Systematic analytical workflow for characterisation and identification of partially reduced species in monoclonal antibody manufacturing.

Fragmentation is a major degradation pathway ubiquitous to all therapeutic monoclonal antibody (mAb) and therefore, monitored throughout the manufacturing process. Here, we describe a three-step approach to 1) detect, 2) confirm and 3) characterize partially reduced fragment species in an immunoglobulin G1 (IgG1) mAb with prolonged hold time of harvested cell culture fluid (HCCF). Microchip capillary electrophoresis (MCE) and high-performance size exclusion chromatography (HPSEC) were used as fast and efficient screening methods to detect fragmentation. HPSEC was found to be underestimating fragmentation levels. To confirm and characterize the fragments, capillary electrophoresis-sodium dodecyl sulphate (CE-SDS) was employed. Interestingly, the absence of fragments in the reduced CE-SDS analysis suggested partial reduction of disulphide bonds contributing to fragmentation in this mAb lot. This was further confirmed using reverse phase high performance liquid chromatography (RP-HPLC) coupled with mass spectrometry, which established the presence of heavy-heavy-light (HHL), heavy-heavy (HH), light-light dimer (LL), light chain (LC) and half antibody (HL) fragments with good mass accuracy. In this study, we demonstrated a readily applicable systematic strategy to support process development and investigate anomalous events in manufacturing. An additional highlight of this work is the data-driven comprehensive comparison of modern and conventional analytical techniques for fragment analysis.

Comprehensive Stress Stability Studies Reveal the Prominent Stability of the Liquid-Formulated Biotherapeutic Asymmetric Monovalent Bispecific IgG1 Monoclonal Antibody Format.

The developed asymmetric monovalent bispecific IgG1 or Duet monoclonal antibody (Duet mAb) has two distinct fragment antigen-binding region (Fab) subunits that target two different epitope specificities sequentially or simultaneously. The design features include unique engineered disulfide bridges, knob-into-hole mutations, and kappa and lambda chains to produce Duet mAbs. These make it structurally and functionally complex, so one expects challenging developability linked to instability, degradation of products and pathways, and limited reports available. Here, we have treated the product with different sources of extreme stress over a lengthy period, including varying heat, pH, photo stress, chemical oxidative stress, accelerated stress in physiological conditions, and forced glycation conditions. The effects of different stress conditions on the product were assessed using various analytical characterization tools to measure product-related substances, post-translational modifications (PTMs), structural integrity, higher-order disulfide linkages, and biological activity. The results revealed degradation products and pathways of Duet mAb. A moderate increase in size, charge, and hydrophobic variants, PTMs, including deamidation, oxidation, isomerization, and glycation were observed, with most conditions exhibiting biological activity. In addition, the characterization of fractionated charge variants, including deamidated species, showed satisfactory biological activity. This study demonstrated the prominent stability of the Duet mAb format comparable to most marketed mAbs.

Identification and quantification of chain-pairing variants or mispaired species of asymmetric monovalent bispecific IgG1 monoclonal antibody format using reverse-phase polyphenyl chromatography coupled electrospray ionization mass spectrometry.

Developing a knob-into-hole asymmetric bispecific IgG1 monoclonal antibody (mAb) poses manufacturing challenges due to the expression of chain pairing variants, also called mispaired species, in the desired product. The incorrect pairing of light and heavy chains could result in heterogeneous mispaired species of homodimers, heterodimers, light chain swapping, and low molecular weight species (LMWS). Standard chromatography, capillary electrophoretic, or spectroscopic methods poorly resolve these from the main variants. Here, we report a highly sensitive reverse-phase polyphenyl ultra-high-performance liquid chromatography (RP-UHPLC) method to accurately measure mispaired species of Duet mAb format, an asymmetric IgG1 bispecific mAb, for both process development and quality control analytical tests. Coupled with electrospray ionization mass spectrometry (ESI-MS), it enabled direct online characterization of mispaired species. This single direct assay detected diverse mispaired IgG-like species and LMWS. The method resolved eight disulfide bonds dissociated LMWS and three mispaired LMWS. It also resolved three different types of IgG-like mispaired species, including two homodimers and one heterodimer. The characterization and quantification simultaneously enabled the cell line selection that produces a lesser heterogeneity and lower levels of mispaired species with the desired correctly paired product. The biological activity assessment of samples with increased levels of these species quantified by the method exhibited a linear decline in potency with increasing levels of mispaired species in the desired product. We also demonstrated the utility of the technique for testing in-process intermediate materials to determine and assess downstream purification process capability in removing diverse mispaired IgG-like species and LMWS to a certain level during the downstream purification process. Our investigation demonstrates that adopting this method was vital in developing asymmetric bispecific mAb from the initial stage of cell line development to manufacturing process development. Therefore, this tool could be used in the control strategy to monitor and control mispaired species during manufacturing, thus improving the quality control of the final product.

CHO synthetic promoters improve expression and product quality of biotherapeutic proteins.

When expressing complex biotherapeutic proteins, traditional expression plasmids and methods may not always yield sufficient levels of high-quality product. High-strength viral promoters commonly used for recombinant protein (rProtein) production in mammalian cells allow for maximal expression, but provide limited scope to alter their transcription dynamics. However, synthetic promoters designed to provide tunable transcriptional activity offer a plasmid engineering approach to more precisely regulate product quality, yield or to reduce product related contaminants. We substituted the viral promoter CMV with synthetic promoters that offer different transcriptional activities to express our gene of interest in Chinese hamster ovary (CHO) cells. Stable pools were established and the benefits of regulating transgene transcription on the quality of biotherapeutics were examined in stable pool fed-batch overgrow experiments. Specific control of gene expression of the heavy chain (HC):light chain (LC) of a Fab, and the ratio between the two HCs in a Duet mAb reduced levels of aberrant protein contaminants; and the controlled expression of the helper gene XBP-1s improved expression of a difficult-to-express mAb. This synthetic promoter technology benefits applications that require custom activity. Our work highlights the advantages of employing synthetic promoters for production of more complex rProteins.

Computer assisted recognition of breast cancer in biopsy images via fusion of nucleus-guided deep convolutional features.

BACKGROUND AND OBJECTIVE: Breast cancer is a commonly detected cancer among women, resulting in a high number of cancer-related mortality. Biopsy performed by pathologists is the final confirmation procedure for breast cancer diagnosis. Computer-aided diagnosis systems can support the pathologist for better diagnosis and also in reducing subjective errors. METHODS: In the automation of breast cancer analysis, feature extraction is a challenging task due to the structural diversity of the breast tissue images. Here, we propose a nucleus feature extraction methodology using a convolutional neural network (CNN), 'NucDeep', for automated breast cancer detection. Non-overlapping nuclei patches detected from the images enable the design of a low complexity CNN for feature extraction. A feature fusion approach with support vector machine classifier (FF + SVM) is used to classify breast tumor images based on the extracted CNN features. The feature fusion method transforms the local nuclei features into a compact image-level feature, thus improving the classifier performance. A patch class probability based decision scheme (NucDeep + SVM + PD) for image-level classification is also introduced in this work. RESULTS: The proposed framework is evaluated on the publicly available BreaKHis dataset by conducting 5 random trials with 70-30 train-test data split, achieving average image level recognition rate of 96.66  ±  0.77%, 100% specificity and 96.21% sensitivity. CONCLUSION: It was found that the proposed NucDeep + FF + SVM model outperforms several recent existing methods and reveals a comparable state of the art performance even with low training complexity. As an effective and inexpensive model, the classification of biopsy images for breast tumor diagnosis introduced in this research will thus help to develop a reliable support tool for pathologists.

Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion.

BACKGROUND AND OBJECTIVE: Breast cancer is a frequently diagnosed cancer in women, contributing to significant mortality rates. Death rates are relatively higher in developing nations due to the shortage of early detection amenities and constraints on access to technical advances combating this disease. The only way to diagnose cancer with certainty is through biopsy performed by pathologists. Computer-aided diagnostic algorithms can assist pathologists in being more productive, objective and consistent in the diagnostic process. The focus of this work is to develop a reliable automated breast cancer diagnosis method which can operate in the prevailing clinical environment. METHODS: Nuclei overlap and complex structural organisation of the breast tissue in biopsy images make nuclei segmentation, feature extraction and classification challenging. In this work, a nucleus guided transfer learning (NucTraL) methodology is proposed as a simple and affordable breast tumor classification algorithm. The image feature is represented by fusion of local nuclei features that are extracted using convolutional neural network (CNN) models pretrained on the ImageNet database. The nucleus patch extraction strategy used in this work avoids fine segmentation of the nuclei boundary but provides features with good discriminative power for classification. Classification of the fused features into benign and malignant classes is performed using a support vector machine (SVM) classifier. A belief theory based classifier fusion (BCF) strategy is then employed to combine the outputs arising from the different CNN-SVM combinations to improve accuracy further. RESULTS: Evaluation of results is achieved by executing 100 random trials with 70%-30% train to test division on the publicly available BreaKHis dataset. The proposed framework achieved average accuracy of 96.91%, sensitivity of 97.24% and specificity of 96.18%. CONCLUSION: It is found that the proposed NucTraL+BCF framework outperforms several recent approaches and achieves results comparable to the state-of-the-art methods even without using high computational power. This qualitative framework based on transfer learning can contribute significantly for developing cost effective and low complexity CAD system for breast cancer diagnosis from histopathological images.

Identification and quantification of product-related quality attributes in bio-therapeutic monoclonal antibody via a simple, and robust cation-exchange HPLC method compatible with direct online detection of UV and native ESI-QTOF-MS analysis.

Modern analytical ion-exchange chromatography is one of the conventional tools used for assessment of product-related quality attributes in bio-therapeutic monoclonal antibodies (mAbs). Here, we present an approach to resolve, identify, and quantify product-related substances of therapeutic mAb at its intact molecular level by cation exchange (CIEX) HPLC coupled directly to electrospray ionization - quadrupole time of flight mass spectrometry (ESI-QTOF-MS). This method utilizes pH gradient elution mode comprised of ammonium formate buffer components, and a weak cation exchange column as stationary phase. Furthermore, ion-mobility mass spectrometry (IM-MS) provided additional insights on its higher order structure. Also, orthogonal assays such as conventional CIEX-HPLC, high resolution capillary isoelectric focusing, peptide mapping, spectroscopic, and fluorescence methods were used considerably to support the findings. Additionally, an in vitro assay was included to assess the associated impact on Fc mediated function. Overall, the developed method with simultaneous detection of UV peak area percentage at 280 nm and native ESI-MS is found to be a rapid and robust analytical tool for direct assessment of structural and purity attributes, process optimization, product development, and to decipher the relevant role of micro-variants on quality, stability, and clinical outcomes.

Mass Spectrometry Based Mechanistic Insights into Formation of Tris Conjugates: Implications on Protein Biopharmaceutics.

We present here extensive mass spectrometric studies on the formation of a Tris conjugate with a therapeutic monoclonal antibody. The results not only demonstrate the reactive nature of the Tris molecule but also the sequence and reaction conditions that trigger this reactivity. The results corroborate the fact that proteins are, in general, prone to conjugation and/or adduct formation reactions and any modification due to this essentially leads to formation of impurities in a protein sample. Further, the results demonstrate that the conjugation reaction happens via a succinimide intermediate and has sequence specificity. Additionally, the data presented in this study also shows that the Tris formation is produced in-solution and is not an in-source phenomenon. We believe that the facts given here will open further avenues on exploration of Tris as a conjugating agent as well as ensure that the use of Tris or any ionic buffer in the process of producing a biopharmaceutical drug is monitored closely for the presence of such conjugate formation. Graphical Abstract ᅟ.