Introduction: Administration of high-dose busulphan is a critical component in many conditioning regimens for both adults and children before haemopoietic stem cell transplantation. Current intravenous formulations of busulphan contain N,N-dimethylacetamide (DMA), which is an organic solvent that acts as an excipient for drug administration. Despite available information regarding the safety of DMA use in myeloablative treatment, studies have shown that DMA exhibits various neuro- and hepatotoxic effects, notably sinusoidal obstruction syndrome . Furthermore, the pharmacokinetics and pharmacodynamics of DMA, as well as its metabolite N-methylacetamide (MMA) have been sparsely studied in relation to toxicity, and current literature may not confer accuracy given the limited number of patients and sample observations . As children are often given high doses of busulphan over a 4 – 5 day course, cumulative DMA exposure will also be observed. It is therefore clinically important to assess the pharmacokinetics and pharmacodynamics of DMA in children receiving intravenous busulphan.
Aim: To build a preliminary model for evaluation of DMA in paediatric patients receiving intravenous busulphan before undergoing haemopoietic stem cell transplantation.
Methods: 367 concentration data points were generated from 18 patients aged 0.3 – 18 years (median 3.5 years) receiving intravenous busulphan over the course of 4 – 5 days. Population pharmacokinetics were performed using nonlinear mixed effects modelling (NONMEM version 7.4) and (PsN version 4.9). RStudio and R packages Xpose and Lattice were used for data visualisation. One- and two-compartment models were tested alongside various statistical and covariate models as a means to minimise the objective function. Predictability was assessed through simulation-based visual predictive checks and model robustness was determined through nonparametric bootstrapping (n = 1000). Covariates tested included weight (including allometric exponent scaling), age, body surface area, and glomerular filtration rate as predictors of clearance (CL) and volume of distribution (V).
Results: A one-compartment model best described the data, with inter-individual variability descriptors on CL and V. Residual error was described using a combined additive and proportional model. Typical CL increased after the first day of infusion, and modelled accordingly to provide a better fit to the data. Median adjusted patient body weight was determined to be the best predictor of CL and V. Other covariates were omitted from the final model as they did not significantly improve the estimation. Mean day one CL and subsequent day CL was estimated to be 0.95 and 1.43 L/h, respectively. Inter-individual variation of CL and V was reduced from 72.1% and 67.8% to 26.1% and 14%, respectively. Goodness of fit plots did not display any model misspecification, with residuals distributed normally around zero. Observed DMA concentrations were within the median, 5th, and 95th percentiles of the model predicted concentrations, with comparatively similar values between the bootstrapped mean values and final parameter estimates. Results are comparable to the current literature . Metabolite concentration data has been collected and was observed to be accumulative in all patients across all days. These findings have yet to be implemented into the pharmacokinetic model.
Conclusions: These results provide a satisfactory preliminary model for investigation of DMA pharmacokinetics. Currently, the number of patients and observations from this study is limited, but this project is ongoing and several patient samples are readily available for analysis. Correlating these findings with patient toxicity, as well as incorporating metabolite data into the model are now being planned.
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