M. Veronese(1), S. Zamuner(2), R.N. Gunn(3,4) and A. Bertoldo(1)
(1) Department of Information Engineering, University of Padova, Italy; (2) Clinical Pharmacology Modelling and Simulation , GlaxoSmithKline, Stockley Park, UK; (3) Imanova Limited, London, UK; (4) Imperial College, London, UK;
Objectives:To increase the efficiency of pharmacokinetic/pharmacodynamic experiments, optimal experimental design has been used to successfully optimize dose allocation and sampling schedule [1]. In PET receptor occupancy (PET-RO) [2] studies it has been demonstrated that adaptive optimal design (AOD) algorithms improve the assessment of drug kinetic time-courses [3]. However the value of applying adaptive or non-adaptive optimal design methodologies to PET-RO studies depends on several factors including drug affinity to the target as well as feasibility constrains such as sample size, number of scan per subjects and logistical constrains. In this work we presented a simulation study to explore the potentialities of optimal design algorithms when applied to PET-RO, by evaluating the sensitivity of the results to experimental scanning times as well as misspecified drug kinetic assumptions.
Methods: Simulated data were generating according the following PK-BP model (kon=0.088 hrs-1 and koff=0.221 hrs-1, BP0=3, inter-subject variability=30%, proportional error model):
dBP/dt=koff•BP0 – (Cp•kon+koff)•BP
Simulated experimental designs were chosen according to adaptive, non-adaptive optimal designs and non optimized designs by using different levels of parameter misspecifications respect to the true simulated values (range: [-300%;+300%]). For each design, 100 populations each with 12 subjects were considered. Only two time points were assumed per subject, chosen in a time window of 0-36 hours (minimum distance 4 hours). Design optimization was identified using the D-optimality criterion [4]. Three simulated compounds with different brain affinities (low, medium and high) were tested, with Kd(=koff/kon) equal to 15, 2.5 and 0.25 respectively . The dose level was held constant for all the simulations.
Results: For all the drugs and experiments considered, the best performances were achieved using optimal approaches (adaptive and non-adaptive) applied without parameter misspecification. The worst performances were reported by the non-adaptive method when initial parameter assumptions significantly underestimated the true kinetic of the tracer. However, when AOD was applied to the misspecified cases, precision and accuracy of parameters were recovered. Kd was the most robust parameter (bias range [1%;30%]), while kon and koff were much more sensitive to experimental choices (maximum bias 64% and 50% respectively). High-affinity compound were more robust to experimental setting changes than medium or low affinity drugs.
Conclusions: Our results confirmed that an optimal choice of PET scanning times can improve the quality of parameter estimates in PET-RO. In particular if the initial misspecification is limited (<100%) D-optimality provided reliable results. In case of greater parameters misspecification, AOD represents a valid tool to guide experimental design settings.
References:
[1] Dodds MG, Hooker AC, Vicini P. Robust population pharmacokinetic experiment design. J Pharmacokinet Pharmacodyn, 2005. 32(1):33-64.
[2] Abanades S, van der Aart J, Barletta JA, Marzano C, Searle GE, Salinas CA, Ahmad JJ, Reiley RR, Pampols-Maso S, Zamuner S, Cunningham VJ, Rabiner EA, Laruelle MA, Gunn RN. Prediction of repeat-dose occupancy from single-dose data: characterisation of the relationship between plasma pharmacokinetics and brain target occupancy. J Cereb Blood Flow Metab, 2011. 31(3):944-52.
[3] Zamuner S, Di Iorio VL, Nyberg J, Gunn RN, Cunningham VJ, Gomeni R, Hooker AC. Adaptive-optimal design in PET occupancy studies. Clin Pharmacol Ther, 2010. 87(5):563-71.
[4] Foracchia M, Hooker A, Vicini P, Ruggeri A. POPED, a software for optimal experiment design in population kinetics. Comput Methods Programs Biomed, 2004. 74(1):29-46.
Reference: PAGE 21 (2012) Abstr 2520 [www.page-meeting.org/?abstract=2520]
Poster: Study Design