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.

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.

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We report the first Ga,O,(Gd,O,) insulated gate n-channel enhancement-mode Iq.53G%,4,As MOSFETs on InP semi-insulating substrate. A 0.75 x 50 pm2 gate device exhibits an extrinsic transconductance of 190 mS/mm which is an order of magnitude improvement over previously reported values.In, 53Gq,47As lattice-matched to InP substrate is a promising semiconductor for electronic and long wavelength optical communication applications due to the large T-L intervalley separation, high low-field carrier mobility and high saturation velocity. However, the Schottky gate characteristics on InGaAs are poor. Previously, various techniques, such as plasma oxidation, silicon dioxide, and silicon nitride, have been used to passivate the InGaAs surface to form the MIS structure for better gate characteristics. In this work, we have investigated I n G a s MOSFET using a mixture of Ga,O, and Gd,O, as the gate dielectric evaporated from a high purity single crystal Gd,Ga,O,, source.The epitaxial layers of InGaAs MOSFET were grown on semi-insulating InP with a gas source molecular beam epitaxy (GSMBE) system using Be as the p-type dopant. A crosssectional view of the n-channel InGaAs MOSFET is shown in Fig. 1. The source and drain regions were selectively implanted with Si for low resistance ohmic contacts. The implanted dopant was activated by annealing at 650 "C for 5 minutes. The wafer was then transferred to a solid source MBE chamber and the native oxides of InGaAs were thermally desorbed at substrate temperatures of 520-550 "C under an As overpressure. The preservation of surface periodicity and atomic order was monitored by in-situ reflection high energy electron diffraction (WEED). After oxide desorption, the wafer was transferred under vacuum (lo-'' Torr) into a second chamber and Gaz0,(Gd,03) was deposited on the InGaAs with e-beam evaporation at a substrate temperature of 535 "C. AuBe/Pt/Au, Ge/Ni/AuGe/Mo/Au and Pt/Ti/Pt/Au were then deposited for the contacts of p-well, n-source (and drain), and gate electrode, respectively. Fig. 2 shows the drain I-V characteristics of a typical deviceand the threshold voltage is 0.4 V. There is no drain-current drifting or hysteresis observed. Fig. 3. illustrates dependence of the extrinsic transconductance on device gate length. The effective mobility of 470 cm'Ns is derived from the variation of drain conductance, g,, versus gate voltage at small drain voltage (-0 V). The rf characteristics of the same device are shown in Fig. 4. The current gain cut-off frequency and the maximum frequency of oscillation of 6.8 and 7.8 GHz were obtained, respectively.The results presented here in combination with our recent demonstration of enhancement mode GaAs MOSFETs show that the in-situ deposition of Ga,O,(Gd,O,> has opened up the possibility for the applications of 111-V MOSFET technlolgies.

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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.

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The methylotrophic yeast Pichia pastoris is widely used as a microbial host for recombinant protein production. Bioreactor models for P. pastoris can inform understanding of cellular metabolism and can be used to optimize bioreactor operation. This article constructs an extensive macroscopic bioreactor model for P. pastoris which describes substrates, biomass, total protein, other medium components, and off‐gas components. Species and elemental balances are introduced to describe uptake and evolution rates for medium components and off‐gas components. Additionally, a pH model is constructed using an overall charge balance, acid/base equilibria, and activity coefficients to describe production of recombinant protein and precipitation of medium components. The extent of run‐to‐run variability is modeled by distributions of a subset of the model parameters, which are estimated using the maximum likelihood method. Model prediction from the extensive macroscopic bioreactor model well describes experimental data with different operating conditions. The probability distributions of the model predictions quantified from the parameter distribution are quantifiably consistent with the run‐to‐run variability observed in the experimental data. The uncertainty description in this macroscopic bioreactor model identifies the model parameters that have large variability and provides guidance as to which aspects of cellular metabolism should be the focus of additional experimental studies. The model for medium components with pH and precipitation can be used for improving chemically defined medium by minimizing the amount of components needed while meeting cellular requirements.