We present results on the thermodynamic and structural aspects of the hydration of hydrophobic solutes in three tetramethylammonium [N(CH 3 ) 4 + ] salt solutions at various concentrations obtained from molecular dynamics simulations. Monovalent counterions of different sizessF -, Cl -, and a relatively large model ion BIsare chosen in order to cover a range of kosmotropic to chaotropic behaviors. Chemical potentials of hard-sphere solutes obtained using test particle insertions display both salting-in and salting-out effects depending on the type of salt. Water and salt-ion densities in the vicinity of hard-sphere solutes are calculated. Small and strongly hydrated Fions (kosmotropes) are excluded from the vicinity of hydrophobic solutes, leading to an increase in local water densities near hydrophobic solutes (i.e., preferential hydration). This increases the excess chemical potential of hydrophobic solutes in solution which leads to salting-out. Opposite behavior is observed for large, less favorably hydrated BIions (chaotropes) which associate strongly with hydrophobic solutes. Compressive forces due to neighboring water molecules, cations, and anions on the surface of the hard sphere solute are calculated. We find that water molecules make the most significant contribution toward the total compressive force. This explains the observed linear correlation between the extent of preferential hydration or dehydration of the solute surface and salting-out or salting-in effects. The trends in the thermodynamics of hydration of hydrophobic solutes upon addition of salts are explained in terms of the structural hydration of individual salt ions.

Quantitative Structure-Retention Relationship (QSRR) models are developed for the prediction of protein retention times in anion-exchange chromatography systems. Topological, subdivided surface area, and TAE (Transferable Atom Equivalent) electron-density-based descriptors are computed directly for a set of proteins using molecular connectivity patterns and crystal structure geometries. A novel algorithm based on Support Vector Machine (SVM) regression has been employed to obtain predictive QSRR models using a two-step computational strategy. In the first step, a sparse linear SVM was utilized as a feature selection procedure to remove irrelevant or redundant information. Subsequently, the selected features were used to produce an ensemble of nonlinear SVM regression models that were combined using bootstrap aggregation (bagging) techniques, where various combinations of training and validation data sets were selected from the pool of available data. A visualization scheme (star plots) was used to display the relative importance of each selected descriptor in the final set of "bagged" models. Once these predictive models have been validated, they can be used as an automated prediction tool for virtual high-throughput screening (VHTS).

For many protein therapeutics including monoclonal antibodies, aggregate removal process can be complex and challenging. We evaluated two different process analytical technology (PAT) applications that couple a purification unit performing preparative hydrophobic interaction chromatography (HIC) to a multi-angle light scattering (MALS) system. Using first principle measurements, the MALS detector calculates weight-average molar mass, Mw and can control aggregate levels in purification. The first application uses an in-line MALS to send start/stop fractionation trigger signals directly to the purification unit when preset Mw criteria are met or unmet. This occurs in real-time and eliminates the need for analysis after purification. The second application uses on-line ultra-high performance size-exclusion liquid chromatography to sample from the purification stream, separating the mAb species and confirming their Mw using a µMALS detector. The percent dimer (1.5%) determined by the on-line method is in agreement with the data from the in-line application (Mw increase of approximately 2750 Da). The novel HIC-MALS systems demonstrated here can be used as a powerful tool for real-time aggregate monitoring and control during biologics purification enabling future real time release of biotherapeutics.

There has been increasing momentum recently in the biopharmaceutical industry to transition from traditional batch processes to next‐generation integrated and continuous biomanufacturing. This transition from batch to continuous is expected to offer several advantages which, taken together, could significantly improve access to biologics drugs for patients. Despite this recent momentum, there has not been a commercial implementation of a continuous bioprocess reported in the literature. In this study, we describe a successful pilot‐scale proof‐of‐concept demonstration of an end‐to‐end integrated and continuous bioprocess for the production of a monoclonal antibody (mAb). This process incorporated all of the key unit operations found in a typical mAb production process, including the final steps of virus removal filtration, ultrafiltration, diafiltration, and formulation. The end‐to‐end integrated process was operated for a total of 25 days and produced a total of 4.9 kg (200 g/day or 2 g/L BRX/day) of the drug substance from a 100‐L perfusion bioreactor (BRX) with acceptable product quality and minimal operator intervention. This successful proof‐of‐concept demonstrates that end‐to‐end integrated continuous bioprocessing is achievable with current technologies and represents an important step toward the realization of a commercial integrated and continuous bioprocessing process.

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