Physiologically‐based pharmacokinetic model to investigate the effect of pregnancy on risperidone and paliperidone pharmacokinetics: Application to a pregnant woman and her neonate

• Main Authors: Walaa Y. B. Mahdy (Author), Kazuhiro Yamamoto (Author), Takahiro Ito (Author), Naoko Fujiwara (Author), Kazumichi Fujioka (Author), Tadasu Horai (Author), Ikuo Otsuka (Author), Hitomi Imafuku (Author), Tomohiro Omura (Author), Kazumoto Iijima (Author), Ikuko Yano (Author)
• Format: Book
• Published: Wiley, 2023-04-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1752-8062; 1752-8054; 10.1111/cts.13473
• Keywords: Therapeutics. Pharmacology; RM1-950; Public aspects of medicine; RA1-1270
• Source: Clinical and Translational Science, Vol 16, Iss 4, Pp 618-630 (2023)

Abstract This study aimed to determine the effects of pregnancy and ontogeny on risperidone and paliperidone pharmacokinetics by assessing their serum concentrations in two subjects and constructing a customized physiologically‐based pharmacokinetic (PBPK) model. Risperidone and paliperidone serum concentrations were determined in a pregnant woman and her newborn. PBPK models for risperidone and paliperidone in adults, pediatric, and pregnant populations were developed and verified using the Simcyp simulator. These models were then applied to our two subjects, generating their "virtual twins." Effects of pregnancy on both drugs were examined using models with fixed pharmacokinetic parameters. In the neonatal PBPK simulation, 10 different models for estimating the renal function of neonates were evaluated. Risperidone was not detected in the serum of both pregnant woman and her newborn. Maternal and neonatal serum paliperidone concentrations were between 2.05-3.80 and 0.82-1.03 ng/ml, respectively. Developed PBPK models accurately predicted paliperidone's pharmacokinetics, as shown by minimal bias and acceptable precision across populations. The individualized maternal model predicted all observed paliperidone concentrations within the 90% prediction interval. Fixed‐parameter simulations showed that CYP2D6 activity largely affects risperidone and paliperidone pharmacokinetics during pregnancy. The Flanders metadata equation showed the lowest absolute bias (mean error: 22.3% ± 6.0%) and the greatest precision (root mean square error: 23.8%) in predicting paliperidone plasma concentration in the neonatal population. Our constructed PBPK model can predict risperidone and paliperidone pharmacokinetics in pregnant and neonatal populations, which could help with precision dosing using the PBPK model‐informed approach in special populations.