Pascal Schulthess (1), James WT Yates (2), Piet Hein van der Graaf (1,3)
(1) Systems Biomedicine & Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands, (2) DMPK, Oncology, Innovative Medicines and Early Development, AstraZeneca, Chesterford Research Park, United Kingdom, (3) Certara QSP, Canterbury Innovation House, Canterbury, United Kingdom
Objectives: It was recently demonstrated that key biological control systems (such as the MAPK pathway) are highly sensitive to the frequency of external stimuli in a non-intuitive manner which cannot be predicted by conventional pharmacometrics approaches [1]. This suggests that quantitative systems pharmacology (QSP) can provide novel insights into optimal dosing regimens which could add a new dimension to the design of novel treatments. However, methods for such an approach are currently lacking. Recently, we illustrated the utility of frequency-domain response analysis (FdRA), a method widely used in electrical and control engineering, using several generic pharmacokinetic-pharmacodynamic case studies [2]. We now demonstrate the use of FdRA to optimise treatment regimen for cell cycle specific chemotherapy.
Methods: FdRA informs on the response of a QSP model to a wide range of perturbations as used in repetitive treatment regimen and enables the identification of treatment frequencies that amplify or attenuate the treatment response. Here, FdRA is applied to a cell cycle specific two compartmental model of tumour growth dynamics [3]. The proliferating cells in G1, S, G2, or M phase of the cell cycle inhabit the first compartment while quiescent cells in G0 phase reside in the second compartment. While the proliferating cells are degraded, growing and transfer to G0 phase, we assume that the quiescent cells are not degraded but only transfer back to become proliferative. The pharmacokinetic model of Etoposide (VP-16), a cell cycle specific anti-cancer drug widely used against childhood leukaemia, testicular tumours, Hodgkin’s disease, large cell lymphomas and small cell lung cancer consists of two compartments. Etoposide in plasma stimulates the degradation of proliferating tumour cells. By assuming repetitive bolus doses at frequencies between two per day and one per ten days and while keeping the total dose administered over the course of treatment constant, we numerically measure the amplitude of the plasma concentration of Etoposide (as input) as well as the amplitudes of the total number of tumour cells at distinct times during treatment (as output). The output to input amplitude ratio is then plotted over the dosing frequency in a diagram similar to the Bode diagrams used in engineering [2].
Results: Comparing the amplitude ratios at different time points during treatment, we observed that the frequency response for all time points (30, 45, 60 days after treatment start) assumed a similar shape with a low amplitude ratio for less frequent and a high amplitude ratio for high frequent dosing. Lastly, the amplitude ratio of the 30 days’ time point was larger than for all other time points for less frequent dosing while it was the smallest as compared to all other time points for high frequent dosing. An amplitude ratio intersection for the points at 59 doses per 100 days is observed. Thus, in order to decrease the fluctuations in tumour mass as well as total tumour mass high frequent low dose treatment is advised.
Conclusions: Drug dosing regimen can significantly impact drug effect and, thus, the success of treatments. Here, we show that FdRA, as a novel analytical method in systems pharmacology, facilitates not only the characterisation of QSP model dynamics with respect to the presence and magnitude of time-delays, model stability and performance but also aids the understanding of the pharmacological system and the optimisation of drug treatment regimen.
References:
[1] Mitchell, A., Wei, P. & Lim, W. A. Oscillatory stress stimulation uncovers an Achilles’ heel of the yeast MAPK signaling network. Science 350, 1379–1383 (2015).
[2] Schulthess, P., Post, T. M., Yates, J. & van der Graaf, P. H. Frequency-Domain Response Analysis for Quantitative Systems Pharmacology Models. CPT Pharmacometrics Syst Pharmacol 6, 418 (2017).
[3] Zhu, J. et al. Optimization of drug regimen in chemotherapy based on semi-mechanistic model for myelosuppression. J Biomed Inform 57, 20–27 (2015).
Reference: PAGE 27 (2018) Abstr 8441 [www.page-meeting.org/?abstract=8441]
Poster: Drug/Disease Modelling - Oncology