Methodologies for Quantitative Systems Pharmacology (QSP) Models: Design and Estimation.

With the increased interest in the application of quantitative systems pharmacology (QSP) models within medicine research and development, there is an increasing need to formalize model development and verification aspects. In February 2016, a workshop was held at Roche Pharma Research and Early Development to focus discussions on two critical methodological aspects of QSP model development: optimal structural granularity and parameter estimation. We here report in a perspective article a summary of presentations and discussions.

A Mathematical Modeling Approach to Understanding the Effect of Anti-Interleukin Therapy on Eosinophils.

Emerging T-helper type 2 (Th2 ) cytokine-based asthma therapies, such as tralokinumab, lebrikizumab (anti-interleukin (IL)-13), and mepolizumab (anti-IL-5), have shown differences in their blood eosinophil (EOS) response. To better understand these effects, we developed a mathematical model of EOS dynamics. For the anti-IL-13 therapies, lebrikizumab and tralokinumab, the model predicted an increase of 30% and 10% in total and activated EOS in the blood, respectively, and a decrease in the total and activated EOS in the airways. The model predicted a rapid decrease in total and activated EOS levels in blood and airways for the anti-IL-5 therapy mepolizumab. All model-based predictions were consistent with published clinical observations. The modeling approach provided insights into EOS response after treatment with Th2 -targeted therapies, and supports the hypothesis that an increase in blood EOS after anti-IL-13 therapy is part of the pharmacological action of these therapies.

Predicting the impact of physiological and biochemical processes on oral drug bioavailability.

Recent advances in computational methods applied to the fields of drug delivery and biopharmaceutics will be reviewed with a focus on prediction of the impact of physiological and biochemical factors on simulation of gastrointestinal absorption and bioavailability. Our application of a gastrointestinal simulation for the prediction of oral drug absorption and bioavailability will be described. First, we collected literature data or we estimated biopharmaceutical properties by application of statistical methods to a set of 2D and 3D molecular descriptors. Second, we integrated the differential equations for an advanced compartmental absorption and transit (ACAT) model in order to determine the rate, extent, and approximate gastrointestinal location of drug liberation (for controlled release), dissolution, passive and carrier-mediated absorption, and saturable metabolism and efflux. We predict fraction absorbed, bioavailability, and C(p) vs. time profiles for common drugs and compare those estimates to literature data. We illustrate the simulated impact of physiological and biochemical processes on oral drug bioavailability.

Evaluating systems pharmacology models is different from evaluating standard pharmacokinetic-pharmacodynamic models.

Based on the author's recent experience, there appears to be some confusion regarding the steps required to qualify a systems pharmacology model as adequate for the intended purpose. This manuscript outlines the model evaluation approach used in the author's recent publication(1) on the systems pharmacology of a 5-lipoxygenase inhibitor and is an attempt to generate discussion on this topic within the pharmacometrics and systems pharmacology community.

Effects of IL-1ß-Blocking Therapies in Type 2 Diabetes Mellitus: A Quantitative Systems Pharmacology Modeling Approach to Explore Underlying Mechanisms.

Recent clinical studies suggest sustained treatment effects of interleukin-1ß (IL-1ß)-blocking therapies in type 2 diabetes mellitus. The underlying mechanisms of these effects, however, remain underexplored. Using a quantitative systems pharmacology modeling approach, we combined ex vivo data of IL-1ß effects on ß-cell function and turnover with a disease progression model of the long-term interactions between insulin, glucose, and ß-cell mass in type 2 diabetes mellitus. We then simulated treatment effects of the IL-1 receptor antagonist anakinra. The result was a substantial and partly sustained symptomatic improvement in ß-cell function, and hence also in HbA1C, fasting plasma glucose, and proinsulin-insulin ratio, and a small increase in ß-cell mass. We propose that improved ß-cell function, rather than mass, is likely to explain the main IL-1ß-blocking effects seen in current clinical data, but that improved ß-cell mass might result in disease-modifying effects not clearly distinguishable until >1 year after treatment.

Systems pharmacology models can be used to understand complex pharmacokinetic-pharmacodynamic behavior: an example using 5-lipoxygenase inhibitors.

Zileuton, a 5-lipoxygenase (5LO) inhibitor, displays complex pharmaokinetic (PK)-pharmacodynamic (PD) behavior. Available clinical data indicate a lack of dose-bronchodilatory response during initial treatment, with a dose response developing after ~1-2 weeks. We developed a quantitative systems pharmacology (QSP) model to understand the mechanism behind this phenomenon. The model described the release, maturation, and trafficking of eosinophils into the airways, leukotriene synthesis by the 5LO enzyme, leukotriene signaling and bronchodilation, and the PK of zileuton. The model provided a plausible explanation for the two-phase bronchodilatory effect of zileuton-the short-term bronchodilation was due to leukotriene inhibition and the long-term bronchodilation was due to inflammatory cell infiltration blockade. The model also indicated that the theoretical maximum bronchodilation of both 5LO inhibition and leukotriene receptor blockade is likely similar. QSP modeling provided interesting insights into the effects of leukotriene modulation.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e74; doi:10.1038/psp.2013.49; advance online publication 11 September 2013.

Coupled macroscopic and microscopic scale modeling of fibrillar tissues and tissue equivalents.

Collagen mechanics are crucial to the function and dysfunction of many tissues, including blood vessels and articular cartilage, and bioartificial tissues. Previous attempts to develop computer simulations of collagenous tissue based on macroscopic property descriptions have often been limited in application by the simplicity of the model; simulations based on microscopic descriptions, in contrast, have numerical limitations imposed by the size of the mathematical problem. We present a method that combines the tractability of the macroscopic approach with the flexibility of the microstructural approach. The macroscopic domain is divided into finite elements (as in standard FEM). Each element contains a microscopic scale network. Instead of a stress constitutive equation; the macroscopic problem is distributed over the microscopic scale network and solved in each element to satisfy the weak formulation of Cauchy's stress continuity equation over the macroscopic domain. The combined method scales by order 1.1 as the overall number of degrees of freedom is increased, allowing it to handle larger problems than a direct microstructural approach. Model predictions agree qualitatively with tensile tests on isotropic and aligned reconstituted type I collagen gels.