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The new open source project to be developed and updated Online InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, announces the launch of its fundamentally new project in response to the ongoing global threat, the open source QSP model of COVID-19. In accordance with its mission, which is to assist pharmaceutical industry to speed up the delivery of the cure to patients, InSysBio team could not stay aside. Thus, the aim of the new project is to develop QSP model of COVID-19 describing virus and host cell life cycles, innate and adoptive immune response and possible therapeutic treatments.

IRT version 3.1.0 acquires some principal upgrades (Moscow – 15.04.2020) InSysBio is one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling has published the new version of IRT database, one of its core products.

Cytocon DB 1.1 facilitates access of QSP modelers to baseline in vivo data in public domain (Moscow - 31.03.2020) InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) platform development and provision, has released its new Cytocon DB 1.1. The name of the database derives from Cell and cYTOkine CONcentrations.

26-28 February 2020 InSysBio QSP-company held its 13th Annual Internal Scientific Meeting. InSysBio team presented the results of 2019 year professional progress. Every member demonstrated their personal achievements and shared the plans for the future development. Oleg Demin, InSysBio CEO and founder, summarized all the company’s advancement of the year 2019.

IRT Version 3.0.0 acquires a wide variety of updates and new options (Moscow – 21.02.2020) InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) platform development and provision, moves forward to the future.

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.