BioUML: plugin for population-based modeling

Ilya Kiselev, Fedor Kolpakov


DOI: 10.12704/vb/e15

Abstract


Motivation and Aim: Non-linear mixed effects (NLME) model is an efficient tool for analyzing of population data and estimating of model parameters. It is widely used in pharmacological modeling, but may be applied to a variety of fields. NLME model contains core structural model which is the mathematical model of studying process (e.g. drug dynamics in organism) and suggests distribution of model parameters across population. nlme is a library written in R language implementing log-likelihood approach for NLME models creation and analysis. Core structural model should be supplied as R function which complicates usage of sophisticated mathematical models. Library nlmeODE allows usage of ODEs inside nlme, but it has certain restrictions on possible models and textual format complicates using of complex ODE systems.

Results: We have implemented plugin for BioUML platform for population-based modeling. Plugin includes graphical notation facilitating work with detailed and large-scaled models, parameter estimation is performed by R function, supplied (using rJava) with Java simulator from BioUML. It grants possibility to use any model created in BioUML as a structural model. Executing R script is automatically generated on the basis of the diagram.

Availability: Plugin is freely available as a part of BioUML software at www.biouml.org.


Keywords


Non-linear mixed effcets model, parameter estimation, R, BioUML.

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References


Beal, S., Sheiner, L.B., Boeckmann, A., & Bauer, R.J., NONMEM User's Guides. (1989-2009), Icon Development Solutions, Ellicott City, MD, USA, 2009.

Lunn, D.; Spiegelhalter, D.; Thomas, A.; Best, N. (2009). "The BUGS project: Evolution, critique and future directions". Statistics in Medicine 28 (25): 3049–3067.

Moodie, S.L., et al. PharmML: The Pharmocometrics Markup Language. Language Specification. 2013. Available at www.pharmml.org.

Pinheiro J.C., Bates D.M. Mixed-Effect Models in S and S-PLUS, Springer-Verlag, New York, NY, 2000. DOI: 10.1007/b98882.

Tornoe C.W., et al. Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations. Computer Methods and Programs in Biomedicien, 2004. 76(1) 31-40. DOI: 10.1016/j.cmpb.2004.01.001.

Hucka, M. et al. The Systems Biology Markup Language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics, 2003, vol. 19, no. 4, pp. 524–531. DOI: 10.1093/bioinformatics/btg015.

Nicolas Le Novère et al. The Systems Biology Graphical Notation. Nature Biotechnology, 2009, 27, 735 – 741. DOI: 10.1038/nbt.1558.


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