The method of averaging applied to pharmacokinetic/pharmacodynamic indirect response models
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The computational effort required to fit the pharmacodynamic (PD) part of a pharmacokinetic/pharmacodynamic (PK/PD) model can be considerable if the differential equations describing the model are solved numerically. This burden can be greatly reduced by applying the method of averaging (MAv) in the appropriate circumstances. The MAv gives an approximate solution, which is expected to be a good approximation when the PK profile is periodic (i.e. repeats its values in regular intervals) and the rate of change of the PD response is such that it is approximately constant over a single period of the PK profile. This paper explains the basis of the MAv by means of a simple mathematical derivation. The NONMEM® implementation of the MAv using the abbreviated FORTRAN function FUNCA is described and explained. The application of the MAv is illustrated by means of an example involving changes in glycated hemoglobin (HbA1c%) following administration of canagliflozin, a selective sodium glucose co-transporter 2 inhibitor. The PK/PD model applied to these data is fitted with NONMEM® using both the MAv and the standard method using a numerical differential equation solver (NDES). Both methods give virtually identical results but the NDES method takes almost 8 h to run both the estimation and covariance steps, whilst the MAv produces the same results in less than 30 s. An outline of the NONMEM® control stream and the FORTRAN code for the FUNCA function is provided in the appendices.
KeywordsPharmacokinetic/pharmacodynamic model Method of averaging Computational efficiency
- 6.Beal SL, Sheiner LB, .Boeckmann A, Bauer RJ (2009) NONMEM user’s guides (1989-2009), Icon Development Solutions, Ellicott CityGoogle Scholar
- 7.Hoeben E, Vermeulen A, deWinter W, Neyens M, Devineni D, Dunne (2015) A Population pharmacokinetic modeling of canagliflozin in healthy volunteers and patients with Type 2 diabetes mellitus. Submitted to Clinical Pharmacokinetics Google Scholar
- 8.Hindmarsh AC (1983) ODEPACK, a systematized collection of ODE solvers. In: Stepleman RS et al (eds) IMACS transactions on scientific computation, vol 1. North-Holland, Scientific Computing, pp 55–64Google Scholar
- 9.Butcher JC (1987) The numerical analysis of ordinary differential equations: Runge-Kutta and general linear methods. Wiley, New YorkGoogle Scholar