Development and qualification of 3 L scale-down model for large scale vaccine process on Vero cell culture using microcarriers.

Scale-down models (SDM) are pivotal tools for process understanding and improvement to accelerate the development of vaccines from laboratory research to global commercialization. In this study, a 3 L SDM representing a 50 L scale Vero cell culture process of a live-attenuated virus vaccine using microcarriers was developed and qualified based on the constant impeller power per volume principle. Both multivariate data analysis (MVDA) and the traditional univariate data analysis showed comparable and equivalent cell growth, metabolic activity, and product quality results across scales.

Effects of process parameters on tablet critical quality attributes in continuous direct compression: a case study of integrating data-driven statistical models and mechanistic compaction models.

Continuous manufacturing of oral-dosage drug products is increasing the need for rigorous process understanding both from a process design and control perspective. The purpose of this study is to develop a methodology that analyzes the effects of upstream process parameters on continuous tablet compaction and then correlates associated upstream variables to the final tablet attributes (e.g.

Assessment of spatial heterogeneity in continuous twin screw wet granulation process using three-compartmental population balance model.

In this study, a novel three-compartmental population balance model (PBM) for a continuous twin screw wet granulation process is developed, combining the techniques of PBM and regression process modeling. The developed model links screw configuration, screw speed, and blend throughput with granule properties to predict the granule size distribution (GSD) and volume-average granule diameter. The granulator screw barrel was divided into three compartments along barrel length: wetting compartment, mixing compartment, and steady growth compartment.

Systems biology of platelet-vessel wall interactions.

Blood systems biology seeks to quantify outside-in signaling as platelets respond to numerous external stimuli, typically under flow conditions. Platelets can activate via GPVI collagen receptor and numerous G-protein coupled receptors (GPCRs) responsive to ADP, thromboxane, thrombin, and prostacyclin. A bottom-up ODE approach allowed prediction of platelet calcium and phosphoinositides following P2Y1 activation with ADP, either for a population average or single cell stochastic behavior.

Multiscale prediction of patient-specific platelet function under flow.

During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient's platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost.

Simulation of aggregating particles in complex flows by the lattice kinetic Monte Carlo method.

We develop and validate an efficient lattice kinetic Monte Carlo (LKMC) method for simulating particle aggregation in laminar flows with spatially varying shear rate, such as parabolic flow or flows with standing vortices. A contact time model was developed to describe the particle-particle collision efficiency as a function of the local shear rate, G, and approach angle, θ. This model effectively accounts for the hydrodynamic interactions between approaching particles, which is not explicitly considered in the LKMC framework.

Lattice kinetic Monte Carlo simulations of convective-diffusive systems.

Diverse phenomena in physical, chemical, and biological systems exhibit significant stochasticity and therefore require appropriate simulations that incorporate noise explicitly into the dynamics. We present a lattice kinetic Monte Carlo approach to simulate the trajectories of tracer particles within a system in which both diffusive and convective transports are operational. While diffusive transport is readily accounted for in a kinetic Monte Carlo simulation, we demonstrate that the inclusion of bulk convection by simply biasing the rate of diffusion with the rate of convection creates unphysical, shocklike behavior in concentrated systems due to particle pile up.