Assessment of pharmacokinetic mycophenolic acid clearance models using Monte Carlo numerical analysis.

Previously, we performed population pharmacokinetic analysis and indicated age, mycophenolate mofetil (MMF)/mycophenolic acid (MPA) daily dose, and presence of nifedipine in patient therapy as significant predictors of MPA apparent clearance (CL/F) variability. This study aimed to determine the reliability of previously published population pharmacokinetic models derived from similar studies. Furthermore, this study investigated correspondence between chosen population models from the literature.By means of the Monte Carlo simulation method, pharmacokinetic models from different studies are simulated and analysed in the range of standard deviations of measured system parameters as well as the range of observed model parameters taken from the comparison studies.The 1000 numerical simulations were performed for every analysed model in order to calculate the most possible MPA CL/F values according to the expected values from the performed experiment. Fitting our results with other models showed how the presence of nifedipine makes difference in MPA CL/F values.By testing the data from selected studies into our model, a similar range of expected CL/F values was obtained, which may confirm the validity of our model. The results of our population pharmacokinetic study are partially applicable in models by other researchers.

Variability of mycophenolic acid elimination in the renal transplant recipients ­ population pharmacokinetic approach.

The aim of this study was to develop a population pharmacokinetic (PK) model for clearance of mycophenolic acid (MPA) in adult renal transplant recipients, to quantify the PK parameters and the influence of covariates on the MPA pharmacokinetic parameters. Parameters associated with plasma concentrations of MPA at steady-state were analyzed in 70 renal transplant recipients (mean age 42.97 years; mean total body weight 75.33 kg) using nonlinear mixed-effect modeling (NONMEM). Characteristics of patients screened for influence on the pharmacokinetic parameters were gender, age, body weight, time after transplantation, whether the patient was diagnosed as having diabetes mellitus, organ source (living or deceased donor), biochemical parameters and co-therapy (tacrolimus, cyclosporine, prednisolone, omeprazole, bisoprolol, carvedilol, nifedipine). A validation set of 25 renal transplant recipients was used to estimate the predictive performance of population pharmacokinetic model. Typical mean value of MPA oral clearance, estimated by base model (without covariates) was 0.741 L h(-1). During population modeling, the full model showed that clearance of the MPA was significantly influenced by age, total daily dose of MPA, creatinine clearance, albumin level, status and gender of a donor, and the nifedipine and tacrolimus co-therapy. In the final model, clearance of MPA was reported to be significantly influenced by age, total daily dose of MPA and thenifedipine co-therapy. The derived model describes adequately MPA clearance in terms of characteristics of our patients, offering basis for individual pharmacotherapy approach.

Joint use of population pharmacokinetics and machine learning for optimizing antiepileptic treatment in pediatric population.

Purpose: Unpredictable drug efficacy and safety of combined antiepileptic therapy is a major challenge during pharmacotherapy decisions in everyday clinical practice. The aim of this study was to describe the pharmacokinetics of valproic acid (VA), lamotrigine (LTG), and levetiracetam (LEV) in a pediatric population using nonlinear mixed-effect modeling, while machine learning (ML) algorithms were applied to identify any relationships among the plasma levels of the three medications and patients' characteristics, as well as to develop a predictive model for epileptic seizures. Methods: The study included 71 pediatric patients of both genders, aged 2-18 years, on combined antiepileptic therapy. Population pharmacokinetic (PopPK) models were developed separately for VA, LTG, and LEV. Based on the estimated pharmacokinetic parameters and the patients' characteristics, three ML approaches were applied (principal component analysis, factor analysis of mixed data, and random forest). PopPK models and ML models were developed, allowing for greater insight into the treatment of children on antiepileptic treatment. Results: Results from the PopPK model showed that the kinetics of LEV, LTG, and VA were best described by a one compartment model with first-order absorption and elimination kinetics. Reliance on random forest model is a compelling vision that shows high prediction ability for all cases. The main factor that can affect antiepileptic activity is antiepileptic drug levels, followed by body weight, while gender is irrelevant. According to our study, children's age is positively associated with LTG levels, negatively with LEV and without the influence of VA. Conclusion: The application of PopPK and ML models may be useful to improve epilepsy management in vulnerable pediatric population during the period of growth and development.

Pharmacokinetics and machine learning in epilepsy Abstract: Nowadays, combined antiepileptic therapy is the best option for a number of pediatric patients. Furthermore, there are no standard procedures in the therapy management of this complex treatment. Besides therapeutic monitoring, the population pharmacokinetic (PopPK) approach and machine learning (ML) are useful sources of information regarding the optimization of therapy. The aim of this study was to describe the pharmacokinetics of valproic acid (VA), lamotrigine (LTG), and levetiracetam (LEV) in a pediatric population using nonlinear mixed-effect modeling, while ML algorithms were applied to identify any relationships among the plasma levels of the three medications and patients' characteristics. The study included 71 pediatric patients of both genders, aged 2­18 years, on combined antiepileptic therapy. Population pharmacokinetic (PopPK) models were developed separately for VA, LTG, and LEV. Based on the estimated pharmacokinetic parameters and the patients' characteristics, three ML approaches were applied (principal component analysis, factor analysis of mixed data, and random forest). According to our study, children's age is positively associated with LTG levels, negatively with LEV and without influence from VA. However, the gender of patients has no influence on drug plasma concentration. Findings demonstrated that the application of PopPK and ML models may be useful to improve epilepsy management in vulnerable pediatric population during the period of growth and development.

Antibiotic utility and susceptibility changes of multidrug-resistant Escherichia coli and Klebsiella spp: 5-year experience in a tertiary healthcare centre.

OBJECTIVES: Multiple studies have identified cross-sectional relationships between antibiotic use and bacterial resistance. The aim of this study was to analyse the susceptibility of multidrug-resistant (MDR) and non-MDR (nMDR) isolates of Escherichia coli and Klebsiella spp to cephalosporins: ceftazidime (CTZ), ceftriaxone (CTX), cefepime (CEF) and fluoroquinolones: ciprofloxacin (CIP) and levofloxacin (LEV) in a tertiary healthcare centre from 2014 to 2018. In addition, we aimed to evaluate a correlation between the antibiotic utility and susceptibility of the selected enterobacteria. METHODS: Antibiotics consumption and antimicrobial resistance were monitored in a tertiary care university hospital from 2014 to 2018. Utilisation of antibiotics in the observed period was expressed as defined daily dose (DDD) per 100 bed/days (DBD). Bacterial susceptibility was reported as the percentage of susceptible results among all tested isolates from all patient samples. In further analysis, bacterial strains were considered as MDR or nMDR species. An MDR bacterial strain was defined as one with acquired non-susceptibility to at least one agent in three or more antimicrobial categories. RESULTS: Our results suggest that cephalosporins were the most used antibiotics, followed by fluoroquinolones, during the entire observed period 2014-2018. Our findings show that MDR isolates of E. coli had an increasing trend in susceptibility in relation to CTX (p=0.005), whereas a decreasing trend was observed for MDR isolates of E. coli susceptibility towards CIP and LEV (p<0.001). Klebsiella spp susceptibility for MDR isolates showed a decreasing trend in relation to CEF (p<0.001) and both fluoroquinolones (p<0.001). A significant negative association between CEF consumption and Klebsiella spp MDR isolates susceptibility was observed (p=0.045). CONCLUSION: Implementation of antimicrobial stewardship programmes with early detection and close monitoring of MDR bacterial strains of E. coli and Klebsiella spp may be a crucial step in reducing the menace of antimicrobial resistance, which is now a global problem.

Utility of salivary mycophenolic acid concentration monitoring: Modeling and Monte Carlo validation approach.

The results of the previous studies demonstrated an association between mycophenolic acid (MPA) exposure, serum albumin level (ALB), and adverse effects in kidney transplant patients. The aim was the identification of mathematical correlation and association between both, total and unbound MPA concentration in relation to ALB, body mass (BM), age and estimated glomerular filtration rate (eGFR) in stable kidney transplant recipients. Furthermore, investigation was conducted with the aim to clarify the role of salivary concentration (CSAL ) of MPA in adverse effect profile. In order to analyze the association between total and salivary concentration of MPA in relation to ALB, BM, age and eGFR, a least squares method for determining the correlation between these parameters was performed. In addition, derived mathematical model based on experimental data can also be performed and simulated through the Monte Carlo (MC) approach. Adverse effects were grouped according to the nature of symptoms and scored by a previously published validated system. Numerically calculated values of CSAL from the models [CSAL  = f(ALB, BM, age, eGFR, CP ) = a00 + a10 *(ALB, BM, age, eGFR) + a01 *CP ] were then compared with those from validation set of patients, where the best fitting model was for ALB [CSAL  = 54.96-1.64*ALB +13.4*CP ]. Adverse effects estimation showed the difference in esthetic score, positively correlated with CSAL in the lower ALB group (145.41 ± 219.02 vs. 354.08 ± 262.19; with statistical significance p = .014) and almost significant for gastrointestinal score (167.69 ± 174.79 vs. 347.55 ± 320.95; p = .247). The study showed that CSAL MPA may contribute to management of adverse effects, but these findings require confirmation of clinical utility.

Effect of the Interrelation between CYP3A5 Genotype, Concentration/Dose Ratio and Intrapatient Variability of Tacrolimus on Kidney Graft Function: Monte Carlo Simulation Approach.

Background: Tacrolimus (Tac) is characterized by large between- and within-patient (IPV) variability in pharmacokinetics and exposure. Aim: This study aimed to assess and validate the effect of Tac IPV and trough concentration-to-dose ratio (C0/D) over 6-12 months on reduced estimated glomerular filtration rate (eGFR) values in the late period after kidney transplantation (Tx), applying Monte Carlo (MC) simulation. Methods: The previously published linear regression was the basis for MC simulation, performed to determine how variations in significant predictors affect the distribution of eGFR from 13 to 36 months post-transplantation. The input C0/D values were derived from CYP3A5 genotype subgroups. Results: Patients characterized by high Tac IPV and low mean C0/D over 6-12 months could have been at greater risk of lower eGFR values in a three-year period following Tx compared to the other patient groups. This effect was more pronounced in patients with a lower eGFR at the 6th month and a history of acute rejection. The proven contribution of CYP3A5 expresser genotype to low C0/D values may suggest its indirect effect on long-term graft function. Conclusion: The findings indicate that simultaneous assessment of Tac IPV, C0/D, and CYP3A5 genotype may identify patients at risk of deterioration of graft function in the long-term post-transplantation period.

Adverse effects of mycophenolic acid in renal transplant recipients: gender differences.

Background Mycophenolic acid is widely used immunosuppressive drug, associated with adverse effects which increase patient morbidity and decrease medication adherence. Objective To evaluate the adverse effects in renal transplant recipients under mycophenolate treatment with respect to gender. Setting University Clinical Centre of Nis, Clinic of Nephrology, Serbia. Method This research included 96 renal transplant recipients, who received immunosuppressive regimen, based on tacrolimus or cyclosporin A, prednisone and mycophenolic acid. The high-performance liquid chromatography method combined with protein precipitation was used for the analysis of mycophelate concentration in human plasma. Drug concentration and dose-adjusted concentration were determined with respect to the patients' gender. An adverse effect scoring system developed by nephrologists within the University of Buffalo Nephrology/Transplant Program was used to monitor adverse effects of therapy. Main outcome measure Individual and scores of adverse effects in relation to the dosing regimen and gender. Results Results showed statistically lower dose and concentrations in men compared to the women in our investigation group. Also, female patients demonstrated higher mean scores (cumulative and subscores) within the same dosing regimens of mycophenolic acid. The gastrointestinal score was significantly higher in women who received a dose greater than 720 mg compared to men (0.20 ± 0.12 vs 0.12 ± 0.12). Women demonstrated higher individual adverse effects such as diarrhea and skin changes (41.7 vs 17.0; p = 0.038 and 62.5 vs 30.2; p = 0.037, respectively). Conclusions The results of our research showed that recipients' gender may play an important role in pharmacokinetic profile of mycophenolic acid, suggesting that women had higher concentration of mycophenolic acid and more serious side effects.

Metronidazole- and levofloxacin-induced psychotic disorders in chronic kidney patient.

We present a case which reports the occurrence of psychotic disorders after metronidazole and levofloxacin therapy in a chronic kidney patient while being treated for enterocolitis and urinary infection. A 48-year-old female was admitted to a hospital for the placement of a peritoneal dialysis catheter due to indicated peritoneal dialysis. During admission, symptoms of enterocolitis and urinary infection had occurred, so metronidazole and levofloxacin were introduced into therapy, respectively. After 4 days of metronidazole and 3 days of levofloxacin therapy, the patient became confused, disoriented, with signs of delirium. Since the diagnosis of psychoorganic disorder was made, the therapy with lorazepam and haloperidol was initiated, while metronidazole and levofloxacin were discontinued. Complete recovery 4 days after discontinuation indicates that the patient has experienced antibiotics-induced neurotoxicity. This is the first report of expressed neurotoxicity after the combination of metronidazole and levofloxacin in chronic kidney patients.

Potentially inappropriate prescribing among older patients and associated factors: comparison of two versions of STOPP/START criteria

Abstract The study aimed to estimate and compare the prevalence and type of potentially inappropriate medications (PIMs) and potential prescribing omissions (PPOs) between the STOPP/START original (v1) and updated version (v2) among older patients in various settings, as well as associated factors. The study included 440 patients attending a community pharmacy, 200 outpatients and 140 nursing home users. An increase in the prevalence of STOPP v2 (57.9%) compared to v1 (56.2%) was not statistically significant in the total sample and within each setting (p>0.05). A decrease in the prevalence of START v1 (55.8%) to v2 (41.2%) was statistically significant (p<0.001) in the total sample and within each setting (p<0.05). Drug indication (32.9%) and fall-risk medications (32.2%) were most commonly identified for STOPP v2, while cardiovascular system criteria (30.5%) were the most frequently detected for START v2. The number of medications was the strongest predictor for both STOPP v1 and v2, with odds ratio values of 1.35 and 1.34, respectively. Patients' characteristics associated with the occurrence of STOPP and START criteria were identified. According to both STOPP/START versions, the results indicate a substantial rate of potentially inappropriate prescribing among elderly patients. The prevalence of PIMs was slightly higher with the updated version, while the prevalence of PPOs was significantly lower

Current Biochemical Monitoring and Risk Management of Immunosuppressive Therapy after Transplantation.

Immunosuppressive drugs play a crucial role in the inhibition of immune reaction and prevention of graft rejection aswell as in the pharmacotherapy of autoimmune disorders. Effective immunosuppression should provide an adequate safety profile and improve treatment outcomes and the patients' quality of life. High-risk transplant recipients may be identified, but a definitive prediction model has still not been recognized. Therapeutic drug monitoring (TDM) for immunosuppressive drugs is an essential, but at the same time insufficient tool due to low predictability of drug exposition and marked pharmacokinetic variability. Parallel therapeutic, biochemical and clinical monitoring may successfully optimize and individualize therapy for transplanted recipients, providing optimal medical outcomes. Modern pharmacotherapy management should include new biomarkers with better sensitivity and specificity that can identify early cell damage. The aim of this study was to point out the importance of finding new biomarkers that would enable early detection of adverse drug events and cell damage in organ transplant recipients. We wanted to confirm the importance of routine biochemical monitoring in improving the safety of immunosuppressive treatment.