May 24, 2018
InSysBio announces their participation at PAGE 2018 27th Meeting being held from 29 May to 1 June 2018 in Montreux, Switzerland. InSysBio welcomes visitors at the booth B1. InSysBio is also presenting four posters.
Wednesday, May 30 (10:10-11:40):
Thursday, May 31 (09:55-11:30):
Thursday, May 31 (15:10-16:40):
In addition, Etienne Pigeolet from Novartis will present a poster co-authored with InSysBio scientists Tatiana Karelina, Alexandra Urusova and Oleg Demin on Thursday, May 31 (15:10-16:40):
About InSysBio
InSysBio (formerly Institute for System Biology Moscow) 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 quantitative systems pharmacology (QSP) modeling. InSysBio’s innovative approach has already become a part of the drug development process implemented by our strategic partners: nowadays there are more than 100 completed projects in collaboration with leaders of pharmaceutical industry. The company has published multiple scientific studies in various therapeutic areas. InSysBio team is developing software and tools for QSP and continuously improves methods for biological modeling. For more information about InSysBio, its solutions and services, visit www.insysbio.com.
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18 Nov 2019 19:58
Course “Modeling for systems biology and biomedicine” at the Faculty of Bioengineering and Bioinformatics
This year InSysBio CEO Dr Oleg Demin with expert modelers Tatiana Karelina and Evgeny Metelkin and modelers Dmitry Shchelokov, Svetlana Rubina and Veronika Musatova are giving the course “Modeling for systems biology and biomedicine” at the Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University.
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25 Nov 2019 18:47
PK/RO simulator for anti-PD-1 mAbs
InSysBio, a pioneer in Quantitative Systems Pharmacology (QSP), modeling and simulation for drug development, announced the launch of application ‘PK/RO simulator for anti-PD-1 mAbs’. The application is based on the model allowing to predict pharmacokinetics and target binding in human for therapeutic antibodies against PD-1 receptor.
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