Enhancing Host-Cell Protein Detection in Protein Therapeutics Using HILIC Enrichment and Proteomic Analysis.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics approaches have been widely used to identify residual host-cell proteins (HCPs) in support of process and product characterization for protein therapeutics. Particularly, these methods can provide a general and unbiased approach for the detection of HCPs and may generate critical information on HCPs that are outside the coverage provided by a conventional immunoassay. A significant technical hurdle for HCP analysis is the overwhelmingly large background of biotherapeutic that obscures HCP detection and quantification. In this work, we developed a method that relies on hydrophilic interaction chromatography (HILIC) for HCP enrichment followed by in situ concentration and digestion prior to LC-MS analysis. This approach has enabled detection of HCPs in a drug substance that were not observed in other conventional flow rate LC-MS strategies. For example, 28% of HCPs identified in NISTmAb (20 out of 71) were not previously published or identified by established methods such as the native digestion technique. For an IgG1 protein spiked with 1000 ppm HCP standards, we detected 83 HCPs, 61 out of which were not identified by the native digestion method. Similar improvement in performance was demonstrated for an Fc-fusion protein therapeutic. Our method can be readily implemented in most protein mass spectrometry laboratories to support process development for protein therapeutics.

Subunit mass analysis for monitoring multiple attributes of monoclonal antibodies.

RATIONALE: Multi-Attribute Methods (MAMs) are appealing due to their ability to provide data on multiple molecular attributes from a single assay. If fully realized, such tests could reduce the number of assays required to support a product control strategy while providing equivalent or greater product understanding relative to the conventional approach. In doing so, MAMs have the potential to decrease development and manufacturing costs by reducing the number of tests in a release panel. METHODS: In this work, we report a MAM which is based on subunit mass analysis. RESULTS: The MAM assay is shown to be suitable for use as a combined method for identity testing, glycan profiling, and protein ratio determination for co-formulated monoclonal antibody (mAb) drugs. This is achieved by taking advantage of the high mass accuracy and relative quantification capabilities of intact mass analysis using quadrupole time-of-flight mass spectrometry (Q-TOF MS). Protein identification is achieved by comparing the measured masses of light chain (LC) and heavy chain (HC) mAbs against their theoretical values. Specificity is based on instrument mass accuracy. Glycan profiling and relative protein ratios are determined by the relative peak intensities of the protein HC glycoforms and LC glycoforms, respectively. Results for these relative quantifications agree well with those obtained by the conventional hydrophilic interaction liquid chromatography (HILIC) and reversed-phase LC methods. CONCLUSIONS: The suitability of this MAM for use in a quality control setting is demonstrated through assessment specificity for mAb identity, and accuracy, precision, linearity and robustness for glycan profiling and ratio determination. Results from this study indicate that a MAM with subunit mass analysis has the potential to replace three conventional methods widely used for mAb release testing including identification assay, glycosylation profiling, and ratio determination for co-formulated mAbs.

Impact of Tryptophan Oxidation in Complementarity-Determining Regions of Two Monoclonal Antibodies on Structure-Function Characterized by Hydrogen-Deuterium Exchange Mass Spectrometry and Surface Plasmon Resonance.

PURPOSE: Tryptophan's (Trp) unique hydrophobic and structural properties make it an important antigen binding motif when positioned in complementarity-determining regions (CDRs) of monoclonal antibodies (mAbs). Oxidation of Trp residues within the CDR can deleteriously impact antigen binding, particularly if the CDR conformation is altered. The goal of this study was to evaluate the conformational and functional impact of Trp oxidation for two mAb subtypes, which is essential in determining the structure-function relationship and establishing appropriate analytical control strategies during protein therapeutics development. METHODS: Selective Trp oxidation was induced by 2,2'-Azobis(2-amidinopropane) dihydrochloride (AAPH) treatment in the presence of free methionine (Met). The native and chemically oxidized mAbs were characterized by hydrogen-deuterium exchange mass spectrometry (HDX-MS) for conformational changes and surface plasmon resonance (SPR) for antigen-antibody binding. RESULTS: Treatment of mAbs with AAPH selectively oxidized solvent accessible Trp residues. Oxidation of Trp within or in proximity of CDRs increased conformational flexibility in variable domains and disrupted antigen binding. CONCLUSIONS: Trp oxidation in CDRs can adversely impact mAbs' conformation and antigen binding. Trp oxidation should be carefully evaluated as part of critical quality attribute assessments. Oxidation susceptible Trp should be closely monitored during process development for mAbs to establish appropriate analytical control for manufacturing of drug substance and drug product.

Rheology Guided Rational Selection of Processing Temperature To Prepare Copovidone-Nifedipine Amorphous Solid Dispersions via Hot Melt Extrusion (HME).

The production of amorphous solid dispersions via hot melt extrusion (HME) relies on elevated temperature and prolonged residence time, which can result in potential degradation and decomposition of thermally sensitive components. Herein, the rheological properties of a physical mixture of polymer and an active pharmaceutical ingredient (API) were utilized to guide the selection of appropriate HME processing temperature. In the currently studied copovidone-nifedipine system, a critical temperature, which is substantially lower (∼13 °C) than the melting point of crystalline API, was captured during a temperature ramp examination and regarded as the critical point at which the API could molecularly dissolve into the polymer. Based on the identification of this critical point, various solid dispersions were prepared by HME processing below, at, and above the critical temperature (both below and above the melting temperature (Tm) of crystalline API). In addition, the resultant extrudates along with two control solid dispersions prepared by physical mixing and cryogenic milling were assessed by X-ray diffraction, differential scanning calorimetry, hot stage microscopy, rheology, and solid-state NMR. Physicochemical properties of resultant solid dispersions indicated that the identified critical temperature is sufficient for the polymer-API system to reach a molecular-level mixing, manifested by the transparent and smooth appearance of extrudates, the absence of API crystalline diffraction and melting peaks, dramatically decreased rheological properties, and significantly improved polymer-API miscibility. Once the critical temperature has been achieved, further raising the processing temperature only results in limited improvement of API dispersion, reflected by slightly reduced storage modulus and complex viscosity and limited improvement in miscibility.

Solid-State Spectroscopic Investigation of Molecular Interactions between Clofazimine and Hypromellose Phthalate in Amorphous Solid Dispersions.

It has been technically challenging to specify the detailed molecular interactions and binding motif between drugs and polymeric inhibitors in the solid state. To further investigate drug-polymer interactions from a molecular perspective, a solid dispersion of clofazimine (CLF) and hypromellose phthalate (HPMCP), with reported superior amorphous drug loading capacity and physical stability, was selected as a model system. The CLF-HPMCP interactions in solid dispersions were investigated by various solid state spectroscopic methods including ultraviolet-visible (UV-vis), infrared (IR), and solid-state NMR (ssNMR) spectroscopy. Significant spectral changes suggest that protonated CLF is ionically bonded to the carboxylate from the phthalyl substituents of HPMCP. In addition, multivariate analysis of spectra was applied to optimize the concentration of polymeric inhibitor used to formulate the amorphous solid dispersions. Most interestingly, proton transfer between CLF and carboxylic acid was experimentally investigated from 2D 1H-1H homonuclear double quantum NMR spectra by utilizing the ultrafast magic-angle spinning (MAS) technique. The molecular interaction pattern and the critical bonding structure in CLF-HPMCP dispersions were further delineated by successfully correlating ssNMR findings with quantum chemistry calculations. These high-resolution investigations provide critical structural information on active pharmaceutical ingredient-polymer interaction, which can be useful for rational selection of appropriate polymeric carriers, which are effective crystallization inhibitors for amorphous drugs.

Novel endosomolytic poly(amido amine) polymer conjugates for systemic delivery of siRNA to hepatocytes in rodents and nonhuman primates.

The application of small interfering (si)RNAs as potential therapeutic agents requires safe and effective methods for their delivery to the cytoplasm of the target cells and tissues. Recent studies have shown significant progress in the development of targeting reagents that facilitate the recognition of, and siRNA delivery to, specific cell types. Among recently reported delivery approaches, polymers with amphipathic properties have been used to enable endosome escape and cytosolic delivery. Here, we describe a linear amphipathic poly(amido amine) polymer conjugate system for the efficient siRNA delivery in vitro and in vivo. This polymer contains a novel amine bearing bis-acrylamide monomer designed for increasing amine density, which resulted in substantial improvement in liver uptake and RNAi activity compared to our previously reported poly(amido amine disulfide) polymer.1 The activity for this liver targeted delivery system was demonstrated in rodents and nonhuman primates.

Improving the in vivo therapeutic index of siRNA polymer conjugates through increasing pH responsiveness.

Polymer based carriers that aid in endosomal escape have proven to be efficacious siRNA delivery agents in vitro and in vivo; however, most suffer from cytotoxicity due in part to a lack of selectivity for endosomal versus cell membrane lysis. For polymer based carriers to move beyond the laboratory and into the clinic, it is critical to find carriers that are not only efficacious, but also have margins that are clinically relevant. In this paper we report three distinct categories of polymer conjugates that improve the selectivity of endosomal membrane lysis by relying on the change in pH associated with endosomal trafficking, including incorporation of low pKa heterocycles, acid cleavable amino side chains, or carboxylic acid pH sensitive charge switches. Additionally, we determine the therapeutic index of our polymer conjugates in vivo and demonstrate that the incorporation of pH responsive elements dramatically expands the therapeutic index to 10-15, beyond that of the therapeutic index (less than 3), for polymer conjugates previously reported.

Rapid total sialic acid monitoring during cell culture process using a machine learning model based soft sensor.

Total sialic acid content (TSA) in biotherapeutic proteins is often a critical quality attribute as it impacts the drug efficacy. Traditional wet chemical assays to quantify TSA in biotherapeutic proteins during cell culture typically takes several hours or longer due to the complexity of the assay which involves isolation of sialic acid from the protein of interest, followed by sample preparation and chromatographic based separation for analysis. Here, we developed a machine learning model-based technology to rapidly predict TSA during cell culture by using typically measured process parameters. The technology features a user interface, where the users only have to upload cell culture process parameters as input variables and TSA values are instantly displayed on a dashboard platform based on the model predictions. In this study, multiple machine learning algorithms were assessed on our dataset, with the Random Forest model being identified as the most promising model. Feature importance analysis from the Random Forest model revealed that attributes like viable cell density (VCD), glutamate, ammonium, phosphate, and basal medium type are critical for predictions. Notably, while the model demonstrated strong predictability by Day 14 of observation, challenges remain in forecasting TSA values at the edges of the calibration range. This research not only emphasizes the transformative power of machine learning and soft sensors in bioprocessing but also introduces a rapid and efficient tool for sialic acid prediction, signaling significant advancements in bioprocessing. Future endeavors may focus on data augmentation to further enhance model precision and exploration of process control capabilities.

Endosomolytic bioreducible poly(amido amine disulfide) polymer conjugates for the in vivo systemic delivery of siRNA therapeutics.

Efficient siRNA delivery is dependent not only on the ability of the delivery vehicle to target a specific organ but also on its ability to enable siRNA entry into the cytoplasm of the target cells. Polymers with endosomolytic properties are increasingly being used as siRNA delivery vehicles due to their potential to facilitate endosomal escape and intracellular delivery. Addition of disulfide bonds in the backbone of these polymers was expected to provide degradability through reduction by glutathione in cytosol. This paper describes the synthesis of new endosomolytic bioreducible poly(amido amine disulfide) polymers whose lytic potential can be masked at physiological pH, but can be restored at acidic endosomal pH. These polymer conjugates gave good in vitro knockdown (KD) and did not demonstrate cytotoxicity in a MTS assay. Efficient mRNA KD for apolipoprotein B in mouse liver was observed with these polyconjugates following intravenous dosing.

Assessing the heterogeneity level in lipid nanoparticles for siRNA delivery: size-based separation, compositional heterogeneity, and impact on bioperformance.

A primary consideration when developing lipid nanoparticle (LNP) based small interfering RNA (siRNA) therapeutics is formulation polydispersity or heterogeneity. The level of heterogeneity of physicochemical properties within a pharmaceutical batch could greatly affect the bioperformance, quality, and ability of a manufacturer to consistently control and reproduce the formulations. This article studied the heterogeneity in the size, composition, and in vitro performance of siRNA containing LNPs, by conducting preparative scale fractionation using a sephacryl S-1000 based size-exclusion chromatography (SEC) method. Eight LNPs with size in the range of 60-190 nm were first evaluated by the SEC method for size polydispersity characterization, and it was found that LNPs in the range of 60-150 nm could be well-resolved. Two LNPs (LNP A and LNP B) with similar bulk properties were fractionated, and fractions were studied in-depth for potential presence of polydispersity in size, composition, and in vitro silencing, as well as cytotoxicity. LNP A was deemed to be monodisperse following results of a semipreparative SEC fractionation that showed similar size, chemical composition, in vitro silencing activity, and cytotoxicity across the fractions. Therefore, LNP A represents a relatively homogeneous formulation and offers less of a challenge in its pharmaceutical development. In contrast, LNP B fractions were shown to be significantly more polydisperse in size distribution. Interestingly, LNP B SEC fractions also exhibited profound compositional variations (e.g., 5 fold difference in N/P ratio and 3 fold difference in lipid composition) along with up to 40 fold differences in the in vitro silencing activity. The impact of LNP size and formulation composition on in vitro performance is also discussed. The present results demonstrate the complexity and potential for presence of heterogeneity in LNP-based siRNA drug products. This underscores the need for tools that yield a detailed characterization of LNP formulations. This capability in tandem with the pursuit of improved formulation and process design can lead to more facile development of LNP-based siRNA pharmaceuticals of higher quality.

Polydispersity characterization of lipid nanoparticles for siRNA delivery using multiple detection size-exclusion chromatography.

The development of lipid nanoparticle (LNP) based small interfering RNA (siRNA) therapeutics presents unique pharmaceutical and regulatory challenges. In contrast to small molecule drugs that are highly pure and well-defined, LNP drug products can exhibit heterogeneity in size, composition, surface property, or morphology. The potential for batch heterogeneity introduces a complexity that must be confronted in order to successfully develop and ensure quality in LNP pharmaceuticals. Currently, there is a lack of scientific knowledge in the heterogeneity of LNPs as well as high-resolution techniques that permit this evaluation. This article reports a size-exclusion chromatography (SEC) method that permits the high-resolution analysis of LNP size distribution in its native solution condition. When coupled with multiple detection systems including UV-vis, multi-angle light scattering, and refractive index, on-line characterization of the distributions in size, molecular weight, and siRNA cargo loading of LNPs could be achieved. Six LNPs with sizes in the rang of 60-140 nm were evaluated and it was found that the SEC separation is efficient, highly reproducible, and can be broadly applied to a diverse range of LNPs. A comparison between the current SEC method and asymmetric field flow fractionation (FFF) shows that the current method provides similar size distribution results on LNPs compared to FFF. Two representative LNPs with similar bulk properties were evaluated in-depth using the SEC method along with two other sizing techniques-dynamic light scattering and cryo-TEM. Profound differences in batch polydispersity were observed between them. Despite the similarity in the particle assembly process, it was found that one LNP (A) possessed a narrow size and molecular weight distribution while the other (B) was polydisperse. The present results suggest that LNP drug products are highly complex and diverse in nature, and care should be taken in examining and understanding them to ensure quality and consistency. The method developed here can not only serve as a method for understanding LNP product property, permitting control on product quality, but also could serve as a potential manufacturing method for product purification. Understandings obtained in this work can help to facilitate the development of LNPs as a well-defined pharmaceutical product.

Industry White Paper: Contemporary Opportunities and Challenges in Characterizing Crystallinity in Amorphous Solid Dispersions.

Members of the IQ Consortium ″Working Group on Characterization on Amorphous Solid Dispersions″ shares here a perspective on the analytical challenges, and limitations of detecting low levels of crystalline drug substance in amorphous solid dispersions (ASDs) and associated drug products. These companies aim to employ highly sensitive commercially available analytical technologies to guide development, support control strategies, and enable registration of quality products. We hope to promote consistency in development and registration approaches and guide the industry in development of "characterization best practices" in the interest of providing high quality products for patients. The first half of this perspective highlights the unique challenges of analytical methodologies to monitor crystalline drug substance in ASDs and their associated drug products. Challenges around use of limit tests, analyte spiking experiments, and method robustness are also underscored. The latter half describes the merits and limitations of the diverse analytical "toolbox" (such as XRPD, NIR and DSC), which can be readily applied during development and, in some cases, considered for potential application and validation in the commercial QC setting when necessary.

Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study.

The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment.

Process analytics 4.0: A paradigm shift in rapid analytics for biologics development.

Analytical testing of product quality attributes and process parameters during the biologics development (Process analytics) has been challenging due to the rapid growth of biomolecules with complex modalities to support unmet therapeutic needs. Thus, the expansion of the process analytics tool box for rapid analytics with the deployment of cutting-edge technologies and cyber-physical systems is a necessity. We introduce the term, Process Analytics 4.0; which entails not only technology aspects such as process analytical technology (PAT), assay automation, and high-throughput analytics, but also cyber-physical systems that enable data management, visualization, augmented reality, and internet of things (IoT) infrastructure for real time analytics in process development environment. This review is exclusively focused on dissecting high-level features of PAT, automation, and data management with some insights into the business aspects of implementing during process analytical testing in biologics process development. Significant technological and business advantages can be gained with the implementation of digitalization, automation, and real time testing. A systematic development and employment of PAT in process development workflows enable real time analytics for better process understanding, agility, and sustainability. Robotics and liquid handling workstations allow rapid assay and sample preparation automation to facilitate high-throughput testing of attributes and molecular properties which are otherwise challenging to monitor with PAT tools due to technological and business constraints. Cyber-physical systems for data management, visualization, and repository must be established as part of Process Analytics 4.0 framework. Furthermore, we review some of the challenges in implementing these technologies based on our expertise in process analytics for biopharmaceutical drug substance development.

New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study.

The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography-mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.

Unique Impacts of Methionine Oxidation, Tryptophan Oxidation, and Asparagine Deamidation on Antibody Stability and Aggregation.

Monoclonal antibodies are attractive therapeutic agents because of their impressive biological activities and favorable biophysical properties. Nevertheless, antibodies are susceptible to various types of chemical modifications, and the impact of such modifications on antibody physical stability and aggregation remains understudied. Here, we report a systematic analysis of the impact of methionine oxidation, tryptophan oxidation, and asparagine deamidation on antibody conformational and colloidal stability, hydrophobicity, solubility, and aggregation. Interestingly, we find little correlation between the impact of these chemical modifications on antibody conformational stability and aggregation. Methionine oxidation leads to significant reductions in antibody conformational stability while having little impact on antibody aggregation except at extreme conditions (low pH and elevated temperature). Conversely, tryptophan oxidation and asparagine deamidation have little impact on antibody conformational stability while promoting aggregation at a wide range of solution conditions, and the aggregation mechanisms appear linked to unique types of reducible and nonreducible covalent crosslinks and, in some cases, to increased levels of attractive colloidal interactions. These findings highlight that even related types of chemical modifications can lead to dissimilar antibody aggregation mechanisms, and evaluating these findings for additional antibodies will be important for improving the systematic generation of antibodies with high chemical and physical stability.

Mechanism and Impact of Excipient Incompatibility: Cross-Linking of Xanthan Gum in Pediatric Powder-for-Suspension Formulations.

Research on pharmaceutical pediatric powder-for-suspension formulations mainly focuses on chemical and physical stability of the active pharmaceutical ingredient. However, the chemical stability of excipients could also play a key role in governing the quality and performance of the product. The suspending agents that are added into formulations to suspend the active pharmaceutical ingredient particles are critical to ensure the suspension dose accuracy. In this article, we investigate the chemical stability of the suspending agent-xanthan gum-in the presence of other excipients, particularly commonly used acid modifiers (i.e., citric acid, malic acid, succinic acid, and fumaric acid) in pediatric powder-for-suspension formulations. We observed that some of the acid modifiers catalyze cross-linking of xanthan gum during accelerated stability studies in powder blends, which significantly decreases the viscosity of the corresponding constituted suspension, resulting in poor suspendability and dose inaccuracy. Furthermore, we found that the cross-linking of xanthan gum is acid-dependent and that a careful selection of acid modifiers can mitigate the degradation issues of xanthan gum. Finally, we characterized the cross-linked xanthan gum using Fourier transform infrared spectroscopy and solid-state nuclear magnetic resonance and discussed the possible degradation mechanisms.

Probing the Tryptophan Environment in Therapeutic Proteins: Implications for Higher Order Structure on Tryptophan Oxidation.

Tryptophan (Trp) oxidation in proteins leads to a number of events, including changes in color, higher order structure (HOS), and biological activity. We describe here a number of new findings through a comprehensive characterization of 6 monoclonal antibodies (mAbs) following selective oxidation of Trp residues by 2,2'-azobis(2-amidinopropane) dihydrochloride. Fluorescence spectroscopy, in combination with second derivative analysis, demonstrates that the loss of Trp fluorescence intensity is a sensitive indicator of Trp oxidation in mAbs. Size-exclusion chromatography with UV and intrinsic Trp fluorescence detection was demonstrated to be a useful method to monitor Trp oxidation levels in mAbs. Furthermore, the Trp oxidation levels measured by size-exclusion chromatography with UV and intrinsic Trp fluorescence detection were found to be in agreement with the values obtained from tryptic peptide mapping by liquid chromatography with mass spectrometric detection and correlate with the total solvent accessible surface area of the exposed Trp residues from in silico modeling. Finally, near-UV circular dichroism and Raman spectroscopy were used to evaluate the impact of Trp oxidation on HOS and identify specific oxidation products, respectively. This work demonstrates that protein HOS is altered on Trp oxidation in mAbs and multiple spectroscopic markers can be used to monitor the molecule-dependent Trp oxidation behavior.

Enhanced Precision of Circular Dichroism Spectral Measurements Permits Detection of Subtle Higher Order Structural Changes in Therapeutic Proteins.

Protein higher order structure (HOS) is an essential quality attribute to ensure protein stability and proper biological function. Protein HOS characterization is performed during comparability assessments for product consistency as well as during forced degradation studies for structural alteration upon stress. Circular dichroism (CD) spectroscopy is a widely used technique for measuring protein HOS, but it remains difficult to assess HOS with a high degree of accuracy and precision. Moreover, once spectral changes are detected, interpreting the differences in terms of specific structural attributes is challenging. Spectral normalization by the protein concentration remains one of the largest sources of error and reduces the ability to confidently detect differences in CD spectra. This work develops a simple method to enhance the precision of the CD spectral measurements through normalization of the CD spectra by the protein concentration determined directly from the CD measurement. This method is implemented to successfully detect small CD spectral changes in multiple forced degradation studies as well as comparability assessments during biologics drug development. Furthermore, the interpretation of CD spectral changes in terms of HOS differences are provided based on orthogonal data in conjunction with structural insights gained through in silico homology modeling of the protein structure.