Yesong Shin, Dongwoo Chae, Kyungsoo Park
yonsei
Objectives:
Leflunomide is an immunosuppressive drug indicated for the treatment of rheumatoid arthritis and psoriatic arthritis. Orally administrated leflunomide is mostly metabolized during first pass through the liver. Hence, the pharmacokinetic (PK) profile of leflunomide is commonly analyzed using the dominant active metabolite, A771726, also called teriflunomide. While the PK of teriflunomide is influenced by several factors, such as enterohepatic recycling, protein binding, and genetics, and shows large interindividual variability [1,2] its PK characteristics has not been investigated in Koreans from the population point of view. The goal of this study was to develop a population pharmacokinetic model for teriflunomide and elucidate influencing factors in Korean population.
Methods:
Data was collected from a total of 80 healthy male adult volunteers participating in bioavailability studies of leflunomide. The study subjects’ age was 25.2±3.8 years and weights 71.2±8.9kg (mean±SD). A dose of 40 mg consisting of two 20 mg tablets was given as a single oral administration under fasting condition. Blood samples were collected at pre-dose, 0, 1, 3, 5, 8, 11, 15, 24, 48, 96, 144, 216, 313, 408, 576, and 744 h post-dose. NONMEM ver. 7.3 and R ver. 3.5.2 were used for analysis.
Results:
Exploratory data analysis revealed a rapid absorption phase followed by a second peak in individuals. Through iterative steps of model comparison, the model chosen was a two compartment model with first order absorption and enterohepatic recycling. Here, for modeling enterohepatic recycling, in addition to lag time for drug accumulation (T1) and duration of drug release (DH), two additional parameters were included, KGALL representing the rate of transition from the gallbladder to the gut and KAGUT the reabsorption from the gut to the plasma. The final model well described the data and was judged physiologically plausible. The typical parameter estimates were 0.699 h-1 for absorption rate constant (KA), 0.856 L for central compartment volume(V), 5.31 L for peripheral compartment volume(V2), 2.45 L/h for inter-compartment clearance(Q), 0.0206 L/h for clearance of central compartment(CL), and those for enterohepatic recycling were 4.8 h for T1, 5.6 h for DH, 4.94 h-1 for KGALL and 0.0266 h-1 for KAGUT.[KP1] [예신2] Without gut compartment, the RSE and difficulty of estimating parameters had increased. As a result, the compartment added to reduce the problem. There were two additional parameters associated with enterohepatic recycling – KGALL representing the rate of transition from the gallbladder to the gut and KAGUT the reabsorption from the gut to the plasma, estimated as 4.94 h-1 and 0.0266 h-1, respectively. The inter-individual variability estimates (CV%) were 50.8% for KA, 32.6% for V, 30.7% for V2, 12% for Q, 27.1% for CL, 12.8% for T1, 54.6% for KGALL and 74.3% for KAGUT. The proportional residual error (CV%) was estimated as 11.5%. As proceeding stepwise covariate analysis, in terms of covariates, there are statistically significant relationship between weight and concentration(p=0.0022). [KP3] The final model including covariate factor decreased OFV and induced accuracy. When these results were compared with previous results in the literature, disposition parameters were similar to those from Chinese [3] where systemic clearance was 0.017 L/h and volume of distribution was 6.040 L. However, genetic analysis was not conducted in our study and could not be compared with previous results whereas ABCG2 was associated with teriflunomide PK [3].
Conclusions:
Our model was well fitted to the concentration-time course of teriflunomide. However, the model has limitations in that genetic factors were not examined and high variabilities of some of model parameters remain to be explained. Further work would be necessary to supplement the current results.
References:
[1] AM Hopkins, MD Wiese, SM Proudman, CE O’Doherty, DJR Foster, and RN Upton. Semiphysiologically Based Pharmacokinetic Model of Leflunomide Disposition in Rheumatoid Arthritis Patients. CPT Pharmacometrics Syst Pharmacol. 2015 Jun; 4(6): 362–371.
[2] Bohanec Grabar P, Investigation of the influence of CYP1A2 and CYP2C19 genetic polymorphism on 2-Cyano-3-hydroxy-N-[4-(trifluoromethyl)phenyl]-2-butenamide (A77 1726) pharmacokinetics in leflunomide-treated patients with rheumatoid arthritis. Drug Metab Dispos. 2009 Oct;37(10):2061-8. doi: 10.1124/dmd.109.027482. Epub 2009 Jul 6.
[3] Xueting Yao, Yiwen Wu, Ji Jiang, A population pharmacokinetic study to accelerate early phase clinical development for a novel drug, teriflunomide sodium, to treat systemic lupus erythematosus, European Journal of Pharmaceutical Sciences Volume 136, 1 August 2019, 104942
Reference: PAGE () Abstr 9569 [www.page-meeting.org/?abstract=9569]
Poster: Methodology - Model Evaluation