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Gene therapy is a procedure that enables gene improvement by means of the correction of the altered (mutated) genes, or targets site-specific modifications that have therapeutic treatment as a target [...]

Ion pairing agents are frequently used in liquid chromatography (LC), especially in reversed-phase liquid chromatography (RPLC), to increase the separation and retention of charged analytes. However, their use in other modes of HPLC, such as sizeexclusion HPLC (SE-HPLC) and ion exchange chromatography (IEC) has not been extensively explored. In RPLC, the target analytes may have charged functional groups, which makes it difficult to maintain them on the hydrophobic stationary phase. This difficulty is often overcome by the inclusion of an ion pairing agent, which introduces ionic contacts and strengthens the hydrophobic connections between the analytes and stationary phase. The separation mechanisms in both SE-HPLC and IEC rely on size and charge differences, respectively, between analytes. Thus, they are naturally constructed to separate analytes without the requiring extra ion pairing agents. In this study, we introduced an ion pairing agent (, Reversed-phase liquid chromatography (RPLC) is a simple and user-friendly technology that is often used for separation of bioanalytes, thereby accounting for up to 70-80% of bioseparations (1). Most acidic samples [...]

Over the last several years, our definition of biotherapeutics has evolved from solely protein-based therapeutics, such as monoclonal antibodies (mAbs), to include such product classes as cell and gene therapies. Cell and gene therapies are unique products that require innovative and new approaches to formulation, specifically related to drug delivery. One such delivery modality that has gained significant traction is lipid nanoparticles (LNPs), which, as their name suggests, are nanoparticles comprised of lipids. The first LNP product approved by the United States Food and Drug Administration, was the liposome-encapsulated Doxil, whereas, in 2018, the United States Food and Drug Administration approved the small interfering RNA (siRNA) product Onpattro, using lipid nanoparticles as part of its formulation. Since then, LNPs have gained more international attention in their role in drug delivery because of the mRNA-based COVID-19 vaccines. LNPs in the biopharmaceutical space are still in their infancy related to our understanding of them and how to characterize them, presenting both challenges and opportunities. In this column, we discuss some of those challenges and opportunities and look at the current and future landscape of the most common analytical tools used to analyze and characterize LNP, As our understanding of biotherapeutics expands to include new products such as cell and gene therapies, we are presented with new challenges and opportunities in the characterization of these products. [...]

Multi-attribute methods (MAMs) are becoming increasingly popular for their ability to analyze multiple critical quality attributes (CQA) in a single workflow. This capability becomes particularly attractive for a product class [...]

Analytical methods are used in the biopharmaceutical industry to ensure the quality, efficacy, and safety of drug substances and drug products. One of the fundamental measures of the quality of a drug substance or drug product, including biopharmaceuticals, is the stability of the active pharmaceutical ingredient (API). In fact, the first International Council for Harmonization (ICH) guideline on quality, ICH Q1, is for drug stability. In this column, we look at drug stability in general, differences between largeand small-molecule stability (ICH Q1 and ICH Q5), as well as the analytical methods used to measure the stability of a product. Although there are several analytical methodologies that can be used, and we touch on those briefly, we focus mostly on the chromatography and mass spectrometry methods used to characterize drug stability., At the center of everything we do in the biopharmaceutical industry should be patients and ensuring that their medicines are high quality, safe, and effective. A cornerstone of any drug [...]

The landscape of biopharmaceutical analysis features different analytical requirements in terms of instrumentation and type of analysis (QC, RTRT, and in-process). One of the questions that often crops up for routine analysis is 'How much replication is enough?' Should all the samples be run in triplicate irrespective of the type of analysis, or does the type of analysis (such as charge or size variants) have any bearing on the number of optimal replicates?, There are various factors that the user needs to consider in the matter of biopharmaceutical analysis--first, the objective of replication, and second, the trade-off with respect to cost and time. [...]

A biosimilar is a drug product that has been deemed to be highly similar to its off-patent reference product in terms of purity, molecular structure, and bioactivity. Approvals to such products are granted on the basis of unambiguous demonstration of 'no clinically meaningful differences' between the reference and the intended biosimilar. For a successful biosimilar approval, establishing analytical and functional biosimilarity across all relevant critical quality attributes is an essential prerequisite. This critical activity is performed using a combination of orthogonal, high-resolution tools that can accurately quantitate the minor differences that exist. In this article, we review key findings from some of the recent biosimilarity assessments that we have published on biosimilars of granulocyte-colony-stimulating factor (G-CSF), insulin glargine, rituximab, and trastuzumab., Biosimilars are defined as biotherapeutic drugs that have been shown to have a highly similar quality, safety, and efficacy profile to the original product. Fuelled by the patent cliffs, the [...]

Introduction: Early detection of pancreatic cancer continues to be a challenge due to the difficulty in accurately identifying specific signs or symptoms that might correlate with the onset of pancreatic cancer. Unlike breast or colon or prostate cancer where screening tests are often useful in identifying cancerous development, there are no tests to diagnose pancreatic cancers. As a result, most pancreatic cancers are diagnosed at an advanced stage, where treatment options, whether systemic therapy, radiation, or surgical interventions, offer limited efficacy. Methods: A two-stage weakly supervised deep learning-based model has been proposed to identify pancreatic tumors using computed tomography (CT) images from Henry Ford Health (HFH) and publicly available Memorial Sloan Kettering Cancer Center (MSKCC) data sets. In the first stage, the nnU-Net supervised segmentation model was used to crop an area in the location of the pancreas, which was trained on the MSKCC repository of 281 patient image sets with established pancreatic tumors. In the second stage, a multi-instance learning-based weakly supervised classification model was applied on the cropped pancreas region to segregate pancreatic tumors from normal appearing pancreas. The model was trained, tested, and validated on images obtained from an HFH repository with 463 cases and 2,882 controls. Results: The proposed deep learning model, the two-stage architecture, offers an accuracy of 0.907 ± 0.01, sensitivity of 0.905 ± 0.01, specificity of 0.908 ± 0.02, and AUC (ROC) 0.903 ± 0.01. The two-stage framework can automatically differentiate pancreatic tumor from non-tumor pancreas with improved accuracy on the HFH dataset. Discussion: The proposed two-stage deep learning architecture shows significantly enhanced performance for predicting the presence of a tumor in the pancreas using CT images compared with other reported studies in the literature. [ABSTRACT FROM AUTHOR]

Monoclonal antibodies (mAbs) dominate the pipelines in the biopharmaceutical industry today. Being complex products, this class of molecules has numerous critical quality attributes (CQAs). Their thorough characterization is a necessary and critical component of biopharmaceutical product development. One CQA is size-based heterogeneity. Aggregates are widely considered a CQA because of their likely impact on the immunogenicity of the product. There is no single analytical tool that can accurately characterize aggregates because of the significant diversity that they exhibit with respect to size, structure, and morphology. As a result, it is common practice to use multiple, orthogonal analytical tools for aggregate characterization. This article reviews efforts targeting the use of two-dimensional liquid chromatography (2D-LC) and mass spectrometry (MS) for aggregate characterization., Two-dimensional liquid chromatography (2D-LC) is a technique that is capable of resolving heterogeneity of a biological sample via using two different LC columns, each corresponding to a different separation mechanism. [...]

With the number of complex biologics, such as antibody-drug conjugates (ADCs), increasing, reliable, reproducible, and rapid methods are needed for their bioanaly tical charac terization. Arguably, the most common analy tical technologies currently used for characterizing biologics are liquid chromatography (LC) and mass spectrometry (MS) focused on liquid chromatographytandem mass spectrometry (LC-MS/MS) peptide applications. Just as important is the application of LC-MS to analyze the intact mass of these products. In this column, we explore the most current applications of intact mass analysis, such as quantitation, sequencing, and struc tural charac terizing. The advantages and disadvantages of intac t mass analysis are discussed, and a shor t discussion of how peptide characterization is an orthogonal application to intact characterization is presented. The difference between top-down MS and intact mass analysis is explored, because the two terms are often mistakenly used interchangeably. Finally, intact multi-attribute methods (MAMs) are discussed as well as an unique intact mass approach in characterizing ADCs., Characterization of biopharmaceuticals is important throughout the life cycle of the drug product to ensure the safety, efficacy, and quality of the product. This characterizing is particularly important for biologics [...]

Therapeutic biologics are becoming a critical and significant component of drug discovery pipelines in the pharmaceutical industry. The utility of biologic drugs for treating unmet medical needs is being expanded [...]

Over the last several years, the landscape of the biopharmaceutical industry has begun to change. Monoclonal antibodies (mAbs) still dominate the pipelines in the biopharmaceutical industry; however, more complex molecules, such as antibody-drug conjugates (ADC), are becoming more predominant. In addition to the complexity of ADCs, one of the fastest growing classes of biopharmaceuticals is cell and gene therapies. Gene therapies, for example, use large viral vectors, such as adeno-associated viruses (AAV), as the preferred vector for performing gene therapy. With the complexity of biopharmaceuticals increasing, especially in their size, new and innovative approaches are needed to address and characterize these molecules. This month's column reviews how charge detection mass spectrometry (CDMS) is being used to characterize some of these larger more complex molecules in the biopharmaceutical industry., Biopharmaceuticals are products that are specifically made by living cells or biotechnological processes. By the nature of these products being manufactured in living cells can lead to variability in the [...]

The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber–physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs. [ABSTRACT FROM AUTHOR]

Over the last decade or so, biopharmaceuticals have gained market share and become more complex in their composition. Therefore, new analytical workflows are needed to address these advances, and one [...]

The quality of a biotherapeutic is defined by its various biological, immunological, structural, and physicochemical attributes. Some of these are post-translational modifications (PTMs), other product-related heterogeneities, process related impurities, and [...]

With the advances in analytical technology during the past decade, biotherapeutics or biologicals now represent an important and growing class of drugs. They require extensive characterization, due to their large [...]