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A New Mathematical Model of the Eosinophil Lifecycle Shows Irrelevance of the Asthma Biomarker Choice


Moscow, Russia - November 29th, 2016. Institute for Systems Biology Moscow (, one of the pioneers in bio-modeling and simulation announced the study made in collaboration with scientists of two pharmaceutical leaders: MedImmune and AstraZeneca. The research published in CPT Pharmacometrics & Systems Pharmacology shows how systems pharmacology modeling can help in validation of Asthma biomarkers for patients taking anti-interleukin medication.

Eosinophils (EOS) as a type of leukocytes are responsible for tissue inflammation under pathological conditions. For asthma EOS airway infiltration is a key feature. Historically high blood eosinophilic count is known to be a typical biomarker of asthma progression, though it may not correlate with amount of eosinophils in airways. Several new anti-asthmatic compounds either just appeared on the market or are at the late stage of development. These include emerging T-helper type 2 cytokine-based biotherapeutics such as tralokinumab, lebrikizumab (anti-interleukin-13) and mepolizumab (anti- interleukin-5). Clinical trials have shown that all these antibodies reduce asthma effects in airways except the fact of different EOS response. Using both tralokinumab and lebrikizumab leads to increase in blood eosinophils concentration in patients’ samples.

This paper presented an application of the complex model developed by leading ISBM scientists. This work took them six month.The research group collected published data about processes and cytokines affected on EOS distribution between blood and lungs and set up about 20 differential equations to reproduce key mechanisms underlying EOS cell dynamics. The model precisely described interactions between key participants of the cell dynamics processes both in normal and pathologic cases: EOS maturation, migration, activation and death.

The model enabled researchers to investigate effects of aforementioned treatments on eosinophils. First of all it showed that using tralokinumab (anti-asthma therapy by MedImmune) caused growth in eosinophils blood level by blocking their migration to the lungs, what meant a prevention of airways tissue inflammation. This conclusion is in line with clinical trial results, which in fact were not used during model development.

“In fact, increase of eosinophil count in blood is a direct physiological consequence of positive tralokinumab effect in lungs. Therefore, we can speak about irrelevance of the blood eosinophil response as a valid biomarker choice for asthmatic patients treated by anti- interleukin-13 antibodies,” claimed Tatiana Karelina, PhD, the leader of the research group.

The second feature of this model was developing a population of virtual patients. Variation of key model parameters literally reconstructed thousands of people with their own specific sensibility for anti-asthma medication. The virtual group enables scientists to validate another asthma biomarker – level of plasma periostin, a molecule which is associated with eosinophils migration from blood to airways. Simulation resulted in patient separation into two groups according to their level of plasma periostin. Modeling predicts that tralokinumab therapy could be more efficient for patients with higher content of periostin. Thus plasma periostin was proved to be a better marker of this asthma therapy efficacy.

“This paper is about fear. Systems pharmacology model enables us to explain that one shouldn’t be afraid of high blood eosinophilic count while taking anti-Interleukin 13 medication. Moreover we managed to provide mathematical argumentation for empirical asthma biomarkers in different therapies,” said Oleg Demin, PhD, CEO of the Institute for Systems Biology Moscow

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About Institute for Systems Biology Moscow (ISBM):

Institute for Systems Biology Moscow, Ltd. ( is a leading R&D company providing services for mathematical modeling in drug research and development. ISBM is one of the pioneers in quantitative system pharmacology (QSP) modeling and simulation services and has been working on the market for more than 10 years. The company’s aim is to assist right decisions on the critical stages of drug research and development. ISBM team continuously improves methods and tools for biological modeling. Moreover, company works with students and postgraduates forming professional community of QSP-modelers. Company has published a lot of scientific studies, and has presented at major international conferences of the field. The ISBM innovative approach has become an integral part of the drug development process implemented by our strategic partners: nowadays there are more than 100 completed projects in collaboration with leaders of pharma industry.

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