Belén P. Solans (1,2), Robert Chiesa (3), Iñaki F. Trocóniz (1,2), Joseph F Standing (4,5,6)
(1) Pharmacometrics and Systems Pharmacology, Departament of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Navarra, Pamplona, Spain; (2) IdiSNA; Navarra Institute for Health Research, Pamplona, Spain; (3) Bone Marrow Transplantation Team, Great Ormond Street Hospital for Children, London, UK; (4) Infection, Immunity, Inflammation Programme, UCL Great Ormond Street Institute of Child Health, London, UK; (5) Department of Pharmacy, Great Ormond Street Hospital for Children, London, UK; (6) Paediatric Infectious Diseases Group, St George’s, University of London, UK
Introduction: Hematopoietic Stem Cell Transplantation (HSCT) is a procedure where healthy donor cells are infused to a recipient with the intention of replacing the haematopoietic system in total or in part [1], being one of the most common treatments of a wide range of malignant and non-malignant disorders in children [2]. Prior to HSCT, the ablation of the host immune system is achieved by administering conditioning drugs and/or total body irradiation. There is currently a debate surrounding the relative merits of busulfan (Bu) and treosulfan (Treo), which are used to deplete myeloid cells prior to transplantation. Identifying patient characteristics associated with the dynamics of myeloid reconstitution (inferred from neutrophils) and predicting individual trajectories may prove to be useful in understanding post-HSCT recovery. To do that, pharmacokinetic/pharmacodynamic (PKPD) models were developed, in which both the rate and extent of reconstitution can be obtained by deriving the dynamics of cell count over time.
Objectives: The objectives of the study were (i) to build a joint mechanistic PKPD model of neutrophil count over time and establish a relationship with Bu and Treo plasma concentrations, (ii) compare the myeloablative effects of Bu and Treo in the shape of the PD effect curve and (iii) identify patient characteristics associated with the inter-individual variability in myeloid cell dynamics.
Methods: In this retrospective single-center study, blood concentrations of Bu were quantified in samples acquired for routine drug therapeutic monitoring (TDM). The PK characteristics of Treo were obtained from a model developed as part of a previous study [manuscript under preparation], and PK predicted for those patients without measured concentrations. Daily neutrophil count data from the start of drug administration until 3 months post-transplant was also available from electronic health records. In total 11,555 observations from 152 paediatric patients (median post menstrual age in weeks (PMAW) 204.14, ranging from 47.71 to 948.57 weeks), 85 receiving Bu (median PMAW 216.29, range 69.57 – 948.57 PMAW) and 67 receiving Treo (median PMAW 122.14, range 47.71 – 879.86 PMAW) were included. Integrating all the available data, a PK/PD model was built NONMEM 7.3. The analysis was performed simultaneously for both drugs.
Results: a joint mechanistic PKPD model of neutrophil count over time for Bu and Treo was successfully developed. The blood concentration vs time profiles of Bu and Treo were described by a two-compartment model for both drugs. The drug effects were modelled using an EMAX model for both of the drugs, which resulted significantly better (p<0.01) than a linear model. System parameters (steady-state neutrophil count after transplant (CIRC0), mean transit time (MTT) and feedback parameter (GAMMA)) were consistent across drugs and were therefore the same for Bu and Treo, being the estimates 1.06, 5.74 days and 0.114. Inter-Individual Variability (IIV) could be estimated for all of parameters, being 54.2, 24.5 and 48.2% for CIRC0, MTT and GAMMA, respectively. Since patients may not enter the study at steady-state and/or the post transplant steady-state level may have a different homeostatic set point than the baseline, a different steady state of neutrophils was estimated after transplant than the baseline. The main differences between patients receiving different drugs was the baseline neutrophil value (5.08 for Bu patients vs 1.62 for Treo patients). The myeloablative effects of Treo were steeper and produced earlier in time than those of Bu (EMAX = 2.47 vs 0.57 for Treo and Bu, respectively). A covariate analysis did not find other significant predictors of response.
Conclusions: Drug exposure to the main myeloablative conditioning drugs given to paediatric patients receiving HSCT was successfully described by a two compartment model for each of the drugs, and was linked to neutrophil count dynamics over time and recovery through mixed-effects modelling, and thus, a joint mechanistic PKPD model was built. Further work will now seek to link early neutrophil dynamics to long-term myeloid recovery measured through chimerism analysis.
References:
[1] Sureda A, Bader P, Cesaro S, Dreger P, Duarte RF, Dufour C, et al. Indications for allo- and auto-SCT for haematological diseases, solid tumours and immune disorders: current practice in Europe, 2015. Bone Marrow Transplant. 2015; 50 (8): 1037–56.
[2] Bartelink IH, Belitser SV, Knibbe CA, Danhof M, de Pagter AJ, Egberts TC, et al.Immune reconstitution kinetics as an early predictor for mortality using various hematopoietic stem cell sources in children. Biol. Blood Marrow Transplant. 2013; 19 (2): 305–13.
Reference: PAGE 27 (2018) Abstr 8712 [www.page-meeting.org/?abstract=8712]
Poster: Drug/Disease Modelling - Paediatrics