Schizandrol A (SZA) and schizandrol B (SZB) are two active ingredients of Wuzhi capsule (WZC), a Chinese proprietary medicine commonly prescribed to alleviate tacrolimus (FK-506)-induced hepatoxicity in China. Due to their inhibitory effects on cytochrome P450 (CYP) 3A enzymes, SZA/SZB may display drug–drug interaction (DDI) with tacrolimus. To identify the extent of this DDI, the enzymes’ inhibitory profiles, including a 50% inhibitory concentration (IC50) shift, reversible inhibition (RI) and time-dependent inhibition (TDI) were examined with pooled human-liver microsomes (HLMs) and CYP3A5-genotyped HLMs. Subsequently, the acquired parameters were integrated into a physiologically based pharmacokinetic (PBPK) model to quantify the interactions between the SZA/SZB and the tacrolimus. The metabolic studies indicated that the SZB displayed both RI and TDI on CYP3A4 and CYP3A5, while the SZA only exhibited TDI on CYP3A4 to a limited extent. Moreover, our PBPK model predicted that multiple doses of SZB would increase tacrolimus exposure by 26% and 57% in CYP3A5 expressers and non-expressers, respectively. Clearly, PBPK modeling has emerged as a powerful approach to examine herb-involved DDI, and special attention should be paid to the combined use of WZC and tacrolimus in clinical practice.

IntroductionPeritonitis is a major complication of continuous ambulatory peritoneal dialysis (CAPD), the risk of which is significantly influenced by the type of PD transfer system. Although the Y-disconnect and double-bag system is more efficient in preventing peritonitis compared with the spike system, little information is available to differentiate risks between different brands of the Y-disconnect double-bag system. A randomised controlled trial to evaluate the safety and efficacy of a newly introduced system is needed to provide the necessary clinical evidence to guide policy decision-making.Methods and analysisThe study is an open-label randomised controlled trial. A total of 434 patients with end-stage renal disease undergoing CAPD will be enrolled and randomised to either the intervention group, Stay Safe Link, or the control group, Stay Safe. All study subjects will be followed up and monitored for 1 year. The primary safety outcome is the rate of peritonitis while the primary efficacy outcomes are the delivered dialysis dose and ultrafiltration volume.Ethics and disseminationThe study was approved by the Medical Research Ethics Committee, National Institute of Health Malaysia. A written informed consent will be obtained from all participating subjects prior to any trial-related procedure and the study conduct will adhere strictly to Good Clinical Practice. The findings will be disseminated in a peer-reviewed journal.Trial registration numberNCT03177031; Pre-results.

Aim: nlmixr offers first-order conditional estimation with or without interaction (FOCE or FOCEi) and stochastic approximation estimation-maximisation (SAEM) to fit nonlinear mixed-effect models (NLMEM). We modelled metformin’s population pharmacokinetics with flip-flop characteristics within nlmixr framework and investigated SAEM and FOCEi’s performance with respect to bias, precision, and robustness. Method: Compartmental pharmacokinetic models were fitted. The final model was determined based on the lowest objective function value and visual inspection of goodness-of-fit plots. To examine flip-flop pharmacokinetics, k_a values of a typical concentration-time profile based on the final model were perturbed and changes in the steepness of the terminal elimination phase were evaluated. The bias and precision of parameter estimates were compared between SAEM and FOCEi using stochastic simulations and estimations. For robustness, parameters were re-estimated as the initial estimates were perturbed 100-times and resultant changes evaluated. Results: A one-compartment model with transit compartment for absorption best described the data. At low n, Stirling’s approximation of n! over-approximated plasma concentration unlike the log-gamma function. Flip-flop pharmacokinetics were evident as the steepness of the terminal elimination phase changed with k_a. Mean rRMSE for fixed-effect parameters was 0.932. When initial estimates were perturbed, FOCEi estimates of k_a and food effect on k_a appeared bimodal and were upward biased. Discussion: nlmixr is reliable for NLMEM even if flip-flop is present but caution should be exercised when using Stirling’s approximation for n! in the transit compartment model. SAEM was marginally superior to FOCEi in bias and precision, but SAEM was superior against initial estimate perturbations.

Background: Ganciclovir and valganciclovir are used for prophylaxis and treatment of cytomegalovirus infection. However, there is great interindividual variability in ganciclovir’s pharmacokinetics (PK), highlighting the importance of individualized dosing. To facilitate model-informed precision dosing (MIPD), this study aimed to establish a parametric model repository of ganciclovir and valganciclovir by summarizing existing population pharmacokinetic information and analyzing the sources of variability. (2) Methods: A total of four databases were searched for published population PK models. We replicated these models, evaluated the impact of covariates on clearance, calculated the probability of target attainment for each model based on a predetermined dosing regimen, and developed an area under the concentration–time curve (AUC) calculator using maximum a posteriori Bayesian estimation. (3) Results: A total of 16 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area) and renal function. The results show that 5 mg/kg/12 h of ganciclovir could make the AUC0–24h within 40–80 mg·h/L for 50.03% pediatrics but cause AUC0–24h exceeding the exposure thresholds for toxicity (120 mg·h/L) in 51.24% adults. (4) Conclusions: Dosing regimens of ganciclovir and valganciclovir should be adjusted according to body size and renal function. This model repository has a broad range of potential applications in MIPD.