Prediction of remifentanil metabolic ratio using sparse data collected during non-steady-state infusion with rapidly changing rate
Monica Simeoni, Jonathan Bullman, Chao Chen
Clinical Pharmacology Modelling and Simulation, GlaxoSmithKline, UK
Objectives: Remifentanil (R), an analgesic, is metabolised by non-organ dependent blood and tissue non specific esterases, and has a short plasma half-life of less than 10 minutes [1] [2]. It is metabolised to remifentanil acid (RA) which is eliminated via the kidney with a half-life of about 17 h [3]. Our objective was to estimate metabolic ratio (MR) from sparse data in a 10-day study with rapidly changing IV infusion rates which greatly varied among subjects.
Methods: The work was conducted in three steps:
1) The absence of the steady state condition implied that MR could not be calculated directly as RA/R but a modelling solution was necessary. Using historical data from a 3-day study, a previously presented model [3] was modified and extended into a mixed effect model to fit R and RA data simultaneously. Three and two compartment models were used for subjects with normal/mildly impaired renal function and subjects with moderate/severe renal impairment respectively, with creatinine clearance (CrCL) as a covariate. The new model was tested on the original dataset.
2) Given the between subject variability of the infusion profile, a novel VPC technique was introduced for the model validation: 300 simulations were performed for each subject, with its own infusion profile and CrCL, but typical parameter values.
3) Individual MR in the combined dataset was then estimated using the priors from the original dataset.
Results:
1) A model was successfully identified with good parameter precision and fitting of the data, assuming an exponential relationship between MR and CrCL.
2) The VPC showed that the model described the data well. Only 2 of the 40 estimated MR values fell outside the 5th to 95th percentile interval.
3) Results from the fitting of the spare and fully sampled datasets can be summarized as below. In subjects with normal or mildly impaired renal function the geometric mean of MR was 12, the 5th percentile was 1.9 and the 95th percentile was 71.9, while in subjects with moderate or severe renal impairment the geometric mean was 71, the 5th percentile was 19.7 and the 95th was 251.4.
Conclusion: A population parent/metabolite model was developed and validated with a new VPC technique, taking into account CrCL and input function. The model-based analysis indicated that the MR varied with the degree of renal impairment but not with the Remifentanil IV infusion rates.
References:
[1] Westmoreland CL, Hoke JF, Sebel PS, Hug CC Jr., Muir KT. Pharmacokinetics of remifentanil (GI87084B) and its major metabolite (GR90291) in patients undergoing elective inpatient surgery. Anaesthesiology 1993;79:893-903.
[2] Kapila A. Glass PS. Jacobs JR. Muir KT. Hermann DJ. Shiraishi M., et al. Measured context-sensitive half-times of remifentanil and alfentanil. Anesthesiology,1995;83(5):968-975.
[3] Pitsiu M, Wilmer A, Bodenham A, Breen D, Bach V, Bonde J, Kessler P, Albrecht S, Fisher G, Kirkham A. Pharmacokinetics of remifentanil and its major metabolite, remifentanil acid, in ICU patients with renal impairment. Br J Anaesth. 2004 Apr;92(4):493-503.