The AAPS Journal

, 20:2 | Cite as

Selection and Qualification of Simplified QSP Models When Using Model Order Reduction Techniques

Research Article

Abstract

Quantitative systems pharmacology (QSP) models are increasingly used in drug development to provide a deep understanding of the mechanism of action of drugs and to identify appropriate disease targets. Such models are, however, not suitable for estimation purposes due to their high dimensionality. Based on any desired and specific input-output relationship, the system may be reduced to a model with fewer states and parameters. However, any simplification process will be a trade-off between model performance and complexity. In this study, we develop a weighted composite criterion which brings together the opposing indices of performance and dimensionality. The weighting factor can be determined by qualification of the simplified model based on a visual predictive check (VPC) using the precision of each parameter. The weighted criterion and model qualification techniques were illustrated with three examples: a simple compartmental pharmacokinetic model, a physiologically based pharmacokinetic (PBPK) example, and a semimechanistic model for bone mineral density. When considering the PBPK example, this automated search identified the same reduced model which had been detected in a previous report, as well as a simpler model which had not been previously identified. The simpler bone mineral density model provided an adequate description of the response even after 1 year from the initiation of treatment. The proposed criterion together with a VPC provides a natural way for model order reduction that can be fully automated and applied to multiscale models.

KEY WORDS

composite criterion proper lumping scale reduction systems models visual predictive check 

Notes

Compliance with Ethical Standards

Conflict of Interest

Chihiro Hasegawa is an employee of Ono Pharmaceutical Co., Ltd. and a visiting researcher at the University of Otago.

Supplementary material

12248_2017_170_MOESM1_ESM.doc (152 kb)
ESM 1 (DOC 151 kb)

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Copyright information

© American Association of Pharmaceutical Scientists 2017

Authors and Affiliations

  1. 1.School of PharmacyUniversity of OtagoDunedinNew Zealand
  2. 2.Translational Medicine CenterOno Pharmaceutical Co., Ltd.OsakaJapan

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