July 11, 2022
The new article "Application of different approaches to generate virtual patient populations for the quantitative systems pharmacology model of erythropoiesis" by Galina Kolesova, Alexander Stepanov, Galina Lebedeva and Oleg Demin has been published in Journal of Pharmacokinetics and Pharmacodynamics.
Galina Kolesova comments on the article, "The traditional approach of QSP modeling includes fitting a model output to a series of mean data values. As a result, the parameters of the model represent fixed numbers enabling the description of mean data, thus we generated the so-called “reference patient”. However, the results of clinical trials include a description of variability in patients’ responses to a drug, which is typically expressed in terms of conventional statistical parameters such as standard deviations (SDs) from mean values. To allow a QSP model to reproduce the variability observed in response to a drug administration, a virtual patient (VP) population is usually generated and applied. In our study, we propose and compare four different approaches to generate virtual patient populations based on experimentally measured mean data and statistics, namely, (1) Monte Carlo Markov chain (MCMC), (2) model fitting to Monte Carlo samples, (3) population of clones, and (4) stochastically bounded selection. We applied these approaches to generate virtual patient populations in the QSP model of erythropoiesis. Our main task was to create a sample of virtual patients of the same size as that in clinical trials".
About InSysBio
InSysBio is a Quantitative Systems Pharmacology (QSP) company located in Edinburgh, UK (INSYSBIO UK LIMITED), Moscow, Russia (INSYSBIO LLC) and Cyprus (INSYSBIO CY Ltd). InSysBio was founded in 2004 and has an extensive track record of helping pharmaceutical companies to make right decisions on the critical stages of drug research and development by application of QSP modeling. InSysBio’s innovative QSP approach has already become a part of the drug development process implemented by our strategic partners: there are more than 100 completed projects in collaboration with leaders of pharmaceutical industry. For more information about InSysBio, its solutions and services, visit www.insysbio.com.
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14 Jan 2021 14:28
InSysBio to publish the new article on identifiability analysis in PLOS Computational Biology
[Moscow – 11.01.2021] InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, has published its recent scientific research on identifiability in PLOS Computational Biology.
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26 Jan 2021 13:14
InSysBio to announce the upgrade of its SbmlViewer application to version 0.2.7
[Moscow – 26.01.2021] InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, launces the new version of its SbmlViewer open project. Generally, SbmlViewer represents a tool for fast and easy reading of biological models written in SBML format.
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