.). Often, these terms are used inappropriately or as synonyms, which generates confusion in the field. Through a detailed review of current state-of-the-art systems, consumables, and process intensification case studies, we herein propose a defined approach in the implementation of downstream process intensification through a standardized nomenclature and viewing it as distinct independent levels. These can function separately as intensified single-unit operations or be built upon by integration with other process steps allowing for simple, incremental, cost-effective implementation of process intensification in the manufacturing of biopharmaceuticals.

An automated high inoculation density fed-batch bioreactor, enabled through N-1 perfusion, accommodates clonal diversity and doubles titers

An important consideration for biopharmaceutical processes is the cost of goods (CoGs) of biotherapeutics manufacturing. CoGs can be reduced by dramatically increasing the productivity of the bioreactor process. In this study, we demonstrate that an intensified process which couples a perfused N-1 seed reactor and a fully automated high inoculation density (HID) N stage reactor substantially increases the bioreactor productivity as compared to a low inoculation density (LID) control fed-batch process. A panel of six CHOK1SV GS-KO® CHO cell lines expressing three different monoclonal antibodies was evaluated in this intensified process, achieving an average 85% titer increase and 132% space-time yield (STY) increase was demonstrated when comparing the 12-day HID process to a 15-day LID control process. These productivity increases were enabled by automated nutrient feeding in both the N-1 and N stage bioreactors using in-line process analytical technologies (PAT) and feedback control. The N-1 bioreactor utilized in-line capacitance to automatically feed the bioreactor based on a capacitance-specific perfusion rate (CapSPR). The N-stage bioreactor utilized in-line Raman spectroscopy to estimate real-time concentrations of glucose, phenylalanine, and methionine, which are held to target set points using automatic feed additions. These automated feeding methodologies were shown to be generalizable across six cell lines with diverse feed requirements. We show this new process can accommodate clonal diversity and reproducibly achieve substantial titer uplifts compared to traditional cell culture processes, thereby establishing a baseline technology platform upon which further increases bioreactor productivity and CoGs reduction can be achieved.

Concentration of clarified pool by single-pass tangential flow filtration to improve productivity of protein A capture step: Impact of clarification strategies

Protein A capture chromatography remains a high-cost and relatively low-productivity step for downstream processing of monoclonal antibodies. As bioprocessing transitions toward intensified processes, maximizing the efficiency of individual steps is key to achieving economic targets. This study was performed to assess the impact of inline concentration of clarified cell culture fluid (CCF), using single-pass tangential flow filtration, on protein A chromatography purification productivity. CCF with varying levels of impurities and turbidity were obtained dependent upon the clarification method. These CCFs were concentrated and processed over a protein A capture step. Productivity increases of 1.8- to 2.6-fold were achieved as compared to a protein A capture step with no CCF concentration. Achieving such targeted improvements requires careful consideration of the multiple components in the clarification strategy before implementation.

Online optimization of dynamic binding capacity and productivity by model predictive control

In preparative and industrial chromatography, the current viewpoint is that the dynamic binding capacity governs the process economy, and increased dynamic binding capacity and column utilization are achieved at the expense of productivity. The dynamic binding capacity in chromatography increases with residence time until it reaches a plateau, whereas productivity has an optimum. Therefore, the loading step of a chromatographic process is a balancing act between productivity, column utilization, and buffer consumption. This work presents an online optimization approach for capture chromatography that employs a residence time gradient during the loading step to improve the traditional trade-off between productivity and resin utilization. The approach uses the extended Kalman filter as a soft sensor for product concentration in the system and a model predictive controller to accomplish online optimization using the pore diffusion model as a simple mechanistic model. When a soft sensor for the product is placed before and after the column, the model predictive controller can forecast the optimal condition to maximize productivity and resin utilization. The controller can also account for varying feed concentrations. This study examined the robustness as the feed concentration varied within a range of 50%. The online optimization was demonstrated with two model systems: purification of a monoclonal antibody by protein A affinity and lysozyme by cation-exchange chromatography. Using the presented optimization strategy with a controller saves up to 43% of the buffer and increases the productivity together with resin utilization in a similar range as a multi-column continuous counter-current loading process.