Real-time estimation of bound water concentration during lyophilization with temperature-based state observers.

Lyophilization (aka freeze drying) has been shown to provide long-term stability for many crucial biotherapeutics, e.g., mRNA vaccines for COVID-19, allowing for higher storage temperature. The final stage of lyophilization, namely secondary drying, entails bound water removal via desorption, in which accurate prediction of bound water concentration is vital to ensuring the quality of the lyophilized product. This article proposes a novel technique for real-time estimation of the bound water concentration during secondary drying in lyophilization. A state observer is employed, which combines temperature measurement and mechanistic understanding of heat transfer and desorption kinetics, without requiring any online concentration measurement. Results from both simulations and experimental data show that the observer can accurately estimate the concentration of bound water in real time for all possible concentration levels, operating conditions, and measurement noise. This framework can also be applied for monitoring and control of the residual moisture in other desorption-related processes.

Non-invasive estimation of the powder size distribution from a single speckle image.

Non-invasive characterization of powders may take one of two approaches: imaging and counting individual particles; or relying on scattered light to estimate the particle size distribution (PSD) of the ensemble. The former approach runs into practical difficulties, as the system must conform to the working distance and other restrictions of the imaging optics. The latter approach requires an inverse map from the speckle autocorrelation to the particle sizes. The principle relies on the pupil function determining the basic sidelobe shape, whereas the particle size spread modulates the sidelobe intensity. We recently showed that it is feasible to invert the speckle autocorrelation and obtain the PSD using a neural network, trained efficiently through a physics-informed semi-generative approach. In this work, we eliminate one of the most time-consuming steps of our previous method by engineering the pupil function. By judiciously blocking portions of the pupil, we sacrifice some photons but in return we achieve much enhanced sidelobes and, hence, higher sensitivity to the change of the size distribution. The result is a 60 × reduction in total acquisition and processing time, or 0.25 seconds per frame in our implementation. Almost real-time operation in our system is not only more appealing toward rapid industrial adoption, it also paves the way for quantitative characterization of complex spatial or temporal dynamics in drying, blending, and other chemical and pharmaceutical manufacturing processes.

Multidose transient transfection of human embryonic kidney 293 cells modulates recombinant adeno-associated virus2/5 Rep protein expression and influences the enrichment fraction of filled capsids.

Recombinant adeno-associated virus (rAAV) is a commonly used in vivo gene therapy vector because of its nonpathogenicity, long-term transgene expression, broad tropism, and ability to transduce both dividing and nondividing cells. However, rAAV vector production via transient transfection of mammalian cells typically yields a low fraction of filled-to-total capsids (~1%-30% of total capsids produced). Analysis of our previously developed mechanistic model for rAAV2/5 production attributed these low fill fractions to a poorly coordinated timeline between capsid synthesis and viral DNA replication and the repression of later phase capsid formation by Rep proteins. Here, we extend the model by quantifying the expression dynamics of total Rep proteins and their influence on the key steps of rAAV2/5 production using a multiple dosing transfection of human embryonic kidney 293 (HEK293) cells. We report that the availability of preformed empty capsids and viral DNA copies per cell are not limiting to the capsid-filling reaction. However, optimal expression of Rep proteins (<240 ± 13 ag per cell) enables enrichment of the filled capsid population (>12% of total capsids/cell) upstream. Our analysis suggests increased enrichment of filled capsids via regulating the expression of Rep proteins is possible but at the expense of per cell capsid titer in a triple plasmid transfection. Our study reveals an intrinsic limitation of scaling rAAV2/5 vector genome (vg) production and underscores the need for approaches that allow for regulating the expression of Rep proteins to maximize vg titer per cell upstream.

The state of technological advancement to address challenges in the manufacture of rAAV gene therapies.

Current processes for the production of recombinant adeno-associated virus (rAAV) are inadequate to meet the surging demand for rAAV-based gene therapies. This article reviews recent advances that hold the potential to address current limitations in rAAV manufacturing. A multidisciplinary perspective on technological progress in rAAV production is presented, underscoring the necessity to move beyond incremental refinements and adopt a holistic strategy to address existing challenges. Since several recent reviews have thoroughly covered advancements in upstream technology, this article provides only a concise overview of these developments before moving to pivotal areas of rAAV manufacturing not well covered in other reviews, including analytical technologies for rapid and high-throughput measurement of rAAV quality attributes, mathematical modeling for platform and process optimization, and downstream approaches to maximize efficiency and rAAV yield. Novel technologies that have the potential to address the current gaps in rAAV manufacturing are highlighted. Implementation challenges and future research directions are critically discussed.

Mechanistic modeling of in vitro transcription incorporating effects of magnesium pyrophosphate crystallization.

The in vitro transcription (IVT) reaction used in the production of messenger RNA vaccines and therapies remains poorly quantitatively understood. Mechanistic modeling of IVT could inform reaction design, scale-up, and control. In this work, we develop a mechanistic model of IVT to include nucleation and growth of magnesium pyrophosphate crystals and subsequent agglomeration of crystals and DNA. To help generalize this model to different constructs, a novel quantitative description is included for the rate of transcription as a function of target sequence length, DNA concentration, and T7 RNA polymerase concentration. The model explains previously unexplained trends in IVT data and quantitatively predicts the effect of adding the pyrophosphatase enzyme to the reaction system. The model is validated on additional literature data showing an ability to predict transcription rates as a function of RNA sequence length.

Analysis of Poly(ethylene terephthalate) degradation kinetics of evolved IsPETase variants using a surface crowding model.

Poly(ethylene terephthalate) (PET) is a major plastic polymer utilized in the single-use and textile industries. The discovery of PET-degrading enzymes (PETases) has led to an increased interest in the biological recycling of PET in addition to mechanical recycling. IsPETase from Ideonella sakaiensis is a candidate catalyst, but little is understood about its structure-function relationships with regards to PET degradation. To understand the effects of mutations on IsPETase productivity, we develop a directed evolution assay to identify mutations beneficial to PET film degradation at 30 °C. IsPETase also displays enzyme concentration-dependent inhibition effects, and surface crowding has been proposed as a causal phenomenon. Based on total internal reflectance fluorescence microscopy and adsorption experiments, IsPETase is likely experiencing crowded conditions on PET films. Molecular dynamics simulations of IsPETase variants reveal a decrease in active site flexibility in free enzymes and reduced probability of productive active site formation in substrate-bound enzymes under crowding. Hence, we develop a surface crowding model to analyze the biochemical effects of three hit mutations (T116P, S238N, S290P) that enhanced ambient temperature activity and/or thermostability. We find that T116P decreases susceptibility to crowding, resulting in higher PET degradation product accumulation despite no change in intrinsic catalytic rate. In conclusion, we show that a macromolecular crowding-based biochemical model can be used to analyze the effects of mutations on properties of PETases and that crowding behavior is a major property to be targeted for enzyme engineering for improved PET degradation.

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel.

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries1 and electrocatalysts2. Experimental characterizations of such materials by operando microscopy produce rich image datasets3-6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Mechanistic modeling explains the production dynamics of recombinant adeno-associated virus with the baculovirus expression vector system.

Current manufacturing processes for recombinant adeno-associated viruses (rAAVs) have less-than-desired yields and produce significant amounts of empty capsids. The increasing demand and the high cost of goods for rAAV-based gene therapies motivate development of more efficient manufacturing processes. Recently, the US Food and Drug Administration (FDA) approved the first rAAV-based gene therapy product manufactured in the baculovirus expression vector system (BEVS), a technology that demonstrated production of high titers of full capsids. This work presents a first mechanistic model describing the key extracellular and intracellular phenomena occurring during baculovirus infection and rAAV maturation in the BEVS. The model predictions are successfully validated for in-house and literature experimental measurements of the vector genome and of structural and non-structural proteins collected during rAAV manufacturing in the BEVS with the TwoBac and ThreeBac constructs. A model-based analysis of the process is carried out to identify the bottlenecks that limit full capsid formation. Vector genome amplification is found to be the limiting step for rAAV production in Sf9 cells using either the TwoBac or ThreeBac system. In turn, vector genome amplification is hindered by limiting Rep78 levels. Transgene and non-essential baculovirus protein expression in the insect cell during rAAV manufacturing also negatively influences the rAAV production yields.

Extracting particle size distribution from laser speckle with a physics-enhanced autocorrelation-based estimator (PEACE).

Extracting quantitative information about highly scattering surfaces from an imaging system is challenging because the phase of the scattered light undergoes multiple folds upon propagation, resulting in complex speckle patterns. One specific application is the drying of wet powders in the pharmaceutical industry, where quantifying the particle size distribution (PSD) is of particular interest. A non-invasive and real-time monitoring probe in the drying process is required, but there is no suitable candidate for this purpose. In this report, we develop a theoretical relationship from the PSD to the speckle image and describe a physics-enhanced autocorrelation-based estimator (PEACE) machine learning algorithm for speckle analysis to measure the PSD of a powder surface. This method solves both the forward and inverse problems together and enjoys increased interpretability, since the machine learning approximator is regularized by the physical law.

Mechanistic modeling of viral particle production.

Viral systems such as wild-type viruses, viral vectors, and virus-like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial-scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild-type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in-silico testing of novel process operating strategies and/or advanced process control.

Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments.

Replacing fossil fuels with energy sources and carriers that are sustainable, environmentally benign, and affordable is amongst the most pressing challenges for future socio-economic development. To that goal, hydrogen is presumed to be the most promising energy carrier. Electrocatalytic water splitting, if driven by green electricity, would provide hydrogen with minimal CO2 footprint. The viability of water electrolysis still hinges on the availability of durable earth-abundant electrocatalyst materials and the overall process efficiency. This review spans from the fundamentals of electrocatalytically initiated water splitting to the very latest scientific findings from university and institutional research, also covering specifications and special features of the current industrial processes and those processes currently being tested in large-scale applications. Recently developed strategies are described for the optimisation and discovery of active and durable materials for electrodes that ever-increasingly harness first-principles calculations and machine learning. In addition, a technoeconomic analysis of water electrolysis is included that allows an assessment of the extent to which a large-scale implementation of water splitting can help to combat climate change. This review article is intended to cross-pollinate and strengthen efforts from fundamental understanding to technical implementation and to improve the 'junctions' between the field's physical chemists, materials scientists and engineers, as well as stimulate much-needed exchange among these groups on challenges encountered in the different domains.

Weighing the DNA Content of Adeno-Associated Virus Vectors with Zeptogram Precision Using Nanomechanical Resonators.

Quantifying the composition of viral vectors used in vaccine development and gene therapy is critical for assessing their functionality. Adeno-associated virus (AAV) vectors, which are the most widely used viral vectors for in vivo gene therapy, are typically characterized using PCR, ELISA, and analytical ultracentrifugation which require laborious protocols or hours of turnaround time. Emerging methods such as charge-detection mass spectroscopy, static light scattering, and mass photometry offer turnaround times of minutes for measuring AAV mass using optical or charge properties of AAV. Here, we demonstrate an orthogonal method where suspended nanomechanical resonators (SNR) are used to directly measure both AAV mass and aggregation from a few microliters of sample within minutes. We achieve a precision near 10 zeptograms which corresponds to 1% of the genome holding capacity of the AAV capsid. Our results show the potential of our method for providing real-time quality control of viral vectors during biomanufacturing.

Droplet-Based Evaporative System for the Estimation of Protein Crystallization Kinetics.

Crystallization is a potential cost-effective alternative to chromatography for the purification of biotherapeutic proteins. Crystallization kinetics are required for the design and control of such processes, but only a limited quantity of proteins is available during the initial stage of process development. This article describes the design of a droplet-based evaporative system for the evaluation of candidate crystallization conditions and the estimation of kinetics using only a droplet (on the order of µL) of protein solution. The temperature and humidity of air fed to a flow cell containing the droplet are controlled for evaporation and rehydration of the droplet, which are used for manipulating supersaturation. Dual-angle images of the droplet are taken and analyzed on-line to obtain the droplet volume and crystal sizes. Crystallization kinetics are estimated based on a first-principles process model and experimental data. Tight control of temperature and humidity of the air, fast and accurate image analysis, and accurate estimation of crystallization kinetics are experimentally demonstrated for a model protein lysozyme. The estimated kinetics are suitable for the model-based design and control of protein crystallization processes.

Mechanistic model for production of recombinant adeno-associated virus via triple transfection of HEK293 cells.

Manufacturing of recombinant adeno-associated virus (rAAV) viral vectors remains challenging, with low yields and low full:empty capsid ratios in the harvest. To elucidate the dynamics of recombinant viral production, we develop a mechanistic model for the synthesis of rAAV viral vectors by triple plasmid transfection based on the underlying biological processes derived from wild-type AAV. The model covers major steps starting from exogenous DNA delivery to the reaction cascade that forms viral proteins and DNA, which subsequently result in filled capsids, and the complex functions of the Rep protein as a regulator of the packaging plasmid gene expression and a catalyst for viral DNA packaging. We estimate kinetic parameters using dynamic data from literature and in-house triple transient transfection experiments. Model predictions of productivity changes as a result of the varied input plasmid ratio are benchmarked against transfection data from the literature. Sensitivity analysis suggests that (1) the poorly coordinated timeline of capsid synthesis and viral DNA replication results in a low ratio of full virions in harvest, and (2) repressive function of the Rep protein could be impeding capsid production at a later phase. The analyses from the mathematical model provide testable hypotheses for evaluation and reveal potential process bottlenecks that can be investigated.

Model-based control for column-based continuous viral inactivation of biopharmaceuticals.

Batch low-pH hold is a common processing step to inactivate enveloped viruses for biologics derived from mammalian sources. Increased interest in the transition of biopharmaceutical manufacturing from batch to continuous operation resulted in numerous attempts to adapt batch low-pH hold to continuous processing. However, control challenges with operating this system have not been directly addressed. This article describes a low-cost, column-based continuous viral inactivation system constructed with off-the-shelf components. Model-based, reaction-invariant pH controller is implemented to account for the nonlinearities with Bayesian estimation addressing variations in the operation. The residence time distribution is modeled as a plug flow reactor with axial dispersion in series with a continuously stirred tank reactor, and is periodically estimated during operation through inverse tracer experiments. The estimated residence time distribution quantifies the minimum residence time, which is used to adjust feed flow rates. Controller validation experiments demonstrate that pH and minimum residence time setpoint tracking and disturbance rejection are achieved with fast and accurate response and no instability. Viral inactivation testing demonstrates tight control of logarithmic reduction values over extended operation. This study provides tools for the design and operation of continuous viral inactivation systems in service of increasing productivity, improving product quality, and enhancing patient safety.

Cellular pathways of recombinant adeno-associated virus production for gene therapy.

Recombinant adeno-associated viruses (rAAVs) are among the most important vectors for in vivo gene therapies. With the rapid development of gene therapy, current rAAV manufacturing capacity faces a challenge to meet the emerging demand for these therapies in the future. To examine the bottlenecks in rAAV production during cell culture, we focus here on an analysis of cellular pathways of rAAV production, based on an overview of assembly mechanisms first in the wild-type (wt) AAV replication and then in the common methods of rAAV production. The differences analyzed between the wild-type and recombinant systems provide insights into the mechanistic differences that may correlate with viral productivity. Based on these analyses, we identify potential barriers to high productivity of rAAV and discuss future directions for improvement to meet the emerging needs set by the growth of rAAV-based therapy and the needs of patients.

Analytical methods for process and product characterization of recombinant adeno-associated virus-based gene therapies.

The optimization of upstream and downstream processes for production of recombinant adeno-associated virus (rAAV) with consistent quality depends on the ability to rapidly characterize critical quality attributes (CQAs). In the context of rAAV production, the virus titer, capsid content, and aggregation are identified as potential CQAs, affecting the potency, purity, and safety of rAAV-mediated gene therapy products. Analytical methods to measure these attributes commonly suffer from long turnaround times or low throughput for process development, although rapid, high-throughput methods are beginning to be developed and commercialized. These methods are not yet well established in academic or industrial practice, and supportive data are scarce. Here, we review both established and upcoming analytical methods for the quantification of rAAV quality attributes. In assessing each method, we highlight the progress toward rapid, at-line characterization of rAAV. Furthermore, we identify that a key challenge for transitioning from traditional to newer methods is the scarcity of academic and industrial experience with the latter. This literature review serves as a guide for the selection of analytical methods targeting quality attributes for rapid, high-throughput process characterization during process development of rAAV-mediated gene therapies.

Fictitious phase separation in Li layered oxides driven by electro-autocatalysis.

Layered oxides widely used as lithium-ion battery electrodes are designed to be cycled under conditions that avoid phase transitions. Although the desired single-phase composition ranges are well established near equilibrium, operando diffraction studies on many-particle porous electrodes have suggested phase separation during delithiation. Notably, the separation is not always observed, and never during lithiation. These anomalies have been attributed to irreversible processes during the first delithiation or reversible concentration-dependent diffusion. However, these explanations are not consistent with all experimental observations such as rate and path dependencies and particle-by-particle lithium concentration changes. Here, we show that the apparent phase separation is a dynamical artefact occurring in a many-particle system driven by autocatalytic electrochemical reactions, that is, an interfacial exchange current that increases with the extent of delithiation. We experimentally validate this population-dynamics model using the single-phase material Lix(Ni1/3Mn1/3Co1/3)O2 (0.5 < x < 1) and demonstrate generality with other transition-metal compositions. Operando diffraction and nanoscale oxidation-state mapping unambiguously prove that this fictitious phase separation is a repeatable non-equilibrium effect. We quantitatively confirm the theory with multiple-datastream-driven model extraction. More generally, our study experimentally demonstrates the control of ensemble stability by electro-autocatalysis, highlighting the importance of population dynamics in battery electrodes (even non-phase-separating ones).

Crystallization of a nonreplicating rotavirus vaccine candidate.

Nonreplicating rotavirus vaccine (NRRV) candidates are being developed with the aim of serving the needs of developing countries. A significant proportion of the cost of manufacturing such vaccines is the purification in multiple chromatography steps. Crystallization has the potential to reduce purification costs and provide new product storage modality, improved operational flexibility, and reduced facility footprints. This communication describes a systematic approach for the design of the crystallization of an NRRV candidate, VP8 subunit proteins fused to the P2 epitope of tetanus toxin, using first-principles models and preliminary experimental data. The first-principles models are applied to literature data to obtain feasible crystallization conditions and lower bounds for nucleation and growth rates. Crystallization is then performed in a hanging-drop vapor diffusion system, resulting in the nucleation and growth of NRRV crystals. The crystals obtained in a scaled-up evaporative crystallization contain proteins truncated in the P2 region, but have no significant differences with the original samples in terms of antibody binding and overall conformational stability. These results demonstrate the promise of evaporative crystallization of the NRRV.