A prospective controlled, randomized clinical trial of kidney transplant recipients developed personalized tacrolimus dosing using model-based Bayesian Prediction.

For three decades, tacrolimus (Tac) dose adjustment in clinical practice has been calculated empirically according to the manufacturer's labeling based on a patient's body weight. Here, we developed and validated a Population pharmacokinetic (PPK) model including pharmacogenetics (cluster CYP3A4/CYP3A5), age, and hematocrit. Our study aimed to assess the clinical applicability of this PPK model in the achievement of Tac Co (therapeutic trough Tac concentration) compared to the manufacturer's labelling dosage. A prospective two-arm, randomized, clinical trial was conducted to determine Tac starting and subsequent dose adjustments in 90 kidney transplant recipients. Patients were randomized to a control group with Tac adjustment according to the manufacturer's labeling or the PPK group adjusted to reach target Co (6-10 ng/ml) after the first steady state (primary endpoint) using a Bayesian prediction model (NONMEM). A significantly higher percentage of patients from the PPK group (54.8%) compared with the control group (20.8%) achieved the therapeutic target fulfilling 30% of the established superiority margin defined. Patients receiving PPK showed significantly less intra-patient variability compared to the control group, reached the Tac Co target sooner (5 days vs 10 days), and required significantly fewer Tac dose modifications compared to the control group within 90 days following kidney transplant. No statistically significant differences occurred in clinical outcomes. Thus, PPK-based Tac dosing offers significant superiority for starting Tac prescription over classical labeling-based dosing according to the body weight, which may optimize Tac-based therapy in the first days following transplantation.

Population pharmacokinetic modelling of fibrinogen in patients with congenital or acquired-chronic or acute-hypofibrinogenaemia.

AIMS: Fibrinogen is the key substrate for coagulation. Fibrinogen pharmacokinetics (PK) after single doses of fibrinogen concentrate (FC), using modelling approaches, has only been evaluated in congenital afibrinogenaemic patients. The aims of this study are to characterize the fibrinogen PK in patients with acquired-chronic (cirrhosis) or acute-hypofibrinogenaemia (critical haemorrhage), showing endogenous production. Influencing factors of differences on the fibrinogen PK between subpopulations will be identified. METHODS: A total of 428 time-concentration values from 132 patients were recorded. Eighty-two out of 428 values were from 41 cirrhotic patients administered with placebo and 90 out of 428 were from 45 cirrhotic patients that were given FC, 161 out of 428 values were from 14 afibrinogenaemic patients and 95 out of 428 values were from 32 severe acute trauma haemorrhagic patients. A turnover model that accounted for endogenous production and exogenous dose was fitted using NONMEM74. The production rate (Ksyn), distribution volume (V), plasma clearance (CL) and concentration yielding to 50% of maximal fibrinogen production (EC50) were estimated. RESULTS: Fibrinogen disposition was described by a one-compartment model with CL and V values of 0.0456 L·h-1 and 4.34 L·70 kg-1 , respectively. Body weight was statistically significant in V. Three different Ksyn values were identified that increased from 0.00439 g·h-1 (afibrinogenaemia), to 0.0768 g·h-1 (cirrhotics) and 0.1160 g·h-1 (acute severe trauma). EC50 was of 0.460 g·L-1 . CONCLUSIONS: This model will be key as a support tool for dose calculation to achieve specified target fibrinogen concentrations, in each of the studied populations.

Predictors of Infliximab Trough Concentrations in Inflammatory Bowel Disease Patients Using a Repeated-Measures Design.

BACKGROUND AND AIMS: Treating patients based on a treat-to-trough approach has been shown to be a cost-effective strategy for inflammatory bowel disease (IBD) patients who have become unresponsive to infliximab (IFX). However, the documented evidence for this is limited, and some controversy remains regarding the use of routine proactive therapeutic drug monitoring (TDM). To support routine TDM of IFX and regimen optimization in IBD patients, more in-depth knowledge of the covariates that affect the pharmacokinetic (PK) variability of IFX is needed. The aim of this study was to identify the characteristics of the patient, disease, and treatments that influence IFX PK and exposure in our cohort of IBD patients using a repeated-measures design. METHODS: We performed a prospective observational study of adult IBD patients who received IFX between July 2013 and March 2017. We obtained repeated IFX trough concentration (Cmin) measurements and implemented a previously described population pharmacokinetic model to estimate individual clearance (CL). From the individual primary parameters, the area under the curve (AUC), half-life (t1/2), and central elimination rate constant (K10) were estimated. We performed a repeated-measures analysis to evaluate whether patient characteristics, disease status, concomitant immunosuppressive therapy, and immunogenicity are associated with IFX Cmin and PK parameters. RESULTS: We collected 429 Cmin measurements from 112 patients. The median of the Cmin values was 3.62 mg/L (1.47-6.02). Antibodies to IFX (ATI) were detected in 14 patients. The predicted median AUC was 28,421 mg/h/L (22,336-36,903). The median individual predicted CL, K10, and t1/2 values were 4.77 mL/kg/day (3.88-5.90), 0.09 days (0.08-0.12), and 12.22 days (9.49-14.87), respectively. IFX Cmin, AUC, CL, and K10 were significantly influenced by ATI and serum albumin concentrations. Moreover, body weight was significantly associated with AUC, CL, and K10. Patients receiving concurrent immunosuppressive therapy had higher Cmin and AUC values and lower CL and K10 values than those treated with IFX monotherapy. We also observed high intrapatient variability in Cmin values during the study period. CONCLUSIONS: In this repeated-measures study in a population of IBD patients, we observed significant associations between ATI, serum albumin concentration, concomitant immunosuppressive therapy, body weight and gender, and IFX Cmin, and CL. The high PK variability observed in this study supports the need for proactive TDM to optimize the use of IFX as early as possible in IBD patients.

A phase Ib study of sonidegib (LDE225), an oral small molecule inhibitor of smoothened or Hedgehog pathway, in combination with docetaxel in triple negative advanced breast cancer patients: GEICAM/2012-12 (EDALINE) study.

Up-regulation of the Hedgehog (Hh) pathway is implicated in the genesis of a wide range of tumors including triple negative breast cancer (TNBC). Sonidegib is a potent and selective oral inhibitor of Smo, a key component of the Hh signaling pathway. We designed a phase I clinical study to explore the combination of sonidegib plus docetaxel (fixed dose at 75 mg/m2) in advanced TNBC patients. The primary objective was to ascertain the combination's maximum tolerated dose and the recommended phase II dose (RP2D), based on dose limiting toxicities (DLTs) in the first 2 cycles. A standard "3 + 3" design was followed including three dose levels (DL) of sonidegib: 400 mg (DL1), 600 mg (DL2), and 800 mg (DL3). Twelve patients were included. Sonidegib 800 mg orally q.d. plus docetaxel 75 mg/m2 given intravenously on day 1 of 21-day cycles was established as the RP2D. No DLTs were observed at any DL. The median number of administered cycles at DL3 was 8 (range: 6 to 9). Grade 3 adverse events (AEs) at DL3 were neutropenia (66.7%), CPK increase (33.3%), leukopenia (33.3%), and paresthesia (33.3%), grade 4 AEs were not reported at this DL. At the RP2D, the combination showed antitumor activity in three out of 10 patients with measurable disease. Median time to progression for the overall study was 42.5 days (95% Confidence Interval: 29-155), and 188 days at DL3. No drug-to-drug interactions between sonidegib and docetaxel were found in the PK assessment. Trial Registration: EudraCT study number: 2013-001750-96. Study GEICAM/2012-12. TRIAL REGISTRATION: EudraCT study number: 2013-001750-96. Study GEICAM/2012-12. ClinicalTrials.gov: NCT02027376.

Therapeutic Drug Monitoring of Tacrolimus-Personalized Therapy: Second Consensus Report.

Ten years ago, a consensus report on the optimization of tacrolimus was published in this journal. In 2017, the Immunosuppressive Drugs Scientific Committee of the International Association of Therapeutic Drug Monitoring and Clinical Toxicity (IATDMCT) decided to issue an updated consensus report considering the most relevant advances in tacrolimus pharmacokinetics (PK), pharmacogenetics (PG), pharmacodynamics, and immunologic biomarkers, with the aim to provide analytical and drug-exposure recommendations to assist TDM professionals and clinicians to individualize tacrolimus TDM and treatment. The consensus is based on in-depth literature searches regarding each topic that is addressed in this document. Thirty-seven international experts in the field of TDM of tacrolimus as well as its PG and biomarkers contributed to the drafting of sections most relevant for their expertise. Whenever applicable, the quality of evidence and the strength of recommendations were graded according to a published grading guide. After iterated editing, the final version of the complete document was approved by all authors. For each category of solid organ and stem cell transplantation, the current state of PK monitoring is discussed and the specific targets of tacrolimus trough concentrations (predose sample C0) are presented for subgroups of patients along with the grading of these recommendations. In addition, tacrolimus area under the concentration-time curve determination is proposed as the best TDM option early after transplantation, at the time of immunosuppression minimization, for special populations, and specific clinical situations. For indications other than transplantation, the potentially effective tacrolimus concentrations in systemic treatment are discussed without formal grading. The importance of consistency, calibration, proficiency testing, and the requirement for standardization and need for traceability and reference materials is highlighted. The status for alternative approaches for tacrolimus TDM is presented including dried blood spots, volumetric absorptive microsampling, and the development of intracellular measurements of tacrolimus. The association between CYP3A5 genotype and tacrolimus dose requirement is consistent (Grading A I). So far, pharmacodynamic and immunologic biomarkers have not entered routine monitoring, but determination of residual nuclear factor of activated T cells-regulated gene expression supports the identification of renal transplant recipients at risk of rejection, infections, and malignancy (B II). In addition, monitoring intracellular T-cell IFN-g production can help to identify kidney and liver transplant recipients at high risk of acute rejection (B II) and select good candidates for immunosuppression minimization (B II). Although cell-free DNA seems a promising biomarker of acute donor injury and to assess the minimally effective C0 of tacrolimus, multicenter prospective interventional studies are required to better evaluate its clinical utility in solid organ transplantation. Population PK models including CYP3A5 and CYP3A4 genotypes will be considered to guide initial tacrolimus dosing. Future studies should investigate the clinical benefit of time-to-event models to better evaluate biomarkers as predictive of personal response, the risk of rejection, and graft outcome. The Expert Committee concludes that considerable advances in the different fields of tacrolimus monitoring have been achieved during this last decade. Continued efforts should focus on the opportunities to implement in clinical routine the combination of new standardized PK approaches with PG, and valid biomarkers to further personalize tacrolimus therapy and to improve long-term outcomes for treated patients.

External Evaluation of Population Pharmacokinetic Models of Infliximab in Patients With Inflammatory Bowel Disease.

BACKGROUND: Infliximab (IFX) trough levels vary markedly between patients with inflammatory bowel disease (IBD), which is important for clinical response. The aim of this study was to evaluate the performance of previously developed population pharmacokinetic models in patients with IBD for dose individualization for Crohn disease (CD) and ulcerative colitis in our clinical setting. METHODS: The authors collected 370 trough levels prospectively from 100 adult patients with IBD who were undergoing IFX treatment between July 2013 and August 2016. The external evaluation included prediction- and simulation-based diagnostics [prediction-corrected visual predictive check, prediction- and variability-corrected visual predictive check, and normalized prediction distribution error tests]. RESULTS: In prediction-based diagnostics, the authors observed a nonsignificant overall mean relative bias of -6.87% and an acceptable imprecision of 8.45%. Approximately 100% of the prediction error was within ±30%, indicating satisfactory predictability. Simulation-based diagnostics indicated model misspecification; thus, the model may not be appropriate for simulation-based applications. CONCLUSIONS: While simulation-based diagnostics provided unsatisfactory results, the prediction-based diagnostics demonstrate that the population pharmacokinetic model developed by Fasanmade et al for CD can be used to predict and design individualized IFX dose regimens that meet the individual needs of patients with CD and ulcerative colitis.

The combination of CYP3A4*22 and CYP3A5*3 single-nucleotide polymorphisms determines tacrolimus dose requirement after kidney transplantation.

INTRODUCTION: Tacrolimus (Tac) has a narrow therapeutic window and shows large between-patient pharmacokinetic variability. As a result, over-immunosuppression and under-immunosuppression are frequently encountered in daily clinical practice. Unraveling the impact of genetic polymorphisms on Tac pharmacokinetics may help to refine therapy. In this study, the associations of single-nucleotide polymorphisms (SNPs) in drug-metabolizing enzymes (CYP3A) with Tac pharmacokinetics were investigated in renal transplant recipients. PARTICIPANTS AND METHODS: In a cohort of 272 kidney transplant recipients, associations between functional genetic variants (CYP3A4*22 and CYP3A5*3) and dose-adjusted predose Tac concentrations (C0) and daily doses of Tac at days 5-7 and 15 and 1, 3, 6 and 12 months after renal transplantation were evaluated. Patients were genotyped and clustered according to both CYP3A4*22 and CYP3A5*3 allelic status: poor (PM) (CYP3A4*22 carriers with CYP3A5*3/*3), intermediate (IM) (CYP3A4*1/*1 with CYP3A5*3/*3 or CYP3A4*22 carriers with CYP3A5*1 carriers) and extensive CYP3A-metabolizers (EM) (CYP3A4*1/*1 and CYP3A5*1 carriers). RESULTS: EM had an 88% lower dose-adjusted C0 compared with IM. PM had a 26% higher dose-adjusted C0 compared with IM. The percentage of patients with supratherapeutic Tac exposure (C0>15 ng/ml) was significantly higher in PM (43.5%) compared with EM (0%) at days 5-7 after transplantation (P=0.01). About 30% of EM had subtherapeutic exposure (C0<5 ng/ml) at days 5-7 after transplantation (P=0.001). CONCLUSION: The combined CYP3A4 and CYP3A5 genotype of renal transplant recipients has a major influence on the Tac dose required to reach the target exposure.

Evaluating renal function and age as predictors of amikacin clearance in neonates: model-based analysis and optimal dosing strategies.

AIMS: We aimed to compare the performance of renal function and age as predictors of inter-individual variability (IIV) in clearance of amikacin in neonates through parallel development of population pharmacokinetic (PK) models and their associated impact on optimal dosing regimens. METHODS: Amikacin concentrations were retrospectively collected for 149 neonates receiving amikacin (post-natal age (PNA) between 4-89 days). Two population PK models were developed in parallel, considering at least as predictors current body weight (WT), in combination with either creatinine clearance (CLcr ) or age descriptors. Using stochastic simulations for both renal function or age-based dosing, we identified optimal dosing strategies that were based on attainment of optimal peak- (PCC) and trough target concentration coverage (TCC) windows associated with efficacy and toxicity. RESULTS: The CLcr and age-based population PK models both included current body weight (WT) on CL, central distribution volume and intercompartmental clearance, in combination with either CLcr or PNA as predictors for IIV of clearance (CL). The WT-CLcr model explained 6.9% more IIV in CL compared with the WT-PNA model. Both models successfully described an external dataset (n = 53) of amikacin PK. The simulation analysis of optimal dose regimens suggested similar performance of either CLcr or PNA based dosing. CONCLUSION: CLcr predicted more IIV in CL, but did not translate into clinically relevant improvements of target concentrations. Our optimized dose regimens can be considered for further evaluation to optimize initial treatment with amikacin.

Development of a population PK model of tacrolimus for adaptive dosage control in stable kidney transplant patients.

BACKGROUND: Tacrolimus pharmacokinetics (PK) presents a high variability that hampers its therapeutic use. The aims of this study are to: (1) develop a population pharmacokinetic (PPK) model for tacrolimus and to identify the factors that contribute to the variability of tacrolimus PK in renal transplant patients; and (2) to establish a new Bayesian estimator that can easily and routinely be applied in the hospital. A new PPK model may allow efficacy to be optimized, improve dose regimens, minimize side effects, and decrease the cost of extensive area under the curve (AUC) monitoring. METHODS: PPK analysis of the full PK profiles of 16 patients on 5 occasions was performed with NONMEM 7.2. Biochemical variables (hematocrit, hemoglobin, aspartate aminotransferase, and others) were analyzed. RESULTS: A 2-open-compartment model with interoccasion variability best described the PK of tacrolimus. Three transit compartments provided the best description of the absorption process. The hematocrit, aspartate aminotransferase, and alanine aminotransferase were not significant in the covariate analysis. External validation with 91 patients proved the good predictability of the model with a bias and precision of 0.37 mcg/L (CI 95%, -0.11 to 1.20 mcg/L) and 0.38 mcg/L (CI 95%, 0.02 to 1.21 mcg/L), respectively. A limited sampling strategy using 1 sampling point at predose (trough concentrations) showed a good performance in AUC0-12h estimation with a correlation between AUCfull and AUCLSS, bias and imprecision of r = 0.75, 6.78% (range, -16.26% to 30.06%) and 1.42% (IC 95%, 0.14%-3.61%), respectively. CONCLUSIONS: The PPK model developed provides reliable prior information for Bayesian adaptive control of dosage regimens of tacrolimus to achieve the desired AUC goals in stable renal transplant patients.

Pharmacokinetic modeling of enterohepatic circulation of mycophenolic acid in renal transplant recipients.

Several factors contribute to mycophenolic acid (MPA) between-patient variability. Here we characterize the metabolic pathways of MPA and quantify the effect of combining genetic polymorphism of multidrug-resistant-associated protein-2, demographics, biochemical covariates, co-medication (cyclosporine (CsA) vs. macrolides), and renal function on MPA, 7-O-MPA-glucuronide (MPAG), and acyl-glucuronide (AcMPAG) disposition, in renal transplant recipients, after mycophenolate mofetil. Complete pharmacokinetic profiles from 56 patients (five occasions) were analyzed. Enterohepatic circulation was modeled by transport of MPAG to the absorption site. This transport significantly decreased with increasing CsA trough concentrations (CtroughCsA). MPAG and AcMPAG plasma clearances significantly decreased with renal function. No significant influence of multidrug-resistant-associated protein-2 C24T single-nucleotide polymorphism was found. The model adequately predicted the increase in MPAG/AcMPAG exposures in CsA and macrolide patients with decreased renal function. This resulted in higher MPA exposures in macrolide patients versus CsA patients, and increased MPA exposures with renal function from 25 to 10 ml/min, in macrolide patients, owing to enhanced MPAG enterohepatic circulation. Lower-percentage enterohepatic circulation occurred with higher CtroughCsA and renal function values. The lack of MPA protein-binding modeling did not permit evaluation of the impact of renal function and CtroughCsA on MPA exposures in CsA patients. Thus, dose tailoring of covariates is recommended for target MPA exposure.

Optimal sparse sampling for estimating ganciclovir/valganciclovir AUC in solid organ transplant patients using NONMEN.

BACKGROUND: Ganciclovir and valganciclovir (GCV/VGCV) are used for the treatment and prophylaxis of cytomegalovirus in solid organ transplant (SOT) patients. An area under the time-concentration curve of 40-50 µg × h/mL is related to efficacy. Therapeutic drug monitoring could prevent suboptimal drug exposure and adverse events, but obtaining full concentration profiles is not feasible. Sampling optimization by developing a reliable and clinically applicable limited sampling strategy (LSS) may simplify dose adjustment. METHODS: An LSS was developed using an original pharmacokinetic (PK) data set of 40 full profiles from 20 adult SOT patients. The LSS was developed based on population and Bayesian prediction approaches. Population PK parameters from a previous model were used for simulation or as priors (NONMEM version 7.2). Median percentage of prediction error and median of absolute percentage prediction error were calculated for plasma clearance (CL) and central compartment distribution volume (V(2)). Bias and precisions were compared using 1-way analysis of variance (SPSSv19.0). RESULTS: Sampling windows were designed according to the PK profile previously observed with the entire set of data. The 4 windows selected were distributed from 0.5 to 1.5 hours, 2 to 3 hours, 4 to 5 hours, and 6 to 8 hours. Predose and concentrations beyond 8 hours were not considered in any case because simulated negative concentrations occurred in both cases. Predicted exposure using 3 sampling times (0.5-1.5, 4-5, and 6-8 hours) showed the best predictive performance, by either the population or Bayesian approaches. Bias and imprecision for CL and V(2) were 0 and 0.60%, and -0.78% and 0.78%, respectively. CONCLUSIONS: GCV/VCG area under the time-concentration curve in SOT patients could be predicted with acceptable accuracy for clinical management and dose individualization using LSS. The estimator of GCV/VGC, using 3 concentrations measured at 0.5-1.5, 4-5, and 6-8 hours after drug intake, could be used for dose adjustment.

Population pharmacokinetics of omeprazole in critically ill pediatric patients.

BACKGROUND: To develop a population pharmacokinetic model for intravenous omeprazole in critically ill children. METHODS: One hundred eighty-six omeprazole concentration-time data from 40 critically ill children were analyzed using the nonlinear mixed-effects approach with the nonlinear mixed-effects modeling software, version 7.2 software. Patients were randomized into 2 groups and received intravenous omeprazole at a dose of 0.5 or 1 mg/kg twice daily. Blood samples were drawn at 0.5, 2, 6, 12, 24, and 48 hours after the first infusion. RESULTS: The pharmacokinetic profile was best described by a 2-compartment model with a first-order elimination process. Between-patient variability could only be associated with plasma clearance (CL). The typical values for plasma CL were 24.9 L·h·70 kg (10.08%), with a distributional clearance of 53.9 L·h·70 kg (11.00%) and central and peripheral compartment distribution volumes of 4.23 L/70 kg (19.62%) and 674 L/70 kg (0.89%), respectively. Allometric size models seemed to predict changes adequately in all the pharmacokinetic parameters. High values of between-patient variability of CL [75.50% (2.60%)] and residual variability [130.0% (5.26%)] were still found in the final model. Model-based simulations suggested that the most suitable dose was 1 mg/kg because this yielded similar exposure (defined by the area under the concentration-time curve) to that obtained in adults after a 20-mg dose of omeprazole intravenously. CONCLUSIONS: An allometric size model allows changes to be predicted in all the pharmacokinetic parameters, making dose adjustment by body weight important to achieve the most effective omeprazole exposure. This is the first step toward a population pharmacokinetic study, including more data to develop a predictable model to be used during therapeutic drug monitoring.

Measurement of meropenem concentration in different human biological fluids by ultra-performance liquid chromatography-tandem mass spectrometry.

Meropenem is a broad-spectrum antibiotic, often used for the empirical treatment of infections in critically ill patients with acute kidney injury. Meropenem has clinically insignificant protein binding and, as a carbapenem antibiotic, shows time-dependent bacterial killing, meaning that the unbound or free antibiotic concentration in blood should be maintained above the minimal inhibitory concentration of the pathogen for at least 40 % of the dosing interval. We developed and validated simple chromatographic methods by ultra-performance liquid chromatography-tandem mass spectrometry to measure plasma, filtrate-dialysate, and urine concentrations of meropenem. Chromatographic separation was achieved using an Acquity(®) UPLC(®) BEH(TM) (2.1 × 100 mm id, 1.7 µm) reverse-phase C(18) column, with a water/acetonitrile linear gradient containing 0.1 % formic acid at a 0.4-mL/min flow rate. Meropenem and its internal standard (ertapenem) were detected by electrospray ionization mass spectrometry in positive ion multiple reaction monitoring mode. The limits of quantification were 0.27, 0.24, and 1.22 mg/L, and linearity was observed between 0.27-150, 0.24-150, and 1.22-2,000 mg/L for plasma, filtrate-dialysate, and urine samples, respectively. Coefficients of variation and relative biases were less than 13.5 and 8.0 % for all biological fluids. Recovery values were greater than 68.3 %. Evaluation of the matrix effect showed ion suppression for meropenem and ertapenem. No carry-over was observed. The validated methods are useful for both therapeutic drug monitoring and pharmacokinetic studies. It could be applied to daily clinical laboratory practice to measure the concentration of meropenem in plasma, filtrate-dialysate, and urine.

Pharmacokinetics of Hydroxytyrosol and Its Sulfate and Glucuronide Metabolites after the Oral Administration of Table Olives to Sprague-Dawley Rats.

The pharmacokinetics (PK) of hydroxytyrosol and its metabolites were characterized following oral administration to Sprague-Dawley rats of 3.85 and 7.70 g of destoned Arbequina table olives/kg. Plasma samples were analyzed using a fully validated method consisting of liquid extraction followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Noncompartmental PK analysis of hydroxytyrosol demonstrated linear PK between doses of 2.95 and 5.85 mg hydroxytyrosol/kg. Half-life was approximately 2.5 h, while mean residence time was around 4 h. Clearance occurred by conversion to two sulfate and two glucuronide conjugates. The area under the plasma concentration-time curve (AUC) ratios of metabolites versus parent hydroxytyrosol was approximately 7-9-fold for the sulfate and below 0.25 for the glucuronide, indicating sulfation as the predominant metabolic pathway. Despite extensive metabolism, hydroxytyrosol remained in plasma for up to 8 h with AUCs of 4293 and 8919 min·nmol/L for the doses of 3.85 and 7.70 g/kg, respectively. Therefore, table olives provide a more sustained plasma profile than other foods containing hydroxytyrosol, which may enhance its health-protecting activities.

The Effect of Polymorphisms and Other Biomarkers on Infliximab Exposure in Paediatric Inflammatory Bowel Disease: Development of a Population Pharmacokinetic Model.

BACKGROUND: Therapeutic drug monitoring (TDM) of infliximab has been shown to be a effective strategy for inflammatory bowel disease (IBD). Population pharmacokinetic (PopPK) modeling can predict trough concentrations for individualized dosing. OBJECTIVE: The aim of this study was to develop a PopPK model of infliximab in a paediatric population with IBD, assessing the effect of single nucleotide polymorphisms (SNPs) and other biomarkers on infliximab clearance. METHODS: This observational and ambispective single-centre study was conducted in paediatric patients with IBD treated with infliximab between July 2016 and July 2022 in the Paediatric Gastroenterology Service of the Hospital Universitari Vall d'Hebron (HUVH) (Spain). Demographic, clinical, and analytical variables were collected. Twenty SNPs potentially associated with variations in the response to infliximab plasma concentrations were analysed. infliximab serum concentrations and antibodies to infliximab (ATI) were determined by ELISA. PopPK modelling was performed using nonlinear mixed-effects analysis (NONMEM). RESULTS: Thirty patients (21 males) were included. The median age (range) at the start of infliximab treatment was 13 years (16 months to 16 years). A total of 190 samples were obtained for model development (49 [25.8%] during the induction phase). The pharmacokinetics (PK) of infliximab were described using a two-compartment model. Weight, erythrocyte sedimentation rate (ESR), faecal calprotectin (FC), and the SNP rs1048610 (ADAM17) showed statistical significance for clearance (CL), and albumin for inter-compartmental clearance (Q). Estimates of CL1 (genotype 1-AA), CL2 (genotype 2-AG), CL3 (genotype 3-GG), Q, Vc, and Vp (central and peripheral distribution volumes) were 0.0066 L/h/46.4 kg, 0.0055 L/h/46.4 kg, 0.0081 L/h/46.4 kg, 0.0029 L/h/46.4 kg, 0.6750 L/46.4 kg, and 1.19 L/46.4 kg, respectively. The interindividual variability (IIV) estimates for clearance, Vc, and Vp were 19.33, 16.42, and 36.02%, respectively. CONCLUSIONS: A popPK model utilising weight, albumin, FC, ESR, and the SNP rs1048610 accurately predicted infliximab trough concentrations in children with IBD.

Tools for a personalized tacrolimus dose adjustment in the follow-up of renal transplant recipients. Metabolizing phenotype according to CYP3A genetic polymorphisms versus concentration-dose ratio.

BACKGROUND AND JUSTIFICATION: The strategy of the concentration-dose (C/D) approach and the different profiles of tacrolimus (Tac) according to the cytochrome P450 polymorphisms (CYPs) focus on the metabolism of Tac and are proposed as tools for the follow-up of transplant patients. The objective of this study is to analyse both strategies to confirm whether the stratification of patients according to the pharmacokinetic behaviour of C/D corresponds to the classification according to their CYP3A4/5 cluster metabolizer profile. MATERIALS AND METHODS: 425 kidney transplant patients who received Tac as immunosuppressive treatment have been included. The concentration/dose ratio (C/D) was used to divide patients in terciles and classify them according to their Tac metabolism rate (fast, intermediate, and slow). Based on CYP3A4 and A5 polymorphisms, patients were classified into 3 metabolizer groups: fast (CYP3A5*1 carriers and CYP34A*1/*1), intermediate (CYP3A5*3/3 and CYP3A4*1/*1) and slow (CYP3A5*3/*3 and CYP3A4*22 carriers). RESULTS: When comparing patients included in each metabolizer group according to C/D ratio, 47% (65/139) of the fast metabolizers, 85% (125/146) of the intermediate and only 12% (17/140) of the slow also fitted in the homonym genotype group. Statistically lower Tac concentrations were observed in the fast metabolizers group and higher Tac concentrations in the slow metabolizers when compared with the intermediate group both in C/D ratio and polymorphisms criteria. High metabolizers required approximately 60% more Tac doses than intermediates throughout follow-up, while poor metabolizers required approximately 20% fewer doses than intermediates. Fast metabolizers classified by both criteria presented a higher percentage of times with sub-therapeutic blood Tac concentration values. CONCLUSION: Determination of the metabolizer phenotype according to CYP polymorphisms or the C/D ratio allows patients to be distinguished according to their exposure to Tac. Probably the combination of both classification criteria would be a good tool for managing Tac dosage for transplant patients.

Do drug transporter (ABCB1) SNPs and P-glycoprotein function influence cyclosporine and macrolides exposure in renal transplant patients? Results of the pharmacogenomic substudy within the symphony study.

The function of the efflux pump P-glycoprotein (Pgp) and ABCB1 single nucleotide polymorphisms (SNPs) should be considered as important tools to deepen knowledge of drug nephrotoxicity and disposition mechanisms. The aim of this study is to investigate the association of C3435T, G2677T, C1236T, and T129C ABCB1 SNPs with Pgp activity and exposure to different immunosuppressive drugs in renal transplant patients. Patients included in the Symphony Pharmacogenomic substudy were genotyped for ABCB1 SNPs. According to the design, patients were randomized into four immunosuppressive regimens: low and standard dose of cyclosporine (n = 30), tacrolimus (n = 13), and sirolimus (n = 23) concomitantly with mycophenolate and steroids. Pgp activity was evaluated in PBMC using the Rhodamine 123 efflux assay. TT carrier patients on C3435T, G2677T, and C1236T SNPs (Pgp-low pumpers) showed lower Pgp activity than noncarriers. Pgp-high pumpers treated with cyclosporine showed lower values of Pgp function than macrolides. There was a negative correlation between cyclosporine AUC and Pgp activity at 3 months. Results did not show any correlation between tacrolimus and sirolimus AUC and Pgp activity at 3 months. We found an important role of the ABCB1 SNPs Pgp function in CD3(+) peripheral blood lymphocytes from renal transplant recipients. Pgp activity was influenced by cyclosporine but not macrolides exposure.

Baricitinib Lipid-Based Nanosystems as a Topical Alternative for Atopic Dermatitis Treatment.

Atopic dermatitis (AD) is a chronic autoimmune inflammatory skin disorder which causes a significant clinical problem due to its prevalence. The ongoing treatment for AD is aimed at improving the patient's quality of life. Additionally, glucocorticoids or immunosuppressants are being used in systemic therapy. Baricitinib (BNB) is a reversible Janus-associated kinase (JAK)-inhibitor; JAK is an important kinase involved in different immune responses. We aimed at developing and evaluating new topical liposomal formulations loaded with BNB for the treatment of flare ups. Three liposomal formulations were elaborated using POPC (1-palmitoyl-2-oleoyl-glycero-3-phosphocholine), CHOL (Cholesterol) and CER (Ceramide) in different proportions: (i) POPC, (ii) POPC:CHOL (8:2, mol/mol) and (iii) POPC:CHOL:CER (3.6:2.4:4.0 mol/mol/mol). They were physiochemically characterized over time. In addition, an in vitro release study, ex vivo permeation and retention studies in altered human skin (AHS) were also performed. Histological analysis was used to study the tolerance of the formulations on the skin. Lastly, the HET-CAM test was also performed to evaluate the irritancy capacity of the formulations, and the modified Draize test was performed to evaluate the erythema and edema capacity of the formulations on the altered skin. All liposomes showed good physicochemical properties and were stable for at least one month. POPC:CHOL:CER had the highest flux and permeation, and the retention in the skin was equal to that of POPC:CHOL. The formulations exhibited no harmful or irritating effects, and the histological examination revealed no changes in structure. The three liposomes have shown promising results for the aim of the study.

In Vitro Approaches to Explore the Anticancer Potential of One Natural Flavanone and Four Derivatives Loaded in Biopolymeric Nanoparticles for Application in Topical Delivery Treatments.

The increasing number of skin cancer cases worldwide and the adverse side effects of current treatments have led to the search for new anticancer agents. In this present work, the anticancer potential of the natural flavanone 1, extracted from Eysenhardtia platycarpa, and four flavanone derivatives 1a-d obtained by different reactions from 1 was investigated by an in silico study and through cytotoxicity assays in melanoma (M21), cervical cancer (HeLa) cell lines and in a non-tumor cell line (HEK-293). The free compounds and compounds loaded in biopolymeric nanoparticles (PLGA NPs 1, 1a-d) were assayed. A structure-activity study (SAR) was performed to establish the main physicochemical characteristics that most contribute to cytotoxicity. Finally, ex vivo permeation studies were performed to assess the suitability of the flavanones for topical administration. Results revealed that most of the studied flavanones and their respective PLGA NPs inhibited cell growth depending on the concentration; 1b should be highlighted. The descriptors of the energetic factor were those that played a more important role in cellular activity. PLGA NPs demonstrated their ability to penetrate (Qp of 17.84-118.29 µg) and be retained (Qr of 0.01-1.44 g/gskin/cm2) in the skin and to exert their action for longer. The results of the study suggest that flavanones could offer many opportunities as a future anticancer topical adjuvant treatment.

Population Pharmacokinetic Analysis of Perampanel in Portuguese Patients Diagnosed with Refractory Epilepsy.

Perampanel is a promising antiepileptic drug (AED) for refractory epilepsy treatment due to its innovative mechanism of action. This study aimed to develop a population pharmacokinetic (PopPK) model to be further used in initial dose optimization of perampanel in patients diagnosed with refractory epilepsy. A total of seventy-two plasma concentrations of perampanel obtained from forty-four patients were analyzed through a population pharmacokinetic approach by means of nonlinear mixed effects modeling (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic profiles of perampanel. Interpatient variability (IPV) was entered on clearance (CL), while the residual error (RE) was modeled as proportional. The presence of enzyme-inducing AEDs (EIAEDs) and body mass index (BMI) were found as significant covariates for CL and volume of distribution (V), respectively. The mean (relative standard error) estimates for CL and V of the final model were 0.419 L/h (5.56%) and 29.50 (6.41%), respectively. IPV was 30.84% and the proportional RE was 6.44%. Internal validation demonstrated an acceptable predictive performance of the final model. A reliable population pharmacokinetic model was successfully developed, and it is the first enrolling real-life adults diagnosed with refractory epilepsy.