A mixed-mode reversed-phase/strong-anion-exchange stationary phase: Analyte-retention stability and application in the analysis of nonsteroidal anti-inflammatory drugs.

Mixed-mode reversed-phase/anion-exchange chromatography (RP/AEX) is an effective method for the chromatographic analysis of acidic drugs because it combines reversed-phase chromatography (RP) with anion-exchange chromatography (AEX). However, the result repeatability for the RP/AEX analysis of acidic drugs is frequently compromised by the detrimental effects of residual silanol groups in an RP/AEX stationary phase on peak separation and analyte retention. In this study, an RP/weak-AEX stationary phase with amino anion-exchange groups, Sil-AA, was prepared. Subsequently, an RP/strong-AEX stationary phase, Sil-PBQA, was prepared by replacing the amino groups in Sil-AA with a benzene ring and a benzyl-containing quaternary ammonium salt. The chromatographic behaviors of Sil-PBQA and Sil-AA were compared, and the effect of residual silanol groups on the chromatographic behavior of an RP/AEX stationary phase was evaluated. Residual silanol groups not only caused additional electrostatic interactions for acidic analytes, but also competed with the analytes for the anion-exchange sites in an RP/AEX stationary phase. The effects of different salt-containing mobile-phase systems on the analyte-retention behavior of Sil-PBQA were investigated to develop a method that enhanced the repeatability of the RP/AEX acidic-analyte-analysis results obtained using Sil-PBQA and facilitated the separation of nonsteroidal anti-inflammatory drugs on Sil-PBQA. The ideas presented in this paper can improve the separation of peaks and repeatability of results in the RP/AEX analysis of acidic drugs.

Adjustable chromatographic performance of silica-based mixed-mode stationary phase through the control of co-grafting amounts of imidazole and C18 chain.

In this paper, three imidazole- and C18- bifunctional silica stationary phases (Sil-Im-C18) were prepared by adjusting introduction interval of octadecyltrichlorosilane (ODS) and 3-imidazol-1-ylpropyl(trimethoxy)silane (TMPImS), which can be used for reversed-phase liquid chromatography (RPLC) and ion exchange chromatography (IEC) with adjustable performance. The successful preparation of Sil-Im-C18 were confirmed by the characterizations of elemental analysis, infrared spectroscopy (FTIR) and contact angle (CA). Chromatographic performance of Sil-Im-C18 were evaluated by the separation of Tanaka test mixture, alkylbenzenes, linear PAHs and a set of analytes with different properties (uracil, phenol, 1,2-dinitrobenzene and naphthalene), and compared with commonly used C18 column. It was found that the chromatographic performance of Sil-Im-C18 changed significantly with the difference in bonding amount of imidazole and C18. Sil-Im-C18 demonstrated the excellent separation performance towards polycyclic aromatic hydrocarbons (PAHs), phenylesters, phenylamines, phenols and inorganic anions, and notably, nucleobases and nucleosides can be separated using pure water as mobile phases. The van Deemter plot showed that the column efficiency of Sil-Im-C18-3 was 64,933 plate·m-1 for naphthalene, indicated that Sil-Im-C18 was reasonably chromatographic columns. The RSD values of retention time were 0.22 %-0.61 % for 10 needles alkylbenzenes injected continuously at 50 °C to investigate thermal stability and repeatability, all the fluctuations of k of naphthalene were less than 2.3 % for Sil-Im-C18-1 during flushing 24 h with the mobile phase at different pH values (pH = 3 and 8), the retention time of alkylbenzenes were almost same for Sil-Im-C18-1 at different time, the RSD values of retention time of alkylbenzenes were 0.45 %-2.28 % for two batches Sil-Im-C18-1, revealing the excellent repeatability, thermal stability, durability and reproducibility of Sil-Im-C18, and implying a commercial prospect.

Purification of monoclonal antibodies using novel 3D printed ordered stationary phases.

3D printing offers the unprecedented ability to fabricate chromatography stationary phases with bespoke 3D morphology as opposed to traditional packed beds of spherical beads. The restricted range of printable materials compatible with chromatography is considered a setback for its industrial implementation. Recently, we proposed a novel ink that exhibits favourable printing performance (printing time ∼100 mL/h, resolution ∼200 µm) and broadens the possibilities for a range of chromatography applications thanks to its customisable surface chemistry. In this work, this ink was used to fabricate 3D printed ordered columns with 300 µm channels for the capture and polishing of therapeutic monoclonal antibodies. The columns were initially assessed for leachables and extractables, revealing no material propensity for leaching. Columns were then functionalised with protein A and SO3 ligands to obtain affinity and strong cation exchangers, respectively. 3D printed protein A columns showed >85 % IgG recovery from harvested cell culture fluid with purities above 98 %. Column reusability was evaluated over 20 cycles showing unaffected performance. Eluate samples were analysed for co-eluted protein A fragments, host cell protein and aggregates. Results demonstrate excellent HCP clearance (logarithmic reduction value of > 2.5) and protein A leakage in the range of commercial affinity resins (<100 ng/mg). SO3 functionalised columns employed for polishing achieved removal of leaked Protein A (down to 10 ng/mg) to meet regulatory expectations of product purity. This work is the first implementation of 3D printed columns for mAb purification and provides strong evidence for their potential in industrial bioseparations.

Fabrication and application of a continuously regenerated cationic impurity removal device for ion chromatography.

A continuously regenerated cationic impurity removal device (CR-CRD) has been fabricated and applied for ion chromatography (IC). The removal of cationic impurities is realized by electrodialytically replacing the cationic impurities with hydronium ions. The device is configured in a sandwich structure and the central eluent channel is respectively isolated from both electrodes by stacked cation exchange membranes and a bipolar membrane (BPM) plus stacked anion exchange membranes. The eluent channel is packed with cation exchange resins in hydronium form and their continuous regeneration can be achieved by electrodialysis. A desirable feature of the device is gas-free, and no degasser is required. It showed sufficient ability to remove cationic impurities, as indicated by > 99.9 % removal of 10 mL of 1 mM LiOH solution injected (∼10 µmol) or continuous removal of 1 mM LiOH solution at the flow rate of 1 mL/min (1 µmol/min). A useful application was for sample pretreatment in nuclear power industry, by eliminating strong matrix interference of the sample containing LiOH (1 mM) and boric acid (2000 mg/L) with trace anion analysis.

Targeted CQA analytical control strategy for commercial antibody products: Replacing ion-exchange chromatography methods for charge heterogeneity with multi-attribute monitoring.

Peptide mapping with mass spectrometry (MS) is an important tool for protein characterization in the biopharmaceutical industry. Historically, peptide mapping monitors post-translational modifications (PTMs) of protein products and process intermediates during development. Multi-attribute monitoring (MAM) methods have been used previously in commercial release and stability testing panels to ensure control of selected critical quality attributes (CQAs). Our goal is to use MAM methods as part of an overall analytical testing strategy specifically focused on CQAs, while removing or replacing historical separation methods that do not effectively distinguish CQAs from non-CQAs due to co-elution. For example, in this study, we developed a strategy to replace a profile-based ion-exchange chromatography (IEC) method using a MAM method in combination with traditional purity methods to ensure control of charge variant CQAs for a commercial antibody (mAb) drug product (DP). To support this change in commercial testing strategy, the charge variant CQAs were identified and characterized during development by high-resolution LC-MS and LC-MS/MS. The charge variant CQAs included PTMs, high molecular weight species, and low molecular weight species. Thus, removal of the IEC method from the DP specification was achieved using a validated LC-MS MAM method on a QDa system to directly measure the charge variant PTM CQAs in combination with size exclusion chromatography (SE-HPLC) and capillary electrophoresis (CE-SDS) to measure the non-PTM charge variant CQAs. Bridging data between the MAM, IEC, and SE-HPLC methods were included in the commercial marketing application to justify removing IEC from the DP specification. We have also used this MAM method as a test for identity to reduce the number of QC assays. This strategy has received approvals from several health authorities.

[Preparation of a macroporous anion exchange chromatographic medium by polyamine grafting and evaluation of its protein-adsorption behavior].

The macroporous anion exchange chromatographic medium (FastSep-PAA) was prepared through grafting polyallylamine (PAA) onto polyacrylate macroporous microspheres (FastSep-epoxy). The effects of the synthesis conditions, including the PAA concentration, reaction time, and reaction solution pH, on the ion exchange (IC) of the medium were investigated in detail. When the PAA concentration, reaction time, and reaction solution pH were increased, the IC of the medium increased, and optimal synthesis conditions were then selected in combination with changes of protein binding capacity. A scanning electron microscope was used to examine the surface morphology of the medium. The medium possessed high pore connectivity. Furthermore, the pore structure of the medium was preserved after the grafting of PAA onto the macroporous microspheres. This finding demonstrates that the density of the PAA ligands does not appear to have any discernible impact on the structure of the medium; that is, no difference in the structure of the medium is observed before and after the grafting of PAA onto the microspheres. The pore size and pore-size distribution of the medium before and after grafting were determined by mercury intrusion porosimetry and the nitrogen adsorption method to investigate the relationship between pore size (measured in the range of 300-1000 nm) and protein adsorption. When the pore size of the medium was increased, its protein binding capacity did not exhibit any substantial decrease. An increase in pore size may hasten the mass transfer of proteins within the medium. Among the media prepared, that with a pore size of 400 nm exhibited the highest dynamic-binding capacity (DBC: 70.3 g/L at 126 cm/h). The large specific surface area of the medium and its increased number of protein adsorption sites appeared to positively influence its DBC. When the flow rate was increased, the protein DBC decreased in media with original pore sizes of less than 700 nm. In the case of the medium with an original pore size of 1000 nm, the protein DBC was independent of the flow rate. The protein DBC decreased by 3.5% when the flow rate was increased from 126 to 628 cm/h. In addition, the protein DBC was maintained at 57.7 g/L even when the flow velocity was 628 cm/h. This finding reveals that the diffusion rate of protein molecules at this pore size is less restricted and that the prepared medium has excellent mass-transfer performance. These results confirm that the macroporous polymer anion exchange chromatographic medium developed in this study has great potential for the high-throughput separation of proteins.

Predicting protein retention in ion-exchange chromatography using an open source QSPR workflow.

Protein-based biopharmaceuticals require high purity before final formulation to ensure product safety, making process development time consuming. Implementation of computational approaches at the initial stages of process development offers a significant reduction in development efforts. By preselecting process conditions, experimental screening can be limited to only a subset. One such computational selection approach is the application of Quantitative Structure Property Relationship (QSPR) models that describe the properties exploited during purification. This work presents a novel open-source Python tool capable of extracting a range of features from protein 3D models on a local computer allowing total transparency of the calculations. As open-source tool, it also impacts initial investments in constructing a QSPR workflow for protein property prediction for third parties, making it widely applicable within the field of bioprocess development. The focus of current calculated molecular features is projection onto the protein surface by constructing surface grid representations. Linear regression models were trained with the calculated features to predict chromatographic retention times/volumes. Model validation shows a high accuracy for anion and cation exchange chromatography data (cross-validated R2 of 0.87 and 0.95). Hence, these models demonstrate the potential of the use of QSPR to accelerate process design.

Standardized approach for accurate and reliable model development of ion-exchange chromatography based on parameter-by-parameter method and consideration of extra-column effects.

Developing an accurate and reliable model for chromatographic separation that meets regulatory requirements and ensures consistency in model development remains challenging. In order to address this challenge, a standardized approach was proposed in this study with ion-exchange chromatography (IEC). The approach includes the following steps: liquid flow identification, system and column-specific parameters determination and validation, multi-component system identification, protein amount validation, steric mass action parameters determination and evaluation, and validation of the calibrated model's generalization ability. The parameter-by-parameter (PbP) calibration method and the consideration of extra-column effects were integrated to enhance the accuracy of the developed models. The experiments designed for implementing the PbP method (five gradient experiments for model calibration and one stepwise experiment for model validation) not only streamline the experimental workload but also ensure the extrapolation abilities of the model. The effectiveness of the standardized approach is successfully validated through an application about the IEC separation of industrial antibody variants, and satisfactory results were observed with R2 ≈ 0.9 for the majority of calibration and validation experiments. The standardized approach proposed in this work contributes significantly to improve the accuracy and reliability of the developed IEC models. Models developed using this standardized approach are ready to be applied to a broader range of industrial separation systems, and are likely find further applications in model-assisted decision-making of process development.

Profiling Protein-Protein Interactions in the Human Brain by Refined Cofractionation Mass Spectrometry.

Proteins usually execute their biological functions through interactions with other proteins and by forming macromolecular complexes, but global profiling of protein complexes directly from human tissue samples has been limited. In this study, we utilized cofractionation mass spectrometry (CF-MS) to map protein complexes within the postmortem human brain with experimental replicates. First, we used concatenated anion and cation Ion Exchange Chromatography (IEX) to separate native protein complexes in 192 fractions and then proceeded with Data-Independent Acquisition (DIA) mass spectrometry to analyze the proteins in each fraction, quantifying a total of 4,804 proteins with 3,260 overlapping in both replicates. We improved the DIA's quantitative accuracy by implementing a constant amount of bovine serum albumin (BSA) in each fraction as an internal standard. Next, advanced computational pipelines, which integrate both a database-based complex analysis and an unbiased protein-protein interaction (PPI) search, were applied to identify protein complexes and construct protein-protein interaction networks in the human brain. Our study led to the identification of 486 protein complexes and 10054 binary protein-protein interactions, which represents the first global profiling of human brain PPIs using CF-MS. Overall, this study offers a resource and tool for a wide range of human brain research, including the identification of disease-specific protein complexes in the future.

Mixed-mode size-exclusion silica resin for polishing human antibodies in flow-through mode.

The polishing step in the downstream processing of therapeutic antibodies removes residual impurities from Protein A eluates. Among the various classes of impurities, antibody fragments are especially challenging to remove due to the broad biomolecular diversity generated by a multitude of fragmentation patterns. The current approach to fragment removal relies on ion exchange or mixed-mode adsorbents operated in bind-and-gradient-elution mode. However, fragments that bear strong similarity to the intact product or whose biophysical features deviate from the ensemble average can elude these adsorbents, and the lack of a chromatographic technology enabling robust antibody polishing is recognized as a major gap in downstream bioprocessing. Responding to this challenge, this study introduces size-exclusion mixed-mode (SEMM) silica resins as a novel chromatographic adsorbent for the capture of antibody fragments irrespective of their biomolecular features. The pore diameter of the silica beads features a narrow distribution and is selected to exclude monomeric antibodies, while allowing their fragments to access the pores where they are captured by the mixed-mode ligands. The static and dynamic binding capacity of the adsorbent ranged respectively between 30-45 and 25-33 gs of antibody fragments per liter of resin. Selected SEMM-silica resins also demonstrated the ability to capture antibody aggregates, which adsorb on the outer layer of the beads. Optimization of the SEMM-silica design and operation conditions - namely, pore size (10 nm) and ligand composition (quaternary amine and alkyl chain) as well as the linear velocity (100 cm/h), ionic strength (5.7 mS/cm), and pH (7) of the mobile phase - afforded a significant reduction of both fragments and aggregates, resulting into a final antibody yield up to 80% and monomeric purity above 97%.

Automatic procedure for modelling, calibration, and optimization of a three-component chromatographic separation.

The current landscape of biopharmaceutical production necessitates an ever-growing set of tools to meet the demands for shorter development times and lower production costs. One path towards meeting these demands is the implementation of digital tools in the development stages. Mathematical modelling of process chromatography, one of the key unit operations in the biopharmaceutical downstream process, is one such tool. However, obtaining parameter values for such models is a time-consuming task that grows in complexity with the number of compounds in the mixture being purified. In this study, we tackle this issue by developing an automated model calibration procedure for purification of a multi-component mixture by linear gradient ion exchange chromatography. The procedure was implemented using the Orbit software (Lund University, Department of Chemical Engineering), which both generates a mathematical model structure and performs the experiments necessary to obtain data for model calibration. The procedure was extended to suggest operating points for the purification of one of the components in the mixture by means of multi-objective optimization using three different objectives. The procedure was tested on a three-component protein mixture and was able to generate a calibrated model capable of reproducing the experimental chromatograms to a satisfactory degree, using a total of six assays. An additional seventh experiment was performed to validate the model response under one of the suggested optimum conditions, respecting a 95 % purity requirement. All of the above was automated and set in motion by the push of a button. With these results, we have taken a step towards fully automating model calibration and thus accelerating digitalization in the development stages of new biopharmaceuticals.

Development of a method for the simultaneous determination of ionic nutrients in hydroponic solutions using cation-/anion-exchange chromatography with a neutral eluent.

Nutrient availability in hydroponic solutions must be accurately monitored to maintain crop productivity; however, few cost-effective, accurate, real-time, and long-term monitoring technologies have been developed. In this study, we describe the development and application of cation-/anion-exchange chromatography with a neutral eluent (20-mmol/L sodium formate, pH 7.87) for the simultaneous separation (within 50 min) of ionic nutrients, including K+, NH4+, NO2-, NO3-, and phosphate ion, in a hydroponic fertilizer solution. Using the neutral eluent avoided degradation of the separation column during precipitation of metal ion species, such as hydroxides, with an alkaline eluent and oxidation of NO2- to NO3- with an acidic eluent. The suitability of the current method for monitoring ionic components in a hydroponic fertilizer solution was confirmed. Based on our data, we propose a controlled fertilizer strategy to optimize fertilizer consumption and reduce the chemical load of drained fertilizer solutions.

Predicting multimodal chromatography of therapeutic antibodies using multiscale modeling.

Multimodal chromatography has emerged as a powerful method for the purification of therapeutic antibodies. However, process development of this separation technique remains challenging because of an intricate and molecule-specific interaction towards multimodal ligands, leading to time-consuming and costly experimental optimization. This study presents a multiscale modeling approach to predict the multimodal chromatographic behavior of therapeutic antibodies based on their sequence information. Linear gradient elution (LGE) experiments were performed on an anionic multimodal resin for 59 full-length antibodies, including five different antibody formats at pH 5.0, 6.0, and 7.0 that were used for parameter determination of a linear adsorption model at low loading density conditions. Quantitative structure-property relationship (QSPR) modeling was utilized to correlate the adsorption parameters with up to 1374 global and local physicochemical descriptors calculated from antibody homology models. The final QSPR models employed less than eight descriptors per model and demonstrated high training accuracy (R² > 0.93) and reasonable test set prediction accuracy (Q² > 0.83) for the adsorption parameters. Model evaluation revealed the significance of electrostatic interaction and hydrophobicity in determining the chromatographic behavior of antibodies, as well as the importance of the HFR3 region in antibody binding to the multimodal resin. Chromatographic simulations using the predicted adsorption parameters showed good agreement with the experimental data for the vast majority of antibodies not employed during the model training. The results of this study demonstrate the potential of sequence-based prediction for determining chromatographic behavior in therapeutic antibody purification. This approach leads to more efficient and cost-effective process development, providing a valuable tool for the biopharmaceutical industry.

In-line buffer exchange in the coupling of Protein A chromatography with weak cation exchange chromatography for the determination of charge variants of immunoglobulin G derived from chinese hamster ovary cell cultures.

Immunoglobulin G (IgG) is the most common monoclonal antibody (mAb) grown for therapeutic applications. While IgG is often selectively isolated from cell lines using protein A (ProA) chromatography, this is only a stepping stone for complete characterization. Further classification can be obtained from weak cation exchange chromatography (WCX) to determine IgG charge variant distributions. The charge variants of monoclonal antibodies can influence the stability and efficacy in vivo, and deviations in charge heterogeneity are often cell-specific and sensitive to upstream process variability. Current methods to characterize IgG charge variants are often performed off-line, meaning that the IgG eluate from the ProA separation is collected, diluted to adjust the pH, and then transferred to the WCX separation, adding time, complexity, and potential contamination to the sample analysis process. More recently, reports have appeared to streamline this separation using in-line two-dimensional liquid chromatography (2D-LC). Presented here is a novel, 2D-LC coupling of ProA in the first dimension (1D) and WCX in the second dimension (2D) chromatography. As anticipated, the initial direct column coupling proved to be challenging due to the pH incompatibility between the mobile phases for the two stages. To solve the solvent compatibility issue, a size exclusion column was placed in the switching valve loop of the 2D-LC instrument to act as a means for the on-line solvent exchange. The efficacy of the methodology presented was confirmed through a charge variant determination using the NIST monoclonal antibody standard (NIST mAb), yielding correct acidic, main, and basic variant compositions. The methodology was employed to determine the charge variant profile of IgG from an in-house cultured Chinese hamster ovary (CHO) cell supernatant. It is believed that this methodology can be easily implemented to provide higher-throughput assessment of IgG charge variants for process monitoring and cell line development.

Digital twin in high throughput chromatographic process development for monoclonal antibodies.

The monoclonal antibody (mAb) industry is becoming increasingly digitalized. Digital twins are becoming increasingly important to test or validate processes before manufacturing. High-Throughput Process Development (HTPD) has been progressively used as a tool for process development and innovation. The combination of High-Throughput Screening with fast computational methods allows to study processes in-silico in a fast and efficient manner. This paper presents a hybrid approach for HTPD where equal importance is given to experimental, computational and decision-making stages. Equilibrium adsorption isotherms of 13 protein A and 16 Cation-Exchange resins were determined with pure mAb. The influence of other components in the clarified cell culture supernatant (harvest) has been under-investigated. This work contributes with a methodology for the study of equilibrium adsorption of mAb in harvest to different protein A resins and compares the adsorption behavior with the pure sample experiments. Column chromatography was modelled using a Lumped Kinetic Model, with an overall mass transfer coefficient parameter (kov). The screening results showed that the harvest solution had virtually no influence on the adsorption behavior of mAb to the different protein A resins tested. kov was found to have a linear correlation with the sample feed concentration, which is in line with mass transfer theory. The hybrid approach for HTPD presented highlights the roles of the computational, experimental, and decision-making stages in process development, and how it can be implemented to develop a chromatographic process. The proposed white-box digital twin helps to accelerate chromatographic process development.

Evaluation of a novel stationary phase for the separation of lactose and isomers in lactose-free products using high-performance anion-exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD).

Lactose intolerance is a widespread condition, which prevents a large number of people from consuming dairy products as a part of their daily diet. It is estimated that an average of 65% of the global population is suffering from lactose intolerance. The global market for 'lactose-free' dairy products is rapidly growing and the criteria for 'lactose-free' labelled products are becoming stricter. To check the lactose contents in these products there is a need for fast, sensitive, and selective analytical method. A method is presented for fast and sensitive determination of lactose and its isomers using High-Performance Anion Exchange Chromatography in combination with Pulsed Amperometric Detection (HPAEC-PAD). The use of a new anion-exchange column, SweetSep™ AEX200, which is a strong anion-exchange column with highly monodisperse 5 µm particles, allowed the separation of all compounds of interest in less than 8 min with high resolution. A variety of dairy products were analyzed to demonstrate the versatility of the method.

Realization of digital twin for dynamic control toward sample variation of ion exchange chromatography in antibody separation.

Digital twin (DT) is a virtual and digital representation of physical objects or processes. In this paper, this concept is applied to dynamic control of the collection window in the ion exchange chromatography (IEC) toward sample variations. A possible structure of a feedforward model-based control DT system was proposed. Initially, a precise IEC mechanistic model was established through experiments, model fitting, and validation. The average root mean square error (RMSE) of fitting and validation was 8.1% and 7.4%, respectively. Then a model-based gradient optimization was performed, resulting in a 70.0% yield with a remarkable 11.2% increase. Subsequently, the DT was established by systematically integrating the model, chromatography system, online high-performance liquid chromatography, and a server computer. The DT was validated under varying load conditions. The results demonstrated that the DT could offer an accurate control with acidic variants proportion and yield difference of less than 2% compared to the offline analysis. The embedding mechanistic model also showed a positive predictive performance with an average RMSE of 11.7% during the DT test under >10% sample variation. Practical scenario tests indicated that tightening the control target could further enhance the DT robustness, achieving over 98% success rate with an average yield of 72.7%. The results demonstrated that the constructed DT could accurately mimic real-world situations and perform an automated and flexible pooling in IEC. Additionally, a detailed methodology for applying DT was summarized.

Universal ion chromatography method for anions in active pharmaceutical ingredients enabled by computer-assisted separation modeling.

Ion Chromatography (IC) is one of the most widely used methods for analyzing ionic species in pharmaceutical samples. A universal IC method that can separate a wide range of different analytes is highly desired as it can save a lot of time for method development and validation processes. Herein we report the development of a universal method for anions in active pharmaceutical ingredients (APIs) using computer-assisted chromatography modeling tools. We have screened three different IC columns (Dionex IonPac AS28-Fast 4 µm, AS19 4 µm and AS11-HC 4 µm) to determine the best suitable column for universal IC method development. A universal IC method was then developed using an AS11-HC 4 µm column to separate 31 most common anionic substances in 36 mins. This method was optimized using LC Simulator and a model which precisely predicts the retention behavior of 31 anions was established. This model demonstrated an excellent match between predicted and experimental analyte retention time (R2 =0.999). To validate this universal IC method, we have studied the stability of sulfite and sulfide analytes in ambient conditions. The method was then validated for a subset of 29 anions using water and organic solvent/water binary solvents as diluents for commercial APIs. This universal IC method provides an efficient and simple way to separate and analyze common anions in APIs. In addition, the method development process combined with LC simulator modeling can be effectively used as a starting point during method development for other ions beyond those investigated in this study.

Mechanistic modeling of empty-full separation in recombinant adeno-associated virus production using anion-exchange membrane chromatography.

Recombinant adeno-associated viral vectors (rAAVs) have become an industry-standard technology in the field of gene therapy, but there are still challenges to be addressed in their biomanufacturing. One of the biggest challenges is the removal of capsid species other than that which contains the gene of interest. In this work, we develop a mechanistic model for the removal of empty capsids-those that contain no genetic material-and enrichment of full rAAV using anion-exchange membrane chromatography. The mechanistic model was calibrated using linear gradient experiments, resulting in good agreement with the experimental data. The model was then applied to optimize the purification process through maximization of yield studying the impact of mobile phase salt concentration and pH, isocratic wash and elution length, flow rate, percent full (purity) requirement, loading density (challenge), and the use of single-step or two-step elution modes. A solution from the optimization with purity of 90% and recovery yield of 84% was selected and successfully validated, as the model could predict the recovery yield with remarkable fidelity and was able to find process conditions that led to significant enrichment. This is, to the best of our knowledge, the first case study of the application of de novo mechanistic modeling for the enrichment of full capsids in rAAV manufacturing, and it serves as demonstration of the potential of mechanistic modeling in rAAV process development.

Tuning mobile phase properties to improve empty and full particle separation in adeno-associated virus productions by anion exchange chromatography.

In the past decade, recombinant adeno-associated virus (rAAV) has gained increased attention as a prominent gene therapy technology to treat monogenetic diseases. One of the challenges in rAAV production is the enrichment of full rAAV particles containing the gene of interest (GOI) payload. By adjusting the mobile phase properties of anion-exchange chromatography (AEX), it was demonstrated that empty and full separation of rAAV was improved in monolith based preparative AEX chromatography. When compared to the baseline method using NaCl, the use of tetraethylammonium acetate (TEA-Ac) in the AEX mobile phase resulted in enhanced resolution from 0.75 to 1.23 between "Empty" and "Full" peaks by salt linear gradient elution, as well as increased the percentage of full rAAV particles from 20% to 36% and genome recovery from 59% to 62%. Furthermore, a dual wash plus step elution AEX method was developed. Wherein, the first wash step harnesses TEA-Ac to separate empty and full capsids, which is followed by a second wash step that ensures no TEA-Ac salt is carried over into AEX eluate. The resulting optimized AEX purification method has the potential to be adapted for manufacturing and purification processes involving various rAAV production platforms that experience empty and full rAAV separation challenges.