Four glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have been used in children and adolescents with obesity or overweight. This network meta-analysis was conducted to compare the efficacy and safety of these regimens. Embase, PubMed, and Scopus were searched on March 2023 and updated in June 2024 for eligible randomized controlled trials (RCTs). The primary efficacy outcomes were mean difference in actual body weight, BMI (body mass index), BMI z score, and waist circumference. Safety outcomes included nausea, vomiting, diarrhea, abdominal pain, injection-site reaction, and hypoglycemia. Eleven RCTs with 953 participants were eligible. Semaglutide exhibited greater effects in reducing weight, BMI, and BMI z score versus the placebo. Semaglutide was associated with greater weight loss and BMI z score reduction in comparison with exenatide, liraglutide, and dulaglutide. Semaglutide also significantly decreased BMI than exenatide. None of the four GLP-1 RAs were associated with higher risks of diarrhea, headache, and abdominal pain versus the placebo. Liraglutide was more likely to cause nausea, vomiting, hypoglycemia, and injection-site reactions than the placebo. Liraglutide also had higher odds of causing injection-site reactions than other GLP-1 RAs. Semaglutide appeared to be the most effective and safe option among four GLP-1 RAs in children and adolescents with obesity or overweight.

Drug-induced liver injury (DILI) is a major cause of the withdrawal of pre-marketed drugs, typically attributed to oxidative stress, mitochondrial damage, disrupted bile acid homeostasis, and innate immune-related inflammation. DILI can be divided into intrinsic and idiosyncratic DILI with cholestatic liver injury as an important manifestation. The diagnosis of DILI remains a challenge today and relies on clinical judgment and knowledge of the insulting agent. Early prediction of hepatotoxicity is an important but still unfulfilled component of drug development. In response, in silico modeling has shown good potential to fill the missing puzzle. Computer algorithms, with machine learning and artificial intelligence as a representative, can be established to initiate a reaction on the given condition to predict DILI. DILIsym is a mechanistic approach that integrates physiologically based pharmacokinetic modeling with the mechanisms of hepatoxicity and has gained increasing popularity for DILI prediction. This article reviews existing in silico approaches utilized to predict DILI risks in clinical medication and provides an overview of the underlying principles and related practical applications.

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 AUC_0–24h within 40–80 mg·h/L for 50.03% pediatrics but cause AUC_0–24h 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.

This study investigated the antitumor effects of foretinib on triple-negative breast cancer cells MDA-MB-231 xenograft tumors in vivo underlying phosphorylated mesenchymal to epithelial transition (p-MET)/ hepatocyte growth factor (HGF)-related mechanism, as well as its pharmacokinetic characteristics. The MDA-MB-231 human breast cancer cell line was used for in vitro experiments, and the tumor xenograft model was established for in vivo experiments. MDA-MB-231 xenograft mice received oral foretinib (15 or 50 mg/kg/day) or vehicle for 18 days. The xenograft tumors were collected. Protein expressions of p-MET and HGF were examined with Western blotting and immunohistochemical staining. The mRNA expression of MET was examined with real-time PCR. Blood samples were collected from the mice treated with foretinib under different doses of 2, 10, and 50 mg/kg, and the pharmacokinetic profiles of foretinib were evaluated. We found that foretinib treatment caused a significant inhibition in tumor growth in a dose-dependent manner, whereas the continuous administration did not result in weight loss in treated nude mice. In both MDA-MB-231 cells and xenograft tumors, foretinib suppressed the expression of p-MET and HGF. These findings reveal that the decrease of p-MET and HGF may play an important role in the anti-breast cancer properties of foretinib.

Background: Caspofungin is an echinocandin antifungal agent commonly used as the first-line therapy for invasive candidiasis, salvage therapy for invasive aspergillosis, and empirical therapy for presumed fungal infections. Pharmacokinetic (PK) variabilities and suboptimal exposure have been reported for caspofungin, increasing the risk of insufficient efficacy. Objective: This work aimed to develop a caspofungin population pharmacokinetic (popPK) library and demonstrate its utility by assessing the probability of target attainment across diverse settings. Methods: We established a caspofungin popPK model library following a rigorous literature review, re-implementing selected models in R with rxode2. Quality control procedures included a comparison of different studies and assessing covariate impacts. Model libraries were primarily used to perform Monte Carlo simulations to estimate target attainment and guide personalized dosing in Candida infections. Results: A total of 13 models, one- or two-compartment models, were included. The most significant covariates were body size (weight and body surface area), liver function, and albumin level. The results show that children and adults showed considerable differences in pharmacokinetics. For C. albicans and C. parapsilosis, none of the populations achieved a PTA of ≥90% at their respective susceptible MIC values. In contrast, for C. glabrata, 70% of the adult studies reached a PTA of ≥90%, while all pediatric studies achieved the same PTA level. Conclusion: At the recommended dosage, adult patients showed notably lower exposure to caspofungin compared to pediatric patients. Considering body size, liver function, and serum albumin is crucial when determining caspofungin dosage regimens. Furthermore, further research is required to comprehensively understand the pharmacokinetics of caspofungin in pediatric patients.