Background Mycophenolic acid (MPA) is an effective oral immunosuppressive drug used to treat lupus nephritis (LN), which exhibits large pharmacokinetic variability. This study aimed to characterize MPA pharmacokinetic behaviour in Mexican LN patients and to develop a population pharmacokinetic model which identified factors that influence MPA pharmacokinetic variability. Methods Blood samples from LN patients treated with mycophenolate mofetil (MMF) were collected pre dose and up to six hours post dose. MPA concentrations were determined by a validated ultra-performance liquid chromatography tandem mass spectrometry technique. Patients were genotyped for polymorphisms in enzymes (UGT1A8, 1A9 and 2B7) and transporters (ABCC2 and SLCO1B3). The anthropometric, clinical, genetic and co-medication characteristics of each patient were considered as potential covariates to explain the variability. Results A total of 294 MPA concentrations from 40 LN patients were included in the development of the model. The data were analysed using NONMEM software and were best described by a two-compartment linear model. MPA CL, Vc, Vp, Ka and Q were 15.4 L/h, 22.86 L, 768 L, 1.28 h−1 and 20.3 L/h, respectively. Creatinine clearance and prednisone co-administration proved to have influence on clearance, while body weight influenced Vc. The model was internally validated, proving to be stable. MMF dosing guidelines were obtained through stochastic simulations performed with the final model. Conclusions This is the first MPA population pharmacokinetic model to have found that co-administration of prednisone results in a considerable increase on clearance. Therefore, this and the other covariates should be taken into account when prescribing MMF in order to optimize the immunosuppressant therapy in patients with LN.
To implement and validate an analytical method by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC MS/MS) to quantify mycophenolic acid (MPA) in kidney transplant patients. Quantification of MPA was performed in an ACQUITY UPLC H Class system coupled to a Xevo TQD detector and it was extracted from plasma samples by protein precipitation. The chromatographic separation was achieved through an ACQUITY HSS C 18 SB column with 0.1% formic acid and acetonitrile (60:40 vol/vol) as mobile phase. The pharmacokinetic parameters were calculated by non-compartmental analysis of MPA plasma concentrations from 10 kidney transplant patients. The linear range for MPA quantification was 0.2-30 mg/L with a limit of detection of 0.07 mg/L; the mean extraction recovery was 99.99%. The mean intra-and inter-day variability were 2.98% and 3.4% with a percentage of deviation of 8.4% and 6.6%, respectively. Mean maximal concentration of 10 mg/L at 1.5 h, area under the concentrationtime curve of 36.8 mg·h/L, elimination half-life of 3.9 h, clearance of 0.32 L/h/kg and volume of distribution of 1.65 L/kg were obtained from MPA pharmacokinetics profiles. A simple, fast and reliable UPLC-MS/MS method to quantify MPA in plasma was validated and has been applied for pharmacokinetic analysis in kidney transplant patients.
Background Piperacillin-Tazobactam (PIP/TAZ) is a combination of a β-lactam antibiotic with a β-lactamase inhibitor, used to treat moderate to severe infections due to its broad-spectrum antibacterial activity. Its bactericidal effect is time-dependent. Therefore, the free-drug concentration should remain above the minimum inhibitory concentration during at least 50% of the dosing interval. Patients with severe infections develop pathophysiological changes that alter drugs pharmacokinetics (PK), leading to only 30% of probability of target attainment in clinical setting. Methods A prospective observational study was performed in patients with severe infections from Hospital Central “Dr. Ignacio Morones Prieto”. The protocol was approved by the Research and Ethics Committee (register 05-20) and patients signed written informed consent. Samples were collected at steady-state and plasma concentrations were quantified by liquid chromatography coupled to mass spectrometry. Data were analyzed by a population approach using NONMEM® software. Results A total of 52 patients were included (52% male) with a mean age of 46 ± 17 years and a body mass index of 25 ± 5 Kg/m2. According to the Akaike information criterion and visual inspection, a one-compartment open model was chosen to describe the concentration vs time data (n=156) for both drugs. Typical values (relative standard error) of PK parameters obtained were Clearance [CLPIP (L/h)] = 8.79 (12%) and Volume of distribution [VPIP (L)] = 17.6 (13%); and CLTAZ (L/h) = 12.6 (14%), VTAZ (L) = 32.8 (13%). Interindividual variability (IIV) of each parameter was modeled by exponential error and reported as coefficient of variation as follows: 75.3% and 88.7% for CL; 67.2% and 68.8% for V of PIP and TAZ, respectively. Finally, residual error was modeled as additive and presented a standard deviation (SD) of 7.28 µg/mL for PIP, and for TAZ was modeled as a combined with a SD of 0.22 µg/mL and a coefficient of variation of 17.32%. Conclusion Individualization and optimization of β-lactam dosing are essential in drugs with wide IIV as PIP/TAZ; hence, development of a population PK model will provide a valuable aid in explaining and quantifying some of this variability to allow a priori predictions to design initial regimens to reach pharmacotherapeutic targets. Disclosures All Authors: No reported disclosures.
Background Meropenem (MRP) is commonly used to treat serious infections and displays wide variability in plasma concentrations after administration of the same dose in critically ill patients due to factors that affect MRP volume of distribution (V) and clearance (CL) (e.g. edema, sepsis, kidney failure). These alterations could lead to not achieve the pharmacokinetic/pharmacodinamic (PK/PD) target with the consequent failure of antibacterial therapy. The aim of this study was to describe MRP pharmacokinetic parameters in critically ill patients in order to establish safe and effective initial dosing regimens adapted to patients characteristics. Methods This prospective observational study enrolled 78 critically ill patients receiving MRP based on the clinical, biochemical and microbiological findings. Blood sampling occurred at pre-dose, 1, 3 and 6h post-dose. MRP plasma concentrations were determined by high-performance liquid chromatography. Population pharmacokinetic modelling and Monte Carlo simulations were executed with NONMEM. Several regimen dosages of MRP under different scenarios were simulated in order to achieve high probability of target attainment (PTA > 90%) for PK/PD targets of %t > CMI 50% and 100%. Results In critically-ill Mexican patients, MRP PK were best described by a one compartment model. The final population model was: CL (L/h) = 11.9 ∗ (CLCr/102.23) and V (L) = 25.2. Final model was internally validated proving that it was stable and showed an adequate estimation of variability. Precision and bias fit were assessed through external validation comparing the predictive performance of the base and final models. Different initial dosage regimens were found for CLCr values in which the clinician can choose between a lower dose, a longer dosage interval or a shorter infusion time. However, for patients with augmented renal clearance or PK/PD target 100%t > MIC it was observed that no regimen complied PTA > 90%, suggesting a continuous infusion would be more appropriate. Conclusion This study demonstrates the wide variability in MRP pharmacokinetics and enhances the need to include therapeutic drug monitoring as part of stewardships interventions in critically ill patients to maximize bacteriological and clinical responses. Disclosures All Authors: No reported disclosures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.