This prospective study aimed to evaluate the effect of metronomic cyclophosphamide on carboplatin’s tolerability, efficacy, and pharmacokinetics in dogs with mammary carcinoma. Sixteen female dogs with mammary carcinoma were divided into groups: 300 mg/m² intravenous (i.v.) carboplatin therapy (G1 = 8) or 300 mg/m² i.v. carboplatin which was associated with 12.5 mg/m² oral cyclophosphamide in a metronomic regimen (G2 = 8). The investigated animals underwent a clinical evaluation, a mastectomy, a carboplatin chemotherapy, and serial blood sampling for the pharmacokinetic analysis. The adverse events and survival rates were monitored. A non-compartmental analysis was applied to calculate the pharmacokinetic parameters of carboplatin in the 2nd and 4th chemotherapy cycles. Carboplatin PK showed high interindividual variability with a 10-fold variation in the area under the plasma concentration–time curve (AUC) in G1. The systemic plasma exposure to carboplatin was equivalent in both of the treatments considering the AUC and maximum plasma concentration (C_max) values. Although the red blood cells (p < 0.0001), platelets (p = 0.0005), total leukocytes (p = 0.0002), and segmented neutrophils (p = 0.0007) were reduced in G2, the survival rate increased (p = 0.0044) when it was compared to G1. In conclusion, adding low daily doses of cyclophosphamide to a carboplatin therapy showed promising outcomes in female dogs with mammary tumors.

The present study assessed the effect of systemic lupus erythematosus (SLE) activity, a chronic and inflammatory autoimmune disease, on the sinusoidal uptake transporter OATP1B1 using atorvastatin (ATV) as a probe drug. Fifteen healthy subjects, 13 patients with controlled SLE (SLEDAI 0–4), and 12 patients with uncontrolled SLE (SLEDAI from 6 to 15), all women, were investigated. Apparent total clearance of midazolam (MDZ), a marker of CYP3A4 activity, did not vary among the three investigated groups. The controlled and uncontrolled SLE groups showed higher plasma concentrations of MCP‐1 and TNF‐α, while the uncontrolled SLE group also showed higher plasma concentrations of IL‐10. The uncontrolled SLE group showed higher area under the curve (AUC) for ATV (60.47 (43.76–83.56) vs. 30.56 (22.69–41.15) ng⋅hour/mL) and its inactive metabolite ATV‐lactone (98.74 (74.31–131.20) vs. 49.21 (34.89–69.42) ng⋅hour/mL), and lower apparent total clearance (330.7 (239.30–457.00) vs. 654.5 (486.00–881.4) L/hour) and apparent volume of distribution (2,609 (1,607–4,234) vs. 7,159 (4,904–10,450) L), when compared to the healthy subjects group (geometric mean and 95% confidence interval). The pharmacokinetics of ATV and its metabolites did not differ between the healthy subject group and the patients with controlled SLE group. In conclusion, uncontrolled SLE increased the systemic exposure to both ATV and ATV‐lactone, inferring inhibition of OATP1B1 activity, once in vivo CYP3A4 activity assessed by oral clearance of MDZ was unaltered. The inflammatory state, not the disease itself, was responsible for the changes described in the uncontrolled SLE group as a consequence of inhibition of OATP1B1, because systemic exposure to ATV and its metabolites were not altered in patients with controlled SLE.

This study employed physiologically‐based pharmacokinetic–pharmacodynamics (PBPK/PD) modeling to predict the effect of obesity and gastric bypass surgery on the pharmacokinetics and intragastric pH following omeprazole treatment. The simulated plasma concentrations closely matched the observed data from non‐obese, morbidly obese, and post‐gastric bypass populations. Obesity significantly reduces CYP3A4 and CYP2C19 activities, as reflected by the metabolic ratio [omeprazole sulphone]/[omeprazole] and [5‐hydroxy‐omeprazole]/[omeprazole]. The morbidly obese model accounted for the down‐regulation of CYP2C19 and CYP3A4 to recapitulate the observed data. Sensitivity analysis showed that intestinal CYP3A4, gastric pH, small intestine bypass, and the delay in bile release do not have a major influence on omeprazole exposure. Hepatic CYP3A4 had a significant impact on the AUC of (S)‐omeprazole, while hepatic CYP2C19 affected both (R)‐ and (S)‐omeprazole AUC. After gastric bypass surgery, the activity of CYP3A4 and CYP2C19 is restored. The PBPK model was linked to a mechanism‐based PD model to assess the effect of omeprazole on intragastric pH. Following 40 mg omeprazole, the mean intragastric pH was 4.3, 4.6, and 6.6 in non‐obese, obese, and post‐gastric bypass populations, and the daily time with pH >4 was 14.7, 16.4, and 24 h. Our PBPK/PD approach provides a comprehensive understating of the impact of obesity and weight loss on CYP3A4 and CYP2C19 activity and omeprazole pharmacokinetics. Given that simulated intragastric pH is relatively high in post‐RYGB patients, irrespective of the dose of omeprazole, additional clinical outcomes are imperative to assess the effect of proton pump inhibitor in preventing marginal ulcers in this population.

Background/Objectives: Omeprazole is widely used for managing gastrointestinal disorders like GERD, ulcers, and H. pylori infections. However, its use in pediatrics presents challenges due to drug interactions (DDIs), metabolic variability, and safety concerns. Omeprazole’s pharmacokinetics (PK), primarily influenced by CYP2C19 metabolism, is affected by ontogenetic changes in enzyme expression, complicating dosing in children. Methods: This study aimed to develop and validate a physiologically based pharmacokinetic (PBPK) model for omeprazole and its metabolites to predict age-related variations in metabolism and response. Results: The PBPK model successfully predicted exposure to parent and metabolites in adults and pediatrics, incorporating competitive and mechanism-based inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites. By accounting for age-dependent metabolic pathways, the model enabled priori predictions of omeprazole exposure in different age groups. Linking PK to the pharmacodynamics (PD) model, we described the impact of age-related physiological changes on intragastric pH, the primary outcome for proton pump inhibitors efficacy. Conclusions: The PBPK-PD model allowed for the virtual testing of dosing scenarios, providing an alternative to clinical studies in pediatrics where traditional DDI studies are challenging. This approach offers valuable insights for accurate dosing recommendations in pediatrics, accounting for age-dependent variability in metabolism, and underscores the potential of PBPK modeling in guiding pediatric drug development.