A quantitative systems pharmacology (QSP) model for Pneumocystis treatment in mice

Abstract

BackgroundThe yeast-like fungi Pneumocystis, resides in lung alveoli and can cause a lethal infection known as Pneumocystis pneumonia (PCP) in hosts with impaired immune systems. Current therapies for PCP, such as trimethoprim-sulfamethoxazole (TMP-SMX), suffer from significant treatment failures and a multitude of serious side effects. Novel therapeutic approaches (i.e. newly developed drugs or novel combinations of available drugs) are needed to treat this potentially lethal opportunistic infection. Quantitative Systems Pharmacological (QSP) models promise to aid in the development of novel therapies by integrating available pharmacokinetic (PK) and pharmacodynamic (PD) knowledge to predict the effects of new treatment regimens.ResultsIn this work, we constructed and independently validated PK modules of a number of drugs with available pharmacokinetic data. Characterized by simple structures and well constrained parameters, these PK modules could serve as a convenient tool to summarize and predict pharmacokinetic profiles. With the currently accepted hypotheses on the life stages of Pneumocystis, we also constructed a PD module to describe the proliferation, transformation, and death of Pneumocystis. By integrating the PK module and the PD module, the QSP model was constrained with observed levels of asci and trophic forms following treatments with multiple drugs. Furthermore, the temporal dynamics of the QSP model were validated with corresponding data.ConclusionsWe developed and validated a QSP model that integrates available data and promises to facilitate the design of future therapies against PCP.

Sloppiness: fundamental study, new formalism and its application in model assessment

“…In the existing literature, a method of quantifying this insensitivity of predictions to changes in parameters is captured by (2).…”

“…Whole-cell modelling is an example of complex dynamical systems [1]. Quantitative systems pharmacology (QSP) is an another example of complex dynamical systems modeling [2, 3]. In a modelling exercise, often, there are many free parameters to be estimated from data.…”

The Current Landscape of Novel Formulations and the Role of Mathematical Modeling in Their Development

“…The QSP model was constructed to identify novel therapies with optimal PK/PD characteristics. 137 QSP models can potentially allow a detailed understanding of the biological interactions; however, they demand extensive input data to provide predictions, and often these models can lead to overfitting when the quality of the input data is low. 138 A strategic integration of QSP modeling in the development of novel formulations for drug delivery can provide a computational framework to simulate the potential downstream effect of nanomaterials on drug distribution and consequently on efficacy and toxicity.…”

“…Although there are alternative drugs such as atovaquone, clindamycin‐primaquine, echinocandins, and pentamidine isethionate, they result in PCP relapse. The QSP model was constructed to identify novel therapies with optimal PK/PD characteristics 137 . QSP models can potentially allow a detailed understanding of the biological interactions; however, they demand extensive input data to provide predictions, and often these models can lead to overfitting when the quality of the input data is low 138 .…”

Correction to: A quantitative systems pharmacology (QSP) model for Pneumocystis treatment in mice

“…It was highlighted that the original article [1] contained errors in the figures and their legends and by extension the in-text figure citations (Figs. 1, 2, 3, 4, 5 and 6).…”