Combined 100 keV Cryo-Electron Microscopy and Image Analysis Methods to Characterize the Wider Adeno-Associated Viral Products.

Adeno-associated viruses (AAVs) are effective vectors for gene therapy. However, AAV drug products are inevitably contaminated with empty particles (EP), which lack a genome, owing to limitations of the purification steps. EP contamination can reduce the transduction efficiency and induce immunogenicity. Therefore, it is important to remove EPs and to determine the ratio of full genome-containing AAV particles to empty particles (F/E ratio). However, most of the existing methods fail to reliably evaluate F/E ratios that are greater than 90 %. In this study, we developed two approaches based on the image analysis of cryo-electron micrographs to determine the F/E ratios of various AAV products. Using our developed convolutional neural network (CNN) and morphological analysis, we successfully calculated the F/E ratios of various AAV products and determined the slight differences in the F/E ratios of highly purified AAV products (purity > 95 %). In addition, the F/E ratios calculated by analyzing more than 1000 AAV particles had good correlations with theoretical F/E ratios. Furthermore, the CNN reliably determined the F/E ratio with a smaller number of AAV particles than morphological analysis. Therefore, combining 100 keV cryo-EM with the developed image analysis methods enables the assessment of a wide range of AAV products.

A Comprehensive Analysis of Biopharmaceutical Products Listed in the FDA's Purple Book.

Although biopharmaceuticals constitute around 10% of the drug landscape, eight of the ten top-selling products were biopharmaceuticals in 2023. This study did a comprehensive analysis of the FDA's Purple Book database. Firstly, our research uncovered market trends and provided insights into biologics distributions. According to the investigation, although biotechnology has advanced and legislative shifts have made the approval process faster, there are still challenges to overcome, such as molecular instability and formulation design. Moreover, our research comprehensively analyzed biological formulations, pointing out significant strategies regarding administration routes, dosage forms, product packaging, and excipients. In conjunction with biologics, the widespread integration of innovative delivery strategies will be implemented to confront the evolving challenges in healthcare and meet an expanding array of treatment needs.

Pegylated liposome encapsulating docetaxel using microfluidic mixing technique: Process optimization and results in breast cancer models.

The development of nanoparticles could help to improve the efficacy/toxicity balance of drugs. This project aimed to develop liposomes and immunoliposomes using microfluidic mixing technology.Various formulation tests were carried out to obtain liposomes that met the established specifications. The liposomes were then characterized in terms of size, polydispersity index (PDI), docetaxel encapsulation rate and lamellarity. Antiproliferative activity was tested in human breast cancer models ranging from near-negative (MDA-MB-231), positive (MDA-MB-453) to HER2 positive. Pharmacokinetic studies were performed in C57BL/6 mice.Numerous batches of liposomes were synthesised using identical molar ratios and by varying the microfluidic parameters TFR, FRR and buffer. All synthesized liposomes have a size < 200 nm, but only Lipo-1, Lipo-6, Lipo-7, Lipo-8 have a PDI < 0.2, which meets our initial requirements. The size of the liposomes was correlated with the total FRR, for a 1:1 FRR the size is 122.2 ± 12.3 nm, whereas for a 1:3 FRR the size obtained is 163.4 ± 34.0 nm (p = 0.019. Three batches of liposomes were obtained with high docetaxel encapsulation rates > 80 %. Furthermore, in vitro studies on breast cancer cell lines demonstrated the efficacy of liposomes obtained by microfluidic mixing technique. These liposomes also showed improved pharmacokinetics compared to free docetaxel, with a longer half-life and higher AUC (3-fold and 3.5-fold increase for the immunoliposome, respectively).This suggests that switching to the microfluidic process will produce batches of liposomes with the same characteristics in terms of in vitro properties and efficacy, as well as the ability to release the encapsulated drug over time in vivo. This time-efficiency of the microfluidic technique is critical, especially in the early stages of development.

Integration of just-in-time learning with variational autoencoder for cell culture process monitoring based on Raman spectroscopy.

Protein production in the biopharmaceutical industry necessitates the utilization of multiple analytical techniques and control methodologies to ensure both safety and consistency. To facilitate real-time monitoring and control of cell culture processes, Raman spectroscopy has emerged as a versatile analytical technology. This technique, categorized as a Process Analytical Technology, employs chemometric models to establish correlations between Raman signals and key variables of interest. One notable approach for achieving real-time monitoring is through the application of just-in-time learning (JITL), an industrial soft sensor modeling technique that utilizes Raman signals to estimate process variables promptly. The conventional Raman-based JITL method relies on the K-nearest neighbor (KNN) algorithm with Euclidean distance as the similarity measure. However, it falls short of addressing the impact of data uncertainties. To rectify this limitation, this study endeavors to integrate JITL with a variational autoencoder (VAE). This integration aims to extract dominant Raman features in a nonlinear fashion, which are expressed as multivariate Gaussian distributions. Three experimental runs using different cell lines were chosen to compare the performance of the proposed algorithm with commonly utilized methods in the literature. The findings indicate that the VAE-JITL approach consistently outperforms partial least squares, convolutional neural network, and JITL with KNN similarity measure in accurately predicting key process variables.

Prediction of physicochemical and pharmacokinetic properties of botanical constituents by computational models.

Botanicals contain complex mixtures of chemicals most of which lack pharmacokinetic data in humans. Since physicochemical and pharmacokinetic properties dictate the in vivo exposure of botanical constituents, these parameters greatly impact the pharmacological and toxicological effects of botanicals in consumer products. This study sought to use computational (i.e., in silico) models, including quantitative structure-activity relationships (QSAR) and physiologically based pharmacokinetic (PBPK) modeling, to predict properties of botanical constituents. One hundred and three major constituents (e.g., withanolides, mitragynine, and yohimbine) in 13 botanicals (e.g., ashwagandha, kratom, and yohimbe) were investigated. The predicted properties included biopharmaceutical classification system (BCS) classes based on aqueous solubility and permeability, oral absorption, liver microsomal clearance, oral bioavailability, and others. Over half of these constituents fell into BCS classes I and II at dose levels no greater than 100 mg per day, indicating high permeability and absorption (%Fa > 75%) in the gastrointestinal tract. However, some constituents such as glycosides in ashwagandha and Asian ginseng showed low bioavailability after oral administration due to poor absorption (BCS classes III and IV, %Fa < 40%). These in silico results fill data gaps for botanical constituents and could guide future safety studies. For example, the predicted human plasma concentrations may help select concentrations for in vitro toxicity testing. Additionally, the in silico data could be used in tiered or batteries of assays to assess the safety of botanical products. For example, highly absorbed botanical constituents indicate potential high exposure in the body, which could lead to toxic effects.

Self-micellizing solid dispersion of thymoquinone with enhanced biopharmaceutical and nephroprotective effects.

The present study was designed to develop a self-micellizing solid dispersion (SMSD) containing Thymoquinone (TQM), a phytonutrient obtained from Nigella sativa seeds, aiming to improve its biopharmaceutical and nephroprotective functions. The apparent solubility of TQM in polymer solutions was used to choose an appropriate amphiphilic polymer that could be used to make an SMSD system. Based on the apparent solubility, Soluplus® was selected as an appropriate carrier, and mixing with TQM, SMSD-TQM with different loadings of TQM (5-15%) was made by solvent evaporation and freeze-drying techniques, respectively, and the formulations were optimized. The optimized SMSD-TQM was evaluated in terms of particle size distribution, morphology, release characteristics, pharmacokinetic behavior, and nephroprotective effects in a rat model of acute kidney injury. SMSD-TQM significantly improved the dissolution characteristics (97.8%) of TQM in water within 60 min. Oral administration of SMSD-TQM in rats exhibited a 4.9-fold higher systemic exposure than crystalline TQM. In a cisplatin-induced (6 mg/kg, i.p.) acute kidney-damaged rat model, oral SMSD-TQM (10 mg/kg) improved the nephroprotective effects of TQM based on the results of kidney biomarkers and histological abnormalities. These findings suggest that SMSD-TQM might be efficacious in enhancing the nephroprotective effect of TQM by overcoming biopharmaceutical limitations.

Comparison of Protein-like Model Particles Fabricated by Micro 3D Printing to Established Standard Particles.

Innovative analytical instruments and development of new methods has provided a better understanding of protein particle formation in biopharmaceuticals but have also challenged the ability to obtain reproducible and reliable measurements. The need for protein-like particle standards mimicking the irregular shape, translucent nature and near-to-neutral buoyancy of protein particles remained one of the hot topics in the field of particle detection and characterization in biopharmaceutical formulations. An innovative protein-like particle model has been developed using two photo polymerization (2PP) printing allowing to fabricate irregularly shaped particles with similar properties as protein particles at precise size of 50 µm and 150 µm, representative of subvisible particles and visible particles, respectively. A study was conducted to compare the morphological, physical, and optical properties of artificially generated protein particles, polystyrene spheres, ETFE, and SU-8 particle standards, along with newly developed protein-like model particles manufactured using 2PP printing. Our results suggest that 2PP printing can be used to produce protein-like particle standards that might facilitate harmonization and standardization of subvisible and visible protein particle characterization across laboratories and organizations.

pH inactivation of SARS-CoV-2 and SARS-CoV in virus spiked protein A eluates from a mAb purification process.

Biopharmaceutical manufacturing processes may include a low pH treatment step as a means of inactivating enveloped viruses. Small scale virus clearance studies are routinely performed using model enveloped viruses such as murine leukemia virus to assess inactivation at the pH range used in the downstream manufacturing process. Further, as a means of bioburden reduction, chromatography resins may be cleaned and stored using sodium hydroxide and this can also inactivate viruses. The susceptibility of SARS-CoV-2 and SARS-CoV to low pH conditions using protein A eluate derived material from a monoclonal antibody production process as well as high pH cleaning conditions was addressed. SARS-CoV-2 was effectively inactivated at pH 3.0, moderately inactivated at pH 3.4, but not inactivated at pH 3.8. Low pH was less effective at inactivating SARS-CoV. Both viruses were inactivated at a high pH of ca.13.4. These studies provide important information regarding the effectiveness of viral clearance and inactivation steps of novel coronaviruses when compared to other enveloped viruses.

Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins.

Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.

Combinations of arginine and pullulan reveal the selective effect of stabilization mechanisms on different lyophilized proteins.

The stability of lactate dehydrogenase (LDH) and ß-galactosidase (ß-gal), incorporated in arginine/pullulan (A/P) mixtures at various weight ratios by lyophilization, was determined. The physicochemical characteristics of various A/P mixtures were assessed. With decreasing A/P ratios, the glass transition temperature of the formulations increased. Furthermore, arginine crystallization due to high relative humidity (RH) exposure was prevented at an A/P weight ratio of 4/6 or less. When stored at 0 % RH / 60 °C for 4 weeks, arginine was superior to pullulan as stabilizer. During storage at 43 % RH / 30 ℃ for 4 weeks, the enzymatic activity of LDH was best retained at an A/P weight ratio of 2/8, while ß-gal activity was relatively well-retained at A/P weight ratios of both 8/2 and 2/8. LDH seemed to be more prone to degradation in the rubbery state. In the glassy state, ß-gal degraded faster than LDH. Solid-state nuclear magnetic resonance spectroscopy showed that (labeled) arginine experienced a different interaction in the two protein samples, reflecting a modulation of long-range correlations of the arginine side chain nitrogen atoms (Nε, Nη). In summary, LDH stabilization in the A/P matrix requires vitrification. Further stabilization difference between LDH and ß-gal may be dependent on the interaction with arginine.

Patient-centric Comparability Assessment of Biopharmaceuticals.

The comparability assessment of a biological product after implementing a manufacturing process change should involve a risk-based approach. Process changes may occur at any stage of the product lifecycle: early development, clinical manufacture for pivotal trials, or post-approval. The risk of the change to impact product quality varies. The design of the comparability assessment should be adapted accordingly. A working group reviewed and consolidated industry approaches to assess comparability of traditional protein-based biological products during clinical development and post-approval. The insights compiled in this review article encompass topics such as a risk-evaluation strategy, the design of comparability studies, definition of assessment criteria for comparability, holistic evaluation of data, and the regulatory submission strategy. These practices can be leveraged across the industry to help companies in design and execution of comparability assessments, and to inform discussions with global regulators.

Engineering an Escherichia coli based in vivo mRNA manufacturing platform.

Synthetic mRNA is currently produced in standardized in vitro transcription systems. However, this one-size-fits-all approach has associated drawbacks in supply chain shortages, high reagent costs, complex product-related impurity profiles, and limited design options for molecule-specific optimization of product yield and quality. Herein, we describe for the first time development of an in vivo mRNA manufacturing platform, utilizing an Escherichia coli cell chassis. Coordinated mRNA, DNA, cell and media engineering, primarily focussed on disrupting interactions between synthetic mRNA molecules and host cell RNA degradation machinery, increased product yields >40-fold compared to standard "unengineered" E. coli expression systems. Mechanistic dissection of cell factory performance showed that product mRNA accumulation levels approached theoretical limits, accounting for ~30% of intracellular total RNA mass, and that this was achieved via host-cell's reallocating biosynthetic capacity away from endogenous RNA and cell biomass generation activities. We demonstrate that varying sized functional mRNA molecules can be produced in this system and subsequently purified. Accordingly, this study introduces a new mRNA production technology, expanding the solution space available for mRNA manufacturing.

Optimization of hydrolysis conditions of amino acid analysis for UHPLC-UV antigens content determination: Bexsero vaccine a case study.

In the present study the compositional analysis of the amino acids released by the acidic hydrolysis of the vaccine antigens was approached as an alternative to the dye-binding methods, for improvement of the quality control. In particular, the Analytical Quality by Design principles were undertaken in optimizing the hydrolysis conditions of the antigens to be applied prior to the quantitation by UHPLC-UV. Bexsero was used as a case study; it is a recombinant meningococcal B vaccine and one of its critical quality attributes is the content of the three core protein antigens, namely Neisseria Heparin Binding Antigen, factor H binding protein and Neisseria adhesin A, in the final formulation. Conventionally, the proteins quantitation is carried out by dye-binding assays. Analytical Target Profile was defined as the accurate determination of amounts of the Bexsero antigens. The Critical Method Parameters were chosen by means of the cause-effect matrix. A Face Centered Design was used to select the experiments to investigate the process and finally a Method Operable Design Region with a risk of failure of 5% was defined. The selected working point for routine use was: hydrolysis time, 17 hrs; temperature, 112 °C; 6 M HCl volume, 300 µl; antioxidant 90% phenol volume, 5 µl.

Cell culture product quality attribute prediction using convolutional neural networks and Raman spectroscopy.

Advanced process control in the biopharmaceutical industry often lacks real-time measurements due to resource constraints. Raman spectroscopy and Partial Least Squares (PLS) models are often used to monitor bioprocess cultures in real-time. In spite of the ease of training, the accuracy of the PLS model is impacted if it is not used to predict quality attributes for the cell lines it is trained on. To address this issue, a deep convolutional neural network (CNN) is proposed for offline modeling of metabolites using Raman spectroscopy. By utilizing asymmetric least squares smoothing to adjust Raman spectra baselines, a generic training data set is created by amalgamating spectra from various cell lines and operating conditions. This data set, combined with their derivatives, forms a two-dimensional model input. The CNN model is developed and validated for predicting different quality variables against measurements from various continuous and fed-batch experimental runs. Validation results confirm that the deep CNN model is an accurate generic model of the process to predict real-time quality attributes, even in experimental runs not included in the training data. This model is robust and versatile, requiring no recalibration when deployed at different sites to monitor various cell lines and experimental runs.

Physicochemical modifications in microwave-irradiated chitosan: biopharmaceutical and medical applications.

Biopharmaceutical and biomedical applications of chitosan has evolved exponentially in the past decade, owing to its unique physicochemical properties. However, further applications can be garnered from modified chitosan, specifically, depolymerized chitosan, with potentially useful applications in drug delivery or biomedicine. The use of microwave irradiation in depolymerization of chitosan appears to be more consequential than other methods, and results in modification of key physicochemical properties of chitosan, including molecular weight, viscosity and degree of deacetylation. In-depth review of such microwave-depolymerized chitosan and subsequent potential biopharmaceutical or biomedical applications has not been presented before. Herein, we present a detailed review of key physicochemical changes in chitosan following various depolymerization approaches, with focus on microwave irradiation and how these changes impact relevant biopharmaceutical or biomedical applications.

Overcoming Solubility Challenges: Self-emulsifying Systems for Enhancing the Delivery of Poorly Water-Soluble Antiviral Drugs.

The primary goal of drug formulation is to improve a drug's bioavailability in the body. However, poorly water-soluble drugs present challenging issues related to their solubility and bioavailability factors. Emerging technologies, such as lipid-based drug delivery systems, including micro- or nanoemulsifying drug delivery systems, have become increasingly relevant to address the above challenges. This review presents a thorough overview of self-emulsifying drug delivery systems (SEDDS). It covers the properties, principles, self-emulsification mechanism, formulation strategies, and characterization methods of SEDDS. This review also addresses the delivery of antiviral agents through SEDDS. Moreover, it summarizes the marketed formulations of SEDDS consisting of antiviral agents. This review offers a comprehensive and valuable resource for future perspectives on SEDDS and their potential applications in antiviral drug delivery.

Interpreting the efficacy enhancement mechanism of Chinese medicine processing from a biopharmaceutic perspective.

Chinese medicine processing (CMP) is a unique pharmaceutical technology that distinguishes it from natural medicines. Current research primarily focuses on changes in chemical components to understand the mechanisms behind efficacy enhancement in processing. However, this paper presents a novel perspective on the biopharmaceutics of CMP. It provides a comprehensive overview of the current research, emphasizing two crucial aspects: the role of 'heat' during processing and the utilization of processing adjuvants. The paper highlights the generation of easily absorbed components through the hydrolysis of glycosides by 'heat', as well as the facilitation of dissolution, absorption, and targeted distribution of active components through the utilization of processing adjuvants. From a biopharmaceutic perspective, this paper provides a lucid comprehension of the scientific foundation for augmenting the efficacy of CMP. Moreover, it proposes a three-dimensional research framework encompassing chemical reactions, phase transitions, and biopharmaceutical properties to further investigate the mechanisms involved in enhancing the efficacy of CMP.

Monitoring polysorbate 80 degradation in protein solutions using Total Holographic Characterization.

The degradation of polysorbate surfactants can limit the shelf life of biologic pharmaceutical products. Polysorbate is susceptible to degradation via either oxidation or hydrolysis pathways which releases free fatty acids (FFA) and other complex polymers. Degradants from Polysorbate 80 (PS80) can form particles and impact drug product quality. PS80 degradation products appear at low concentrations, and their refractive indexes are similar to that of the buffer, making them very challenging to detect. Furthermore, aggregates of FFA are similar in size and refractive index to protein aggregates adding complexity to characterizing these particles in protein solutions. Total Holographic Characterization (THC) is used in this work to characterize FFA particles of oleic acid and linoleic acid, the two most common degradation products of PS80. We demonstrate that the characteristic THC profile of the FFA oleic acid emulsion droplets can be used to monitor the degradation of PS80. THC can detect oleic acid at a concentration down to less than 100 ng/mL. Using the characteristic THC signal of oleic acid as a marker, the degradation of PS80 in protein solutions can be monitored quantitatively even in the presence of other contaminants of the same size, including silicone oil emulsion droplets and protein aggregates.

Capillary electrophoresis-mass spectrometry for protein analyses under native conditions: Current progress and perspectives.

Native mass spectrometry is a rapidly emerging technique for fast and sensitive structural analysis of protein constructs, maintaining the protein higher order structure. The coupling with electromigration separation techniques under native conditions enables the characterization of proteoforms and highly complex protein mixtures. In this review, we present an overview of current native CE-MS technology. First, the status of native separation conditions is described for capillary zone electrophoresis (CZE), affinity capillary electrophoresis (ACE), and capillary isoelectric focusing (CIEF), as well as their chip-based formats, including essential parameters such as electrolyte composition and capillary coatings. Further, conditions required for native ESI-MS of (large) protein constructs, including instrumental parameters of QTOF and Orbitrap systems, as well as requirements for native CE-MS interfacing are presented. On this basis, methods and applications of the different modes of native CE-MS are summarized and discussed in the context of biological, medical, and biopharmaceutical questions. Finally, key achievements are highlighted and concluded, while remaining challenges are pointed out.