On-line PAT based monitoring and control of resin aging in protein A chromatography for COGs reduction.

Resin aging is a common occurrence in chromatographic processes and generally influenced by factors such as cleaning procedure and composition of the feed stream. Two major events occur along with protein fouling, one is the loss of protein A ligand and the other is non-specific, irreversible interactions of foulants with resin particles. Both these are responsible for resin aging. As a result, the performance of the resin suffers a fall, and this can be quantified through indicators like reduction in dynamic binding capacity, increased column pressure, or peak broadening. The number of reuse cycles of a resin has a major influence on the cost per batch. This is even more significant in the case of protein A resin, which is the primary cost driver for downstream processing. In this work, we first identify chromatogram characteristics that correlate to resin aging. Next, we propose a data monitoring-based tool for prediction of resin aging. Principal component analysis of the UV data of Mab 1 showed a deviation at 120th cycle and an out of specification at around 149th cycle, corroborating with yield decline. Batch level modelling could deliver a predictable trend for resin aging and was demonstrated for two different Mabs (Mab1 and Mab2). The results demonstrate that significant resin aging can be detected 20-25 cycles prior to observable yield decline. A control strategy has been suggested such that once the deviation has been detected, additional resin cleaning is triggered. Overall, a 50-100 Protein A cycle enhancement in resin lifespan could be achieved.

Multi-wavelength UV-based PAT tool for measuring protein concentration.

Process chromatography is commonly used for purification of therapeutic proteins. Most chromatography skids that are used in such operations utilize single ultraviolet (UV) absorbance for monitoring and quantification of protein content. While the signal from such UV measurement is linear with respect to protein concentration at low values of protein concentrations, as the concentration increases across an eluting product peak, it goes manifold over the linear range, resulting in saturation of the UV signal and as a result incomplete quantification of the protein concentration. This can hamper our ability to decide on where to pool the process chromatography peak. It is evident that a simple, fast, and cost-effective methodology for on-line estimation of protein concentration is the need of the hour. In this paper, a multi-wavelength UV-based approach has been proposed for dilution-free on-line concentration estimation in the range of 0.8-100 g/L. Stable absorbance regions are picked up in the proposed approach from the multi-wavelength UV spectra, thereby offering a solution to the problem of saturation and non-linearity of the UV signal that is otherwise observed at higher concentrations. Further, using chemometrics tools such as principal component analysis (PCA) and partial least squares (PLS), the model has been validated for rapid quantification of protein concentration from the spectra. The predictions from the model were comparable to values measured using an existing UV-based offline method with an R2 of>98%. The proposed process analytical technology (PAT) tool was successfully tested online and exhibited<8% variability and could effectively be used from capture to formulation to enable dilution-free online concentration measurement of IgG. The proposed tool is a simple, low-cost alternative to other methods and could enable integrated/continuous operations throughout the downstream train.