InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, releases a new version of LikelihoodProfiler.jl. LikelihoodProfiler represents a unified Julia package that can be used for practical identifiability analysis for complex computationally demanding QSP models.
Initially, LikelihoodProfiler.jl included a method (CICO) for estimating confidence intervals (CI) and assessing the practical identifiability of model parameters using the profile likelihood approach. Now LikelihoodProfiler package provides various state-of-the-art methods for profile likelihood analysis, including optimization-based and integration-based profiles, CI endpoints search, and more. These methods are now unified under a new interface, making it easier for users to switch between them. The results of LikelihoodProfiler.jl analysis can be used to further reduce the complexity and eliminate model’s uncertainty by implementing identifiable parametrizations and model reduction techniques.
Ivan Borisov, Senior Software Developer, comments on the new version of LikelihoodProfiler.jl, “This release marks the first version of the revamped package. We plan to introduce additional methods, improve interfaces, enhance documentation, and more to make the package more valuable to the community.”
LikelihoodProfiler package is open-source and freely available on GitHub: https://github.com/insysbio/LikelihoodProfiler.jl
About InSysBio
InSysBio is a group of Quantitative Systems Pharmacology (QSP) companies located in Limassol, Cyprus (INSYSBIO CY Ltd) 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 cutting-edge 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 and innovative biotech companies. For more information about InSysBio, its solutions and services, visit www.insysbio.com
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06 Nov 2018 17:27
Investigation of amyloid pathology mechanisms and prediction of clinical trial results using QSP model
InSysBio presents the video of Tatiana Karelina’s talk in framework of session “From translational PKPD models to quantitative system pharmacology in neurodegeneration drug development” at the 9th American Conference on Pharmacometrics (ACoP9):
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26 Nov 2018 14:03
InSysBio updates Immune Response Template online
InSysBio, a pioneer in Quantitative Systems Pharmacology (QSP) modeling and simulation for drug development, today announced a release of updated version of Immune Response Template (IRT) online. The main update in new 2.1.0 version is myeloid-derived suppressor cells (MDSCs). Published human in vitro and in vivo data were analyzed to reconstruct monocytic MDSCs (Mo-MDSCs) and granulocytic MDSCs (Gr-MDSCs) life cycles, derive equations and identify parameters.
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