Prediction of Antibody Viscosity from Dilute Solution Measurements.

The high antibody doses required to achieve a therapeutic effect often necessitate high-concentration products that can lead to challenging viscosity issues in production and delivery. Predicting antibody viscosity in early development can play a pivotal role in reducing late-stage development costs. In recent years, numerous efforts have been made to predict antibody viscosity through dilute solution measurements. A key finding is that the entanglement of long, flexible complexes contributes to the sharp rise in antibody viscosity at the required dosing. This entanglement model establishes a connection between the two-body binding affinity and the many-body viscosity. Exploiting this insight, this study connects dilute solution measurements of self-association to high-concentration viscosity profiles to quantify the relationship between these regimes. The resulting model has exhibited success in predicting viscosity at high concentrations (around 150 mg/mL) from dilute solution measurements, with only a few outliers remaining. Our physics-based approach provides an understanding of fundamental physics, interpretable connections to experimental data, the potential to extrapolate beyond training conditions, and the capacity to effectively explain the physical mechanics behind these outliers. Conducting hypothesis-driven experiments that specifically target the viscosity and relaxation mechanisms of outlier molecules may allow us to unravel the intricacies of their behavior and, in turn, enhance the performance of our model.

Improved Diffusion Interaction Parameter Measurement to Predict the Viscosity of Concentrated mAb Solutions.

During the developability assessment of therapeutic monoclonal antibody (mAb) candidates, utilization of robust high-throughput predictive assays enables rapid selection of top candidates with low risks for late-stage development. Predicting the viscosities of highly concentrated mAbs using limited materials is an important aspect of developability assessment because high viscosity can complicate manufacturability, stability, and administration. Here, we report a high-throughput assay measuring protein-protein interactions to predict mAb viscosity. The diffusion interaction parameter (kD) measures colloidal self-association in dilute solutions and has been reported to be predictive of the mAb viscosity at high concentrations. However, kD of Amgen early stage IgG1 mAb candidates measured in 10 mM acetate at pH 5.2 containing sucrose and polysorbate (denoted A52SuT) shows only weak correlation to their viscosities at 140 mg/mL in A52SuT. We hypothesize that kD measured in A52SuT reflects primarily long-range electrostatic repulsions because most of these mAb candidates carry strong net positive charges in this low ionic strength formulation with pH (5.2) well below pI values of mAb candidates. However, the viscosities of high concentration mAbs depend heavily on short-range molecular interactions. We propose an improved kD method in which salt is added to suppress charge repulsions and to allow for detection of key short-range interactions in dilute solutions. Salt types and salt concentrations were screened, and an optimal salt condition was identified. This optimized method was further validated using two test mAb sets. Overall, the method improves the Pearson R2 between kD and viscosity (6-230 cP) from 0.24 to 0.80 for a data set consisting of 37 mAbs.

Evaluating the resolution of conventional optical microscopes through point spread function measurement.

In the imaging process of conventional optical microscopy, the primary factor hindering microscope resolution is the energy diffusion of incident light, most directly described by the point spread function (PSF). Therefore, accurate calculation and measurement of PSF are essential for evaluating and enhancing imaging resolution. Currently, there are various methods to obtain PSFs, each with different advantages and disadvantages suitable for different scenarios. To provide a comprehensive analysis of PSF-obtaining methods, this study classifies them into four categories based on different acquisition principles and analyzes their advantages and disadvantages, starting from the propagation property of light in optical physics. Finally, two PSF-obtaining methods are proposed based on mathematical modeling and deep learning, demonstrating their effectiveness through experimental results. This study compares and analyzes these results, highlighting the practical applications of image deblurring.

Off-axis three-mirror freeform systems design based on improved W-W differential equations.

Design of an off-axis system using the Wassermann-Wolf (W-W) differential equations can effectively eliminate the spherical aberration and coma problem; however, it is complicated and time consuming to calculate the discrete point coordinates on the freeform mirror surfaces due to multiple numbers of reference system transformation in the design process. This paper presents an improved W-W-differential-equations-based design method for off-axis three-mirror freeform systems. First, to reduce the number of coordinate transformations, a geometric relationship between different optical rays in an off-axis system is established using the distance between the central points of adjacent mirrors. Second, a three-dimensional rotation matrix is used to associate the optical paths passing through adjacent mirrors in different reference coordinate systems, and new simplified W-W differential equations based on the ray vectors are constructed. The experimental results show that our method can easily and effectively design off-axis three-mirror freeform systems with different parameters and structures, and the designed systems have good imaging quality.

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies.

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.

Three-dimensional modelling of blur property for conventional optical microscopes.

Intensity diffusion caused by optical diffraction limits the imaging resolution of conventional optical microscopes, therefore modelling and measuring the intensity transmission and distribution property of the light sources is a significant research topic in system development and pattern recognition. However, the complicated wave propagation process in optical imaging makes it difficult to provide a direct, analytical and simple mathematical model to measure the relationship between the blur degree and various camera parameters. In this study, an improved intensity transmission and distribution calculation method for conventional optical microscopes was proposed; furthermore, a simple mathematical relation between the blur degree and camera parameters was achieved based on the proposed method. First, the light intensity distribution and propagation characteristics of a conventional optical microscope were modeled based on the property of the Fresnel circular hole diffraction combined with the practical optical parameters. Second, by analyzing the property of intensity distribution and blurring imaging, a quantitative simplified mathematical relationship between the blur degree and camera parameters in optical microscope imaging was obtained, and the three-dimensional (3D) blur property in the optical imaging process was analyzed under different conditions. Third, the connection between diffractive optics and geometric optics was obtained by summarizing and generalizing the 3D blur property curve of each monochromatic light source. Finally, the proposed method was verified through a series of simulations and experiments.

Conformational Changes and Drivers of Monoclonal Antibody Liquid-Liquid Phase Separation.

Liquid-liquid phase separation is a phenomenon within biology whereby proteins can separate into dense and more dilute phases with distinct properties. Three antibodies that undergo liquid-liquid phase separation were characterized in the protein-rich and protein-poor phases. In comparison to the protein-poor phase, the protein-rich phase demonstrates more blue-shift tryptophan emissions and red-shifted amide I absorbances. Large changes involving conformational isomerization around disulfide bonds were observed using Raman spectroscopy. Amide I and protein fluorescence differences between the phases persisted to temperatures above the critical temperature but ceased at the temperature at which aggregation occurred. In addition, large changes occurred in the structural organization of water molecules within the protein-rich phase for all three antibodies. It is hypothesized that as the proteins have the same chemical potential in both phases, the protein viscosity is higher in the protein-rich phase resulting in slowed diffusion dependent protein aggregation in this phase. For all three antibodies we performed accelerated stability studies and found that the protein-rich phase aggregated at the same rate or slower than the protein-poor phase.

A Robust and Low Computational Cost Pitch Estimation Method.

Pitch estimation is widely used in speech and audio signal processing. However, the current methods of modeling harmonic structure used for pitch estimation cannot always match the harmonic distribution of actual signals. Due to the structure of vocal tract, the acoustic nature of musical equipment, and the spectrum leakage issue, speech and audio signals' harmonic frequencies often slightly deviate from the integer multiple of the pitch. This paper starts with the summation of residual harmonics (SRH) method and makes two main modifications. First, the spectral peak position constraint of strict integer multiple is modified to allow slight deviation, which benefits capturing harmonics. Second, a main pitch segment extension scheme with low computational cost feature is proposed to utilize the smooth prior of pitch more efficiently. Besides, the pitch segment extension scheme is also integrated into the SRH method's voiced/unvoiced decision to reduce short-term errors. Accuracy comparison experiments with ten pitch estimation methods show that the proposed method has better overall accuracy and robustness. Time cost experiments show that the time cost of the proposed method reduces to around 1/8 of the state-of-the-art fast NLS method on the experimental computer.

An Improvement to Conformer-Based Model for High-Accuracy Speech Feature Extraction and Learning.

Owing to the loss of effective information and incomplete feature extraction caused by the convolution and pooling operations in a convolution subsampling network, the accuracy and speed of current speech processing architectures based on the conformer model are influenced because the shallow features of speech signals are not completely extracted. To solve these problems, in this study, we researched a method that used a capsule network to improve the accuracy of feature extraction in a conformer-based model, and then, we proposed a new end-to-end model architecture for speech recognition. First, to improve the accuracy of speech feature extraction, a capsule network with a dynamic routing mechanism was introduced into the conformer model; thus, the structural information in speech was preserved, and it was input to the conformer blocks via sequestered vectors; the learning ability of the conformed-based model was significantly enhanced using dynamic weight updating. Second, a residual network was added to the capsule blocks, thus, the mapping ability of our model was improved and the training difficulty was reduced. Furthermore, the bi-transformer model was adopted in the decoding network to promote the consistency of the hypotheses in different directions through bidirectional modeling. Finally, the effectiveness and robustness of the proposed model were verified against different types of recognition models by performing multiple sets of experiments. The experimental results demonstrated that our speech recognition model achieved a lower word error rate without a language model because of the higher accuracy of speech feature extraction and learning using our model architecture with a capsule network. Furthermore, our model architecture benefited from the advantage of the capsule network and the conformer encoder, and also has potential for other speech-related applications.

Intra-Micellar and Extra-Micellar Oxidation in Phosphate and Histidine Buffers Containing Polysorbate 80.

Polysorbate is a key excipient included in formulations of therapeutic proteins to help prevent aggregation and surface adsorption. The stability of both polysorbate and therapeutic proteins can be compromised by oxidative degradation. In general, polysorbate is added to formulations at concentrations above the critical micelle concentration (cmc). To date, however, few experiments have quantitatively addressed the extent of extra- and intra-micellar oxidation of polysorbate in pharmaceutically relevant buffers. This study utilizes 2,2'-azobis(2-methylpropionamidine)dihydrochloride (AAPH), a peroxyl radical-generating initiator, C11-BODIPY(581/591), a lipid peroxidation probe, and fluorescence spectroscopy to reveal that both intra- and extra-micellar oxidation proceed in pharmaceutically relevant phosphate and histidine buffers. It is further demonstrated that the relative extent of oxidation observed in the intra- and extra-micellar compartments is similar irrespective of the buffer system.

Effect of the ADCC-Modulating Mutations and the Selection of Human IgG Isotypes on Physicochemical Properties of Fc.

Monoclonal antibodies, particularly IgGs and Ig-based molecules, are a well-established and growing class of biotherapeutic drugs. In order to improve efficacy, potency and pharmacokinetics of these therapeutic drugs, pharmaceutical industries have investigated significantly in engineering fragment crystallizable (Fc) domain of these drugs to optimize the interactions of these drugs and Fc gamma receptors (FcγRs) in recent ten years. The biological function of the therapeutics with the antibody-dependent cellular cytotoxicity (ADCC) enhanced double mutation (S239D/I332E) of isotype IgG1, the ADCC reduced double mutation (L234A/L235A) of isotype IgG1, and ADCC reduced isotype IgG4 has been well understood. However, limited information regarding the effect of these mutations or isotype difference on physicochemical properties (PCP), developability, and manufacturability of therapeutics bearing these different Fc regions is available. In this report, we systematically characterize the effects of the mutations and IgG4 isotype on conformation stability, colloidal stability, solubility, and storage stability at accelerated conditions in two buffer systems using six Fc variants. Our results provide a basis for selecting appropriate Fc region during development of IgG or Ig-based therapeutics and predicting effect of the mutations on CMC development process.

An adapted consensus protein design strategy for identifying globally optimal biotherapeutics.

Biotherapeutic optimization, whether to improve general properties or to engineer specific attributes, is a time-consuming process with uncertain outcomes. Conversely, Consensus Protein Design has been shown to be a viable approach to enhance protein stability while retaining function. In adapting this method for a more limited number of protein sequences, we studied 21 consensus single-point variants from eight publicly available CD3 binding sequences with high similarity but diverse biophysical and pharmacological properties. All single-point consensus variants retained CD3 binding and performed similarly in cell-based functional assays. Using Ridge regression analysis, we identified the variants and sequence positions with overall beneficial effects on developability attributes of the CD3 binders. A second round of sequence generation that combined these substitutions into a single molecule yielded a unique CD3 binder with globally optimized developability attributes. In this first application to therapeutic antibodies, adapted Consensus Protein Design was found to be highly beneficial within lead optimization, conserving resources and minimizing iterations. Future implementations of this general strategy may help accelerate drug discovery and improve success rates in bringing novel biotherapeutics to market.

Automatic Speech Recognition Performance Improvement for Mandarin Based on Optimizing Gain Control Strategy.

Automatic speech recognition (ASR) is an essential technique of human-computer interactions; gain control is a commonly used operation in ASR. However, inappropriate gain control strategies can lead to an increase in the word error rate (WER) of ASR. As there is a current lack of sufficient theoretical analyses and proof of the relationship between gain control and WER, various unconstrained gain control strategies have been adopted on realistic ASR systems, and the optimal gain control with respect to the lowest WER, is rarely achieved. A gain control strategy named maximized original signal transmission (MOST) is proposed in this study to minimize the adverse impact of gain control on ASR systems. First, by modeling the gain control strategy, the quantitative relationship between the gain control strategy and the ASR performance was established using the noise figure index. Second, through an analysis of the quantitative relationship, an optimal MOST gain control strategy with minimal performance degradation was theoretically deduced. Finally, comprehensive comparative experiments on a Mandarin dataset show that the proposed MOST gain control strategy can significantly reduce the WER of the experimental ASR system, with a 10% mean absolute WER reduction at -9 dB gain.

pH-Dependent Phase Behavior and Stability of Cationic Lipid-mRNA Nanoparticles.

Lipid nanoparticles (LNPs) containing mRNA can deliver genetic material to cells for use as vaccines or protein replacement therapies. We characterized the effect of solution pH on cationic LNPs containing green fluorescent protein (EGFP) mRNA and their transfection efficiency. We compared the structural and colloidal properties of mRNA LNPs with LNPs not containing mRNA and mRNA free in solution. We used a combination of biophysical technique to build a picture of the structure of the lipids and mRNA across pH and temperature in the form of an empirical phase diagram (EPD). A combination of Fourier-transform infrared (FTIR) spectroscopy and differential scanning calorimetry was used to investigate lipid phase behavior. The mRNA-LNPs transition from an inverse hexagonal phase at pH values below the pKa of the cationic lipid to a lamellar phase above the pKa. At higher temperatures the mRNA-LNPs also transitioned from an inverse hexagonal phase to a lamellar phase indicating the inverse hexagonal phase is more thermodynamically favorable. Based on circular dichroism, the mRNA within the LNP has more A form structure at pH values below the lipid pKa than above it. Optical density, zeta potential and dynamic light scattering measurements were used to probe the colloidal stability of the mRNA-LNPs. The particles were larger and more prone to aggregation below the pKa. A stability study was performed to relate the biophysical characteristics to the storage of the particles in solution at 4 and 25 °C. mRNA-LNPs had the highest transfection efficiency and stability at pH values below the pKa. However, there was a trade-off between the stability and aggregation propensity since at very low pH the particles were most prone to aggregation. We performed kinetic experiments to show that the time scale of the pH-dependent phase behavior is slow (6 hour transition) and the transition from lamellar to inverse hexagonal phases is irreversible. This suggests that the lamellar phase is less stable and kinetically trapped. Our findings deepen our structural understanding of mRNA-LNPs and will aid the development of related formulations.

Global deblurring for continuous out-of-focus images using a depth-varying diffusion model.

The phenomenon of continuous out-of-focus imaging often occurs in high-magnification optical microscopy when observing large-scale targets. Lacking of accurate depth-varying point spread functions (DVPSFs) for blurred regions at different depths, it is difficult to locally reconstruct the clear images of these blurred regions using traditional deblurring methods, making it unreasonable to globally observe the optical features of large-scale targets in high-magnification optical microscopy. This paper proposes a global deblurring method for continuous out-of-focus images of large-scale sphere samples. In this study, first we analyze the energy diffusion characteristics of the optical imaging process, integrating the relationship between high-frequency energy parameters, optical range distance, and depth of field, and we propose a three-dimensional continuous energy diffusion model for optical imaging. Next, we propose an adaptive weight depth calculation method for a continuously changing surface based on the depth varying diffusion model by introducing the sample surface curvature variation and light direction. Finally, we propose a universal method for deblurring continuous out-of-focus images of large-scale sphere samples for the purpose of observing the global optical features in high-magnification optical microscopy. Moreover, we use dynamic microspheres of different sizes to verify the effectiveness of our proposed method. The results prove that our proposed method can accurately calculate the depth of the sample surface and the energy diffusion parameters at each depth, and it can achieve the image deblurring of a continuously changing surface and the global deblurring of multiple samples in a wide field of view.

Determination of the SLAMF1 self-association affinity constant with sedimentation velocity ultracentrifugation.

Signaling lymphocytic activating molecule family member 1 (SLAMF1 or CD150) is a cell surface glycoprotein expressed on various immune populations, regulating cell-cell interactions, activation, differentiation, and inflammatory responses and has been suggested as a potential target for inflammatory diseases. Signaling is believed to be mediated by high-affinity homophilic interactions; the recombinant soluble form of SLAMF1 has optimal activity in the range of 20 µg/mL. This contradicts with a rather weak homo-dimerization binding constant (KD) value reported previously; however, the analytical approach and data analysis suffered from various technical limitations at the time and therefore warrants re-examination. To address this apparent discrepancy, we determined the KD of soluble SLAMF1 using sedimentation velocity analytical ultracentrifuge (SV-AUC). A globally fitted monomer-dimer model properly explains the data from a wide concentration range obtained with both UV and fluorescence detection systems. The analysis suggests the dimerization KD value for human SLAMF1 is 0.48 µM. Additionally, our data show that SLAMF1 self-association is not driven by non-specific binding to glycans supporting the view of specific protein-protein interaction. We anticipate antibody biotherapeutics capable of modulating the biological consequences of SLAMF1 interactions will be readily identified.

Cis/Trans Isomerization of Unsaturated Fatty Acids in Polysorbate 80 During Light Exposure of a Monoclonal Antibody-Containing Formulation.

Light exposure of a monoclonal antibody formulation containing polysorbate 80 (PS80) leads to cis/trans isomerization of monounsaturated and polyunsaturated fatty acids. This cis/trans isomerization was monitored by positive electrospray ionization mass spectrometry of intact PS80 components as well as by negative ion electrospray ionization mass spectrometry analysis of free fatty acids generated via esterase-catalyzed hydrolysis. The light-induced cis/trans isomerization of unsaturated fatty acids in PS80 required the presence of the monoclonal antibody, or, at a minimum (for mechanistic studies), a combination of N-acetyltryptophan amide and glutathione disulfide, suggesting the involvement of thiyl radicals generated by photoinduced electron transfer from Trp to the disulfide. Product analysis confirmed the conversion of PS80-bound oleic acid to elaidic acid; furthermore, together with linoleic acid, we detected conjugated linoleic acids in PS80, which underwent light-induced cis/trans isomerization.

Comparison of Polysorbate 80 Hydrolysis and Oxidation on the Aggregation of a Monoclonal Antibody.

Polysorbates are used ubiquitously in protein therapeutic drugs to help minimize adsorption to surfaces and aggregation. It has been recognized that polysorbate can itself degrade and in turn result in loss of efficacy of therapeutic proteins. We studied the 2 main pathways of polysorbate 80 (PS80) degradation, enzymatic ester hydrolysis, and oxidation. Degraded polysorbates were quantified through mass spectrometry to identify the loss of individual components. Next Langmuir trough adsorption isotherms were used to characterize changes in the surface activity of the degraded polysorbates. PS80 degraded via hydrolysis results in slower surface adsorption rates, whereas the oxidized PS80 show increased surface activity. However, the critical micelle concentration remained unchanged. A monoclonal antibody was formulated with stock and degraded polysorbates to probe their ability to prevent aggregation. Hydrolyzed polysorbate resulted in a large increase in particle formation during shaking stress. Oxidized PS80 was still protective against aggregation for the monoclonal antibody. Monomer loss as measured by SEC was comparable in formulations without PS80 to those with esterase hydrolyzed PS80. Monomer loss for oxidized PS80 was similar to that of nondegraded PS80. Hydrolysis of PS80 resulted in free fatty acids which formed insoluble particles during mechanical agitation which stimulated protein aggregation.

Effect of Iron Oxide Nanoparticles on the Oxidation and Secondary Structure of Growth Hormone.

Oxidation of therapeutic proteins (TPs) can lead to changes in their pharmacokinetics, biological activity and immunogenicity. Metal impurities such as iron are known to increase oxidation of TPs, but nanoparticulate metals have unique physical and chemical properties compared to the bulk material or free metal ions. Iron oxide nanoparticles (IONPs) may originate from equipment used in the manufacturing of TPs or from needles during injection. In this study, the impact of IONPs on oxidation of a model protein, rat growth hormone (rGH), was investigated under chemical stress. Hydrogen peroxide (H2O2)- and 2,2'-azobis (2-methylpropionamidine) dihydrochloride oxidized methionine residues of rGH, but unexpectedly, oxidation was suppressed in the presence of IONPs compared to a phosphate buffer control. Fourier transform infrared spectroscopy indicated splitting of the α-helical absorbance band in the presence of IONPs, whereas circular dichroism spectra showed a reduced α-helical contribution with increasing temperature for both rGH and rGH-IONP mixtures. The results collectively indicate that IONPs can increase the chemical stability of rGH by altering the kinetics and preference of amino acid residues that are oxidized, although the changes in protein secondary structure by IONPs may lead to alterations of physical stability.

Developing Biologics Tablets: The Effects of Compression on the Structure and Stability of Bovine Serum Albumin and Lysozyme.

Oral administration is advantageous compared to the commonly used parenteral administration for local therapeutic uses of biologics or mucosal vaccines, since it can specifically target the gastrointestinal (GI) tract. It offers better patient compliance, even though the general use of such a delivery route is often limited by potential drug degradation in the GI tract and poor absorption. Using bovine serum albumin (BSA) and lysozyme as two model proteins, we studied their solid-state properties, mechanical properties, and tabletability as well as effects of compaction pressure, particle size, and humidity on protein degradation. It was found that BSA and lysozyme are highly hygroscopic, and their tablet manufacturability (powder caking, punch sticking, and tablet lamination) is sensitive to the humidity. BSA and lysozyme exhibited high plasticity and excellent tabletability and remained amorphous at high pressure and humidity. As for protein stability, lysozyme was resistant to high pressure (up to 300 MPa) and high humidity (up to 93%). In contrast, BSA underwent aggregation upon compression, an effect that was more pronounced for smaller BSA particles. High humidity accelerated the aggregation of BSA during incubation, but it did not further synergize with mechanical stress to induce protein degradation. Thus, compression can potentially induce protein aggregation, but this effect is protein-dependent. Therefore, strategies (e.g., the use of excipients, optimized manufacturing processes) to inhibit protein degradation should be explored before their tablet dosage form development.