Development of an integrated continuous PEGylation and purification Process for granulocyte colony stimulating factor

Convolutional Neural Networks Guided Raman Spectroscopy as a Process Analytical Technology (PAT) Tool for Monitoring and Simultaneous Prediction of Monoclonal Antibody Charge Variants

BACKGROUND

Charge related heterogeneities of monoclonal antibody (mAb) based therapeutic products are increasingly being considered as a critical quality attribute (CQA). They are typically estimated using analytical cation exchange chromatography (CEX), which is time consuming and not suitable for real time control. Raman spectroscopy coupled with artificial intelligence (AI) tools offers an opportunity for real time monitoring and control of charge variants.

OBJECTIVE

We present a process analytical technology (PAT) tool for on-line and real-time charge variant determination during process scale CEX based on Raman spectroscopy employing machine learning techniques.

METHOD

Raman spectra are collected from a reference library of samples with distribution of acidic, main, and basic species from 0-100% in a mAb concentration range of 0-20 g/L generated from process-scale CEX. The performance of different machine learning techniques for spectral processing is compared for predicting different charge variant species.

RESULT

A convolutional neural network (CNN) based model was successfully calibrated for quantification of acidic species, main species, basic species, and total protein concentration with R2 values of 0.94, 0.99, 0.96 and 0.99, respectively, and the Root Mean Squared Error (RMSE) of 0.1846, 0.1627, and 0.1029 g/L, respectively, and 0.2483 g/L for the total protein concentration.

CONCLUSION

We demonstrate that Raman spectroscopy combined with AI-ML frameworks can deliver rapid and accurate determination of product related impurities. This approach can be used for real time CEX pooling decisions in mAb production processes, thus enabling consistent charge variant profiles to be achieved.

Continuous manufacturing of monoclonal antibodies: Dynamic control of multiple integrated polishing chromatography steps using BioSMB

We propose a strategy for automation and control of multi-step polishing chromatography in integrated continuous manufacturing of monoclonal antibodies. The strategy is demonstrated for a multi-step polishing process consisting of cation exchange chromatography in bind-and-elute mode followed by mixed-mode chromatography in flowthrough mode. A BioSMB system with a customized Python control layer is used for automation and scheduling of both the chromatography steps. Further, the BioSMB valve manifold is leveraged for in-line conditioning between the two steps, as tight control of pH and conductivity is essential when operating with multimodal resins because even slight fluctuations in load conditions adversely affect the chromatography performance. The pH and conductivity of the load to the multimodal chromatography columns is consistent, despite the elution gradient of the preceding cation exchange chromatography step. Inputs from the BioSMB pH and conductivity sensors are used for real-time control of the 7 pumps and 240 valves to achieve in-line conditioning inside the BioSMB manifold in a fully automated manner. This is confirmed by showcasing different elution strategies in cation exchange chromatography, including linear gradient, step gradient and process deviations like tubing leakage. In all the above cases, the model was able to maintain the pH and conductivity of multimodal chromatography load within the range of 6 ± 0.1 pH and 7 ± 0.3 mS/cm conductivity. The strategy eliminates the need for using multiple BioSMB units or integrating external pumps, valves, mixers, surge tanks, or sensors between the two steps as is currently the standard approach, thus offering a simple and robust structure for integrating multiple polishing chromatography steps in continuous downstream monoclonal antibody purification trains.

Membrane-Based Hybrid Method for Purifying PEGylated Proteins

PEGylated proteins are usually purified using chromatographic methods, which are limited in terms of both speed and scalability. In this paper, we describe a microfiltration membrane-based hybrid method for purifying PEGylated proteins. Polyethylene glycol (or PEG) is a lower critical solution temperature polymer which undergoes phase transition in the presence of a lyotropic salt and forms micelle-like structures which are several microns in size. In the proposed hybrid method, the PEGylated proteins are first converted to their micellar form by the addition of a lyotropic salt (1.65 M ammonium sulfate). While the micelles are retained using a microfiltration membrane, soluble impurities such as the unmodified protein are washed out through the membrane. The PEGylated proteins thus retained by the membrane are recovered by solubilizing them by removing the lyotropic salt. Further, by precisely controlling the salt removal, the different PEGylated forms of the protein, i.e., mono-PEGylated and di-PEGylated forms, are fractionated from each other. Hybrid separation using two different types of microfiltration membrane devices, i.e., a stirred cell and a tangential flow filtration device, are examined in this paper. The membrane-based hybrid method for purifying PEGylated proteins is both fast and scalable.

Enhancement of oral bioavailability and anti-colitis effect of luteolin-loaded polymer micelles with RA (rosmarinic acid)-SS-mPEG as carrier

OBJECTIVE

Polymer micelles were prepared (L-RSPMs) with luteolin and synthetic RA-SS-mPEG polymeric material before evaluation of their anti-inflammatory effect on 2, 4, 6-trinitro-benzene-sulfonic acid (TNBS)-induced ulcerative colitis (UC) model in rats.

METHODS

The synthetic RA-SS-mPEG was characterized with NMR spectroscopy, before preparation of luteolin-coated RA-SS-mPEG polymer micelles. The in vitro characterization and evaluation of the formulation were accomplished, couple with its pharmacokinetic parameters. The levels of PEG2, MDA, CRP and GSH, as well as concentrations of TNF-α, IL1-β, IL-6 and IL-10 in serum and colon tissue were detected via ELISA kit. The degree of colon injury and inflammation was evaluated via histopathologic examination.

RESULTS

L-RSPMs displayed small average droplet size (133.40 ± 4.52 nm), uniformly dispersed (PDI: 0.163 ± 0.011), good stability, slow release and enhanced solubility. We observed 353.28% increase in the relative bioavailability of L-RSPMs compared to free luteolin, while the half-life of the micelle was extended by 6.16h. Compared to model (M) group, luteolin (low and high doses) and L-RSPMs (low and high doses) significantly reduced levels of MDA, PEG2, CRP, TNF-α, IL-6 and IL-1β in colon tissue and serum of colitic rats but dose dependently increased IL-10 and SOD levels (p < 0.01). Histopathologic examination of colon showed that luteolin (low and high doses) and L-RSPMs (low and high doses) improved colonic inflammation in colitic rats to varying degrees compared to M group.

CONCLUSION

L-RSPMs could improve TNBS-induced colon inflammation by enhancing bioavailability, promoting antioxidant effects and regulating cytokine release, which may become a potential agent for UC treatment in clinical settings.

Design and economic investigation of a Multicolumn Countercurrent Solvent Gradient Purification unit for the separation of an industrially relevant PEGylated protein

Conjugation of biopharmaceuticals to polyethylene glycol chains, known as PEGylation, is nowadays an efficient and widely exploited strategy to improve critical properties of the active molecule, including stability, biodistribution profile, and reduced clearance. A crucial step in the manufacturing of PEGylated drugs is the purification. The reference process in industrial settings is single-column chromatography, which can meet the stringent purity requisites only at the expenses of poor product recoveries. A valuable solution to this trade-off is the Multicolumn Countercurrent Solvent Gradient Purification (MCSGP), which allows the internal and automated recycling of product-containing side fractions that are typically discarded in the batch processes. In this study, an ad hoc design procedure was applied to the single-column batch purification of an industrially relevant PEGylated protein, with the aim of defining optimal collection window, elution duration and elution buffer ionic strength to be then transferred to the MCSGP. This significantly alleviates the design of the continuous operation, subjected to manifold process parameters. The MCSGP designed by directly transferring the optimal parameters allowed to improve the yield and productivity by 8.2% and 17.8%, respectively, when compared to the corresponding optimized batch process, ensuring a purity specification of 98.0%. Once the efficacy of MCSGP was demonstrated, a detailed analysis of its cost of goods was performed and compared to the case of single-column purification. To the best of our knowledge, this is the first example of a detailed economic investigation of the MCSGP across different manufacturing scenarios and process cadences of industrial relevance, which demonstrated not only the viability of this continuous technology but also its flexibility.

Moving Protein PEGylation from an Art to a Data Science

PEGylation is a well-established and clinically proven half-life extension strategy for protein delivery. Protein modification with amine-reactive poly(ethylene glycol) (PEG) generates heterogeneous and complex bioconjugate mixtures, often composed of several PEG positional isomers with varied therapeutic efficacy. Laborious and costly experiments for reaction optimization and purification are needed to generate a therapeutically useful PEG conjugate. Kinetic models which accurately predict the outcome of so-called “random” PEGylation reactions provide an opportunity to bypass extensive wet lab experimentation and streamline the bioconjugation process. In this study, we propose a protein tertiary structure-dependent reactivity model that describes the rate of protein-amine PEGylation and introduces “PEG chain coverage” as a tangible metric to assess the shielding effect of PEG chains. This structure-dependent reactivity model was implemented into three models (linear, structure-based, and machine-learned) to gain insight into how protein-specific molecular descriptors (exposed surface areas, pK_a, and surface charge) impacted amine reactivity at each site. Linear and machine-learned models demonstrated over 75% prediction accuracy with butylcholinesterase. Model validation with Somavert, PEGASYS, and phenylalanine ammonia lyase showed good correlation between predicted and experimentally determined degrees of modification. Our structure-dependent reactivity model was also able to simulate PEGylation progress curves and estimate “PEGmer” distribution with accurate predictions across different proteins, PEG linker chemistry, and PEG molecular weights. Moreover, in-depth analysis of these simulated reaction curves highlighted possible PEG conformational transitions (from dumbbell to brush) on the surface of lysozyme, as a function of PEG molecular weight.

Enablers of continuous processing of biotherapeutic products

The benefits of continuous processing over batch manufacturing are widely acknowledged across the biopharmaceutical industry, primary of which are higher productivity and greater consistency in product quality. Furthermore, the reduced equipment and facility footprint lead to significantly lower capital costs. Technology enablers have a major role in this migration from batch to continuous processing. In this review, we highlight the various enablers that are facilitating adoption of continuous upstream and downstream bioprocessing. This includes new bioreactors and cell retention devices for upstream operations, and on-column and continuous flow refolding, novel continuous chromatography, and single-pass filtration systems for downstream processes. We also elucidate the significant roles of process integration and control as well as of data analytics in these processes.

APB-F1, a long-acting feline granulocyte colony-stimulating factor fusion protein, created by exploiting FL335, a chimeric Fab specific for feline serum albumin

Off-label use of a human granulocyte colony stimulating factor (hG-CSF) has been allowed to treat dogs and cats with neutropenia. However, repeated administration of hG-CSF induces undesirable anti-drug antibody (ADA) responses, implying the necessity of animal-derived G-CSF as a therapeutic reagent, preferably with a long-acting capability. Herein, we generated a recombinant fusion protein by genetically combining FL335, a chimeric Fab specific for feline serum albumin (FSA), and feline G-CSF (fG-CSF), with the ultimate goal of developing a long-acting therapeutic fG-CSF for cats. The resulting FL335-fG-CSF fusion protein, referred to as APB-F1, was produced well as a functional form in a Chinese hamster ovary (CHO) expression system. In in vitro analyses, APB-F1 bound to FSA at high affinity (K_D = 400 pM) and possessed 0.78 × 10⁷ U/mg G-CSF biological activity, clearly proving its biological functionality. Pharmacokinetic (PK) and pharmacodynamic (PD) studies using healthy cats revealed that the serum half-life (t_1/2) of APB-F1 was increased five times compared with that of fG-CSF (t_1/2 = 13.3 h vs. 2.7 h) in subcutaneous (SC) injections. Additionally, APB-F1 induced a profound and sustained increase in white blood cell (WBC) and actual neutrophil count (ANC) up to 10 days, which was far superior to other G-CSF preparations, including filgrastim (Neupogen™) and even pegfilgrastim (Neulasta™). Conclusively, a long-acting fG-CSF with potent in vivo bioactivity was successfully created by using FL335; thus, we provided evidence that our "anti-serum albumin Fab-associated" (SAFA) technology can be applied reliably in developing valuable long-acting biologics in veterinary medicine.