Universiteit Leiden

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Research project

Control theory methods for quantitative systems pharmacology models

Following their application to system biological models, control theory techniques have further potential to aid in the understanding and application of quantitative systems pharmacology models.

Frequency-domain response analysis, for example, a method commonly used in electrical and control engineering, shows potential to aid the model-driven optimisation of treatment schedules.



Control theory has a long history of describing and influencing the behaviour of dynamical systems. Following the emergence of systems biology wherein complex biological processes are viewed as systems and investigated with the help of computational modelling, systems pharmacology pursues a similar goal. But, unlike in systems biology, control and systems theory methods are still rarely used in systems pharmacology. Thus, this project aims to close this gap and translate control and systems theory methods for the use in quantitative systems pharmacology (QSP).

As a first candidate method, we identified the frequency-domain response analysis (FdRA) that is commonly used in electrical and control engineering to investigate the input/output behaviour of dynamical systems. FdRA is not only able to identify the time scales on which a QSP model operates on but also which oscillatory inputs can maximise or minimise the output. Because of its ability to analyse oscillatory inputs, FdRA seems to be perfectly suited to guide drug treatment schedules. Even though QSP models are used to understand the interplay between the pharmacological system and drug action, their ability to guide drug treatment schedules is still under-utilised. Here, FdRA aids the identification of dosing frequencies for which the response of the QSP model is either amplified or attenuated. This facilitates not only the characterisation of QSP models but also supports the understanding of the pharmacological system and the optimisation of treatment schedules or the identification of signature profiles.

Another method that shows potential for QSP is zero dynamics where the aim is to find a suitable input into a dynamic system in order to zero the output. This method might be especially applicable for oncological models of tumour growth.

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