An asymptotic description of a basic FcRn-regulated clearance mechanism and its implications for PBPK modelling of large antibodies.

A basic FcRn-regulated clearance mechanism is investigated using the method of matched asymptotic expansions. The broader aim of the work is to obtain further insight on the mechanism, thereby providing theoretical support for future pharmacologically-based pharmacokinetic modelling efforts. The corresponding governing equations are first non-dimensionalised and the order of magnitudes of the model parameters are assessed based on their values reported in the literature.

Assessing the performance of QSP models: biology as the driver for validation.

Validation of a quantitative model is a critical step in establishing confidence in the model's suitability for whatever analysis it was designed. While processes for validation are well-established in the statistical sciences, the field of quantitative systems pharmacology (QSP) has taken a more piecemeal approach to defining and demonstrating validation. Although classical statistical methods can be used in a QSP context, proper validation of a mechanistic systems model requires a more nuanced approach to what precisely is being validated, and what role said validation plays in the larger context of the analysis.

QSP Toolbox: Computational Implementation of Integrated Workflow Components for Deploying Multi-Scale Mechanistic Models.

Quantitative systems pharmacology (QSP) modeling has become increasingly important in pharmaceutical research and development, and is a powerful tool to gain mechanistic insights into the complex dynamics of biological systems in response to drug treatment. However, even once a suitable mathematical framework to describe the pathophysiology and mechanisms of interest is established, final model calibration and the exploration of variability can be challenging and time consuming. QSP models are often formulated as multi-scale, multi-compartment nonlinear systems of ordinary differential equations.

Targeted purification development enabled by computational biophysical modeling.

Chromatographic and non-chromatographic purification of biopharmaceuticals depend on the interactions between protein molecules and a solid-liquid interface. These interactions are dominated by the protein-surface properties, which are a function of protein sequence, structure, and dynamics. In addition, protein-surface properties are critical for in vivo recognition and activation, thus, purification strategies should strive to preserve structural integrity and retain desired pharmacological efficacy.