Victor Mangas-Sanjuan(1)(2), Núria Buil-Bruna(1), Elena Soto (3), MarÃa J. Garrido (1), Iñaki F. Troconiz (1)
(1) Department of Pharmacy and Pharmaceutical Technology; School of Pharmacy; University of Navarra; Pamplona; Spain (2) Pharmacy and Pharmaceutical Technology Area; Miguel Hernandez University; Alicante; Spain (3) Pfizer; Canterbury; UK.
Objectives: To develop a semi-mechanistic PKPD model of neutropenia able to predict the behavior of neutrophils after different dosing schedules.
Methods: PK and PD data were obtained from five clinical studies developed at several doses and schedules involving 111 patients. Experimental data were fitted using non-linear mixed-effects modelling implemented in NONMEM 7.2[1]. Schedule 1 consisted in IV-bolus administration every 7, 14 or 21 days. Schedule 2 was represented of an oral or IV administration once daily during five days. VPC and NPC by schedule and dose level were performed as internal validation
Results: Plasma drug concentrations were fitted to a three compartment model and plasma neutrophils were modelled using five compartments, one representing proliferating cells, three representing maturation and one representing the circulating neutrophils[2]. Drug effect was described using an Emax function. Inter-individual variability of PK and PD parameters was modelled exponentially and residual variability followed a combined error model. Neutrophils from schedule 2 were simulated employing PD parameters from schedule 1. Underprediction of neutropenia levels of schedule 2 was observed in VPC performed from schedule 1 final parameter estimates. Therefore, we incorporated a cell cycle mechanism that might explain the drug acts on cells that were in a particular stage of the cell cycle.
Conclusions: Final parameters derived from schedule 1 using the model proposed by Friberg [2] were not able to capture the neutropenia observed after repeated administrations with lower doses after IV or oral administration. A modification in the model, incorporating cell cycle mechanism allowed to better predict the observations after repeated administrations.
References:
[1] Beal SL, Sheiner LB, Boeckmann AJ & Bauer RJ (Eds.) NONMEM Users Guides. 1989-2011. Icon Development Solutions, Ellicott City, Maryland, USA.
[2] Friberg LE, Henningsson A, Maas H, Nguyen L, Karlsson MO. Model of chemotherapy-induced myelosuppresson with parameter consistency across drugs. J Clin Oncol (2002) 20: 4713-21.
Reference: PAGE 23 (2014) Abstr 3185 [www.page-meeting.org/?abstract=3185]
Poster: Drug/Disease modeling - Oncology