Population pharmacokinetics of peginterferon α2a in patients with chronic hepatitis B

www.nature.com/scientificreports OPEN Received: 14 March 2017 Accepted: 10 July 2017 Published: xx xx xxxx Population pharmacokinetics of peginterferon α2a in patients with chronic hepatitis B Jingfeng Bi 1, Xingang Li2, Jia Liu3, Dawei Chen4, Shuo Li5, Jun Hou1, Yuxia Zhou6, Shanwei Zhu7, Zhigang Zhao2, Enqiang Qin4 & Zhenman Wei1 There were significant differences in response and pharmacokinetic characteristics to the peginterferon α2a treatment among Chronic Hepatitis B (CHB) patients. The aim of this study is to identify factors which could significantly impact the peginterferon α2a pharmacokinetic characteristics in CHB patients. There were 208 blood samples collected from 178 patients who were considered as CHB and had been treated with peginterferon α2a followed by blood concentration measurement and other laboratory tests. The covariates such as demographic and clinical characteristics of the patients were retrieved from medical records. Nonlinear mixed-effects modeling method was used to develop the population pharmacokinetic model with NONMEM software. A population pharmacokinetic model for peginterferon α2a has been successfully developed which shows that distribution volume (V) was associated with body mass index (BMI), and drug clearance (CL) had a positive correlation with creatinine clearance (CCR). The final population pharmacokinetic model supports the use of BMI and CCR-adjusted dosing in hepatitis B virus patients. Hepatitis B virus (HBV) associates approximately 780,000 deaths each year worldwide, mostly due to the chronic hepatitis B infection1. It has been proved that pegylated interferon alfa-2a (pegylated with a branched 40 kDa PEG chain) is an antiviral drug and it has a dual mode of action includes both antiviral and immunomodulatory effects2. The addition of polyethylene glycol to the interferon, through a process known as pegylation enhances the half-life of the interferon when we compared it to its native form3. This drug has been approved around the world, such as EU, U.S., China and many other countries, on the treatment of chronic hepatitis B (CHB). Numerous international multi-centers randomized controlled clinical trials have proved that for the HBeAg-positive CHB patients, treated with peginterferon α2a 180 μg/week for 48 weeks and follow-up by 24 weeks observation, the HBeAg seroconversion rate was 32~36% and HBsAg seroconversion rate was 2.3~3%4. The significant difference in responses to the treatment among patients was observed5, 6. A preliminary study of the pharmacokinetics on peginterferon α2a in adults has indicated that the coefficient of variation (CV%) of AUC0−t was 36.00%, t1/2Z was 33.67%, Tmax was 30.16%, and Cmax was 36.60%7. We believed that the high inter-individual variability (IIV) of the pharmacokinetic characteristics may be the primary cause for the differences of curative effect. Therefore, we aimed to identify the factors which could significantly influence the peginterferon α2a in vivo behavior in HBV patients. Furthermore, it is necessary to build a quantitative relationship between the influence factors and IIV. Population pharmacokinetic modeling was used to solve this problem8. Once this population model established, it will be helpful to realize precision medication for the patient with HBV. Results Patient demographics. The study of demography and clinical characteristics of the patients, which includes age (AGE, year), weight (WT, kg), body mass index (BMI, kg/m2), height (HT, cm), gender (GNDR, male = 1; 1 Research Center for Clinical & Translational Medicine, 302 Military Hospital, Beijing, 100039, China. 2Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050, China. 3Laboratory Center, 302 Military Hospital, Beijing, 100039, China. 4Infectious Disease Treatment Center, 302 Military Hospital, Beijing, 100039, China. 5Ministry of Health, 302 Military Hospital, Beijing, 100039, China. 6Medical Information Center, 302 Military Hospital, Beijing, 100039, China. 7Department of Pharmacy, 302 Military Hospital, Beijing, 100039, China. Jingfeng Bi, Xingang Li and Jia Liu contributed equally to this work. Correspondence and requests for materials should be addressed to E.Q. (email: ) or Z.W. (email: ) Scientific REPortS | 7: 7893 | DOI:10.1038/s41598-017-08205-5 1 www.nature.com/scientificreports/ Characteristics Number or mean ± SD Median (range) No. patients 178 — No. observations 208 — Observations per patient 1–4 — Dose (ng) 156730.34 ± 27835.12 18000 (50000–180000) Sampling time after dosing (h) — 141.5 (15–13958) Male 99 (55.62) — Female 79 (44.38) — Age (year) 48.40 ± 12.91 50.5 (15–75) Body weight (kg) 65.52 ± 11.74 64 (42.5–100) Alanine transaminase (U/L) 34.79 ± 26.36 26.5 (3–150) Aspartate transaminase (U/L) 37.65 ± 21.01 31 (14–149) Creatinine clearance (mL/min) 91.39 ± 24.33 91.66 (44.80–166.87) Serum creatinine (μmol/L) 74. 65 ± 12.42 73 (44–106) Body mass index (kg/m2) 23.41 ± 3.48 23.33 (15.43–33.80) Height (cm) 166.89 ± 7.95 168 (145–191) GNDR, n (%) Table 1. Demographic background and clinical characteristics of the subjects for modeling. female = 2) were retrieved from medical records. Laboratory results in records, such as serum creatinine (SCR, μmol/L), creatinine clearance (CCR, mL/min, estimated according to the Cockcroft-Gault formula9), aspartate transaminase (AST, U/L), alanine transaminase (ALT, U/L) and disease grade [Disease, hepatitis (APRI ≤ 2) = 1, Compensated Cirrhosis (APRI > 2) = 2] have been tested in one week before blood samples were collected. A total of 178 patients with 208 observations were obtained for analysis and the demographic background of patients for modeling was listed in Table 1. In order to identify the relationship of all the covariates, matrix diagram was performed by SPSS software (version 16.0, SPSS Inc., Chicago, IL, USA) and the result was shown in Fig. 1. Several significant were observed from the Fig. 1, such as AST and ALT, CCR and AGE, CCR and WT, GNDR and HT, BMI and WT, WT and HT, etc. These correlations indicated that related covariates may have interaction when adding them into the population model. Population pharmacokinetic model. The scatter plot of drug concentration versus time has been presented in Fig. 2. Due to the sparse data, it is difficult to identify the one- or two-compartmental model from this plot. Based on the objective function value (OFV) changes, the one-compartmental model was selected as the basic model. The following equations were used to describe this model: dX a = − K a × X a [X a(0) = Dose] dt (1) dX = K a × X a − CL × C [X (0) = 0] dt (2) C = X V (3) where Xa and X respectively represent the drug amount in absorption compartment and the central compartment. Ka represents the drug absorption rate constant from the dosing site. C represents the plasma drug concentration and V represents the distribution volume. (...truncated)