September 16, 2020
InSysBio announces its participation in Eleventh American Conference on Pharmacometrics (ACoP11) which is to be held in virtual format this year due to COVID-19 spread 9-13 November, 2020. The theme of ACoP11 is “Scaling New Heights.” InSysBio team is going to present 9 posters in frames of the Conference, namely:
Tuesday, November 10:
Wednesday, November 11:
Affiliation: 1 Lomonosov Moscow State University, Moscow, Russia; 2InSysBio, Moscow, Russia
Thursday, November 12:
We are looking forward to seeing again in person next year!
About InSysBio
InSysBio is a Quantitative Systems Pharmacology (QSP) company located in Moscow, Russia (INSYSBIO LLC) and Edinburgh, UK (INSYSBIO UK LIMITED). 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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19 May 2021 16:52
InSysBio to upgrade its SbmlViewer application
[Moscow – 19.05.2021] InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, launches the new version (0.3.0) of its SbmlViewer open project. Generally, SbmlViewer is a tool for fast and easy reading and transformation of biological models written in SBML format.
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25 May 2021 17:38
InSysBio to take part in SMB 2021
InSysBio announces its participation in Society of Mathematical Biology Annual Meeting (SMB 2021) which is to be held virtually this year June 13-17, 2021. InSysBio team is going to present 4 posters and Oleg Demin Jr is going to give a presentation "Implementation of variability or uncertainty in parameter values to validate QSP models." and Ivan Borisov is going to give a talk "Constrained Optimization Approach to Predictability Analysis in Bio-Mathematical Modeling."
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