Management of drug-drug interactions with nirmatrelvir/ritonavir in patients treated for Covid-19: Guidelines from the French Society of Pharmacology and Therapeutics (SFPT).

OBJECTIVES: Nirmatrelvir in association with ritonavir (PAXLOVID™, Pfizer) is an antiviral agent targeting the 3-chymotrypsin-like cysteine protease enzyme (3C-like protease or Mpro) which is a key enzyme of the viral cycle of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This combination with a well-known pharmacokinetic enhancer leads to a high risk for drug-drug interactions in a polymedicated elected population for treatment. The aim of this work was to provide recommendations on behalf of the national French society of pharmacology (French Society of Pharmacology and Therapeutics; SFPT), by suggesting optimal and pragmatic therapeutic strategies if nirmatrelvir/ritonavir is to be given together with drugs commonly used, in order to ensure secured physicians' prescription. METHODS: Six clinical pharmacologists search the scientific literature to provide a first draft of recommendations. Thereafter, twelve other clinical pharmacologists verified the recommendations and proposed modifications. The final draft was then validated by all 18 participants. RESULTS: Five distinct recommendations were issued: i) contra-indications, ii) "PAXLOVID™ not recommended with the comedication", iii) "PAXLOVID™ possible whether the comedication is discontinued", iv) "PAXLOVID™ possible only after an expert advice" and v) "PAXLOVID™ possible without modification of the associated treatment". The final document comprises recommendations for 171 drugs/therapeutic classes aiming to secure prescription. In complex situations, clinicians are advised to contact their pharmacology department to obtain specific recommendations on the management of drug-drug interactions with nirmatrelvir/ritonavir. CONCLUSION: These recommendations intend to be a help for clinicians willing to prescribe nirmatrelvir/ritonavir and to prevent drug-drug interactions leading to adverse drug reactions or loss of efficacy. They constitute a guideline for primary care situations. Of course, some complex situations may require expert advices and here, again, clinical pharmacologists are at the forefront in providing therapeutic advice.

A Population Pharmacokinetic Modeling Approach to Determine the Efficacy of Intravenous Amikacin in Children with Cystic Fibrosis.

BACKGROUND: In children with cystic fibrosis (CF), the currently recommended amikacin dose ranges between 30 and 35 mg/kg/d; however, data supporting this dosing efficacy are lacking. In this article, the objectives were to develop a nonparametric pharmacokinetic population model for amikacin in children with CF and investigate the efficacy and toxicity at different dose rates for distinct minimum inhibitory concentration (MIC) clinical breakpoints using Monte Carlo simulations. METHODS: Data from 94 children with CF (613 serum concentrations) from the Bordeaux University Hospital's CF-centre were analyzed. After determination of nonparametric pharmacokinetic population model parameters and associated influent covariates in Pmetrics, 1000 Monte Carlo simulations were performed for 7 different dose rates between 30 and 60 mg/kg/d, to predict the probability of obtaining peak serum amikacin ≥10 × MIC and trough level ≤2.5 mg/L, for MIC values between 1 and 16 mg/L. RESULTS: The median (min-max) age and weight were 10 (0.3-17) years and 29 (6-71) kg, respectively, with only 2 children younger than 1 year of age. Body weight and creatinine clearance significantly impacted the amikacin volume of distribution and clearance. The mean relative bias/root mean squared error between observed and individual predicted concentrations was -0.68%/8.1%. Monte Carlo simulations showed that for sensitive bacteria with MICs ≤ 4, 30 mg/kg/d was most appropriate for a 100% success rate; for bacteria with MICs ≥ 8 [eg, Pseudomonas aeruginosa (MICamikacin = 8)], a dose of at least 40 mg/kg/d allowed a high success probability (90%), with a trough level below 2.5 mg/L. CONCLUSIONS: For intermediate pathogens, a dose of at least 40 mg/kg/d can improve efficacy, with an acceptable calculated residual trough level in cases of normal or hyperfiltration. Because amikacin undergoes renal clearance, which is immature until 1 year of age, dosing recommendations for this age group may be markedly high, warranting cautious interpretation.

Population pharmacokinetics and Bayesian estimators for intravenous mycophenolate mofetil in haematopoietic stem cell transplant patients.

AIMS: Intravenous mycophenolate mofetil (IV MMF), a prodrug of mycophenolic acid (MPA), is used during nonmyeloablative and reduced-intensity conditioning haematopoetic stem cell transplantation (HCT) to improve engraftment and reduce graft-versus-host disease. The aims of this study were to develop population pharmacokinetic models and Bayesian estimators based on limited sampling strategies to allow for individual dose adjustment of intravenous mycophenolate mofetil administered by infusion in haematopoietic stem cell transplant patients. METHODS: Sixty-three MPA concentration-time profiles (median [min-max] = 6 [4-7] samples) were collected from 34 HCT recipients transplanted for 14 (1-45) days and administered IV MMF every 8 hours, concomitantly with cyclosporine. The database was split into development (75%) and validation (25%) datasets. Pharmacokinetic models characterized by a single compartment with first-order elimination, combined with two gamma distributions to describe the transformation of MMF into mycophenolic acid, were developed using in parallel nonparametric (Pmetrics) and parametric (ITSIM) approaches. The performances of the models and the derived Bayesian estimators were evaluated in the validation set. RESULTS: The best limited sampling strategy led to a bias (min, max), root mean square error between observed and modeled interdose areas under the curve in the validation dataset of -11.72% (-31.08%, 5.00%), 14.9% for ITSIM and -2.21% (-23.40%, 30.01%), 12.4% for Pmetrics with three samples collected at 0.33, 2 and 3 hours post dosing. CONCLUSION: Population pharmacokinetic models and Bayesian estimators for IV MMF in HCT have been developed and are now available online (https://pharmaco.chu-limoges.fr) for individual dose adjustment based on the interdose area under the curve.

Effect of genetic polymorphisms in CYP3A4, CYP3A5, and m-TOR on everolimus blood exposure and clinical outcomes in cancer patients.

Genetic variations in CYP3A4, CYP3A5, and m-TOR could contribute to interpatient variability regarding m-TOR inhibitors pharmacokinetics or cellular effects. The purpose of this study was to evaluate the influence of selected candidate variations in these genes on everolimus pharmacokinetics, efficacy, and toxicity in cancer patients. Thirty-four patients receiving everolimus for breast (n = 22) or renal (n = 10) cancers, or neuroendocrine tumors of pancreatic origin (n = 2) were included in the study. Six variants in genes related to everolimus pharmacokinetics (CYP3A4*22 and CYP3A5*3) or pharmacodynamics (m-TOR rs2295079, rs2295080, rs2024627 and rs1057079) were genotyped. Associations with trough concentrations (C0), dose reductions, or treatment interruptions due to toxicity and progression-free survival were investigated using generalized estimating equations and Cox models. CYP3A5 nonexpressers had significantly higher C0 as compared with expressers (ßGG vs AG = + 6.32 ± 2.22 ng/mL, p = 0.004). m-TOR rs2024627 was significantly associated with an increased risk of cancer progression studied alone or as part of an haplotype (T vs C: HR = 2.60, 95% CI [1.16-5.80], p = 0.020; CTCG vs other haplotypes HR = 2.29, 95% CI [1.06-4.95], p = 0.035, respectively). This study showed that CYP3A5 expression impacts everolimus pharmacokinetics in cancer patients and identified a genetic variation in m-TOR associated with the risk of cancer progression.

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.

Towards therapeutic drug monitoring of everolimus in cancer? Results of an exploratory study of exposure-effect relationship.

INTRODUCTION: Therapeutic drug monitoring (TDM) of everolimus is not performed in oncology and no trough level (C0) target has been yet defined. The aim of this study was to determine everolimus C0 target for toxicity and efficacy. MATERIALS AND METHODS: Clinical, biological and radiologic data from 54 patients were collected. Toxicity event was defined by termination, temporary interruption and/or dose reduction of everolimus while efficacy was defined as progression-free survival. C0 values were dichotomized by ROC curve analysis and the association between exposure and outcome was determined using Cox models for repeated events (toxicity) or Cox model censured at the first event (progression free survival). RESULTS: Among the 42 patients (77.8%) with breast cancer, 10 (18.5%) kidney cancer and 2 (3.7%) neuroendocrine cancer, adverse events were reported in 75.9% of the patients (everolimus termination in 25.9% patients). C0 everolimus higher than 26.3ng/mL (Sen=0.38,Spe=0.88) were associated with a 4-fold increased risk of toxicity (HR=4.12, IC95%=[1.48-11.5], p=0.0067) whereas C0 lower than 11.9ng/mL were associated with a 3-fold increased risk of progression (HR=3.2, IC95%=[1.33-7.81],p=0.001). DISCUSSION: Further studies are required to evaluate the everolimus C0 threshold proposed for toxicity (26.3ng/mL) and for progression (11.9ng/mL) especially with a large number of patients and more homogeneous types of cancer. However, these results are in favour of TDM for everolimus in oncology.

A candidate gene approach of the calcineurin pathway to identify variants associated with clinical outcomes in renal transplantation.

AIM: To investigate the potential influence of variants in genes involved in the calcineurin pathway on the efficacy and toxicity of calcineurin inhibitors in renal transplantation. MATERIALS & METHODS: Twenty-three polymorphisms in thirteen genes were tested in 381 renal transplant recipients receiving ciclosporin (n = 221) or tacrolimus (n = 160) and mycophenolate mofetil. Data were collected prospectively over the first year post-transplantation. RESULTS: Multivariate survival analyses revealed no genetic associations with biopsy proven acute graft rejection and serious infections. Donor-recipient Cytomegalovirus mismatch was the only variable associated with serious infection. CONCLUSION: This large exploratory study casts doubts on the potential interest of genetic biomarkers related to CNI pharmacodynamics but associations with other phenotypes in transplantation deserve further studies.

Population pharmacokinetic modelling and design of a Bayesian estimator for therapeutic drug monitoring of tacrolimus in lung transplantation.

BACKGROUND: Therapeutic drug monitoring of tacrolimus is a major support to patient management and could help improve the outcome of lung transplant recipients, by minimizing the risk of rejections and infections. However, despite the wide use of tacrolimus as part of maintenance immunosuppressive regimens after lung transplantation, little is known about its pharmacokinetics in this population. Better knowledge of the pharmacokinetics of tacrolimus in lung transplant recipients, and the development of tools dedicated to its therapeutic drug monitoring, could thus help improve their outcome. OBJECTIVES: The aims of this study were (i) to characterize the population pharmacokinetics of tacrolimus in lung transplant recipients, including the influence of biological and pharmacogenetic covariates; and (ii) to develop a Bayesian estimator of the tacrolimus area under the blood concentration-time curve from time zero to 12 hours (AUC(12)) for its therapeutic drug monitoring in lung transplant recipients. METHODS: A population pharmacokinetic model was developed by nonlinear mixed-effects modelling using NONMEM® version VI, from 182 tacrolimus full concentration-time profiles collected in 78 lung transplant recipients within the first year post-transplantation. Patient genotypes for the cytochrome P450 3A5 (CYP3A5) A6986G single nucleotide polymorphism (SNP) were characterized by TaqMan allelic discrimination. Patients were divided into an index dataset (n = 125 profiles) and a validation dataset (n = 57 profiles). A Bayesian estimator was derived from the final model using the index dataset, in order to determine the tacrolimus AUC(12) on the basis of a limited number of samples. The predictive performance of the Bayesian estimator was evaluated in the validation dataset by comparing the estimated AUC(12) with the trapezoidal AUC(12). RESULTS: Tacrolimus pharmacokinetics were described using a two-compartment model with Erlang absorption and first-order elimination. The model included cystic fibrosis (CF) and CYP3A5 polymorphism as covariates. The relative bioavailability in patients with CF was approximately 60% of the relative bioavailability observed in patients without CF, and the transfer rate constant between the transit compartments was 2-fold smaller in patients with CF than in those without CF (3.32 vs 7.06 h-1). The apparent clearance was 40% faster in CYP3A5 expressers than in non-expressers (24.5 vs 17.5 L/h). Good predictive performance was obtained with the Bayesian estimator developed using the final model and concentrations measured at 40 minutes and at 2 and 4 hours post-dose, as shown by the mean bias (1.1%, 95% CI -1.4, 3.7) and imprecision (9.8%) between the estimated and the trapezoidal AUC(12). The bias was >20% in 1.8% of patients. CONCLUSION: Population pharmacokinetic analysis showed that lung transplant patients with CF displayed lower bioavailability and a smaller transfer rate constant between transit compartments than those without CF, while the apparent clearance was faster in CYP3A5 expressers than in non-expressers. The Bayesian estimator developed in this study provides an accurate prediction of tacrolimus exposure in lung transplant patients, with and without CF, throughout the first year post-transplantation. This tool may allow routine tacrolimus dose individualization and may be used to conduct clinical trials on therapeutic drug monitoring of tacrolimus after lung transplantation.

Bayesian estimation of mycophenolate mofetil in lung transplantation, using a population pharmacokinetic model developed in kidney and lung transplant recipients.

BACKGROUND AND OBJECTIVES: The immunosuppressive drug mycophenolate mofetil is used to prevent rejection after organ transplantation. In kidney transplant recipients, it has been demonstrated that adjustment of the mycophenolate mofetil dose on the basis of the area under the concentration-time curve (AUC) of mycophenolic acid (MPA), the active moiety of mycophenolate mofetil, improves the clinical outcome. Because of the high risks of rejections and infections in lung transplant recipients, therapeutic drug monitoring of the MPA AUC might be even more useful in these patients. The aims of this study were to characterize the pharmacokinetics of MPA in lung and kidney transplant recipients, describe the differences between the two populations and develop a Bayesian estimator of the MPA AUC in lung transplant recipients. METHODS: In total, 460 MPA concentration-time profiles from 41 lung transplant recipients and 116 kidney transplant recipients were included. Nonlinear mixed-effects modelling was used to develop a population pharmacokinetic model. Patients were divided into an index dataset and a validation dataset. The pharmacokinetic model derived from the index dataset was used to develop a Bayesian estimator, which was validated using the 35 lung transplant recipients' profiles from the validation dataset. RESULTS: MPA pharmacokinetics were described using a two-compartment model with lag time, first-order absorption and first-order elimination. The influence of ciclosporin co-treatment and the changes over time post-transplantation were included in the model. Lung transplant recipients had, on average, a 53% slower absorption rate and 50% faster MPA apparent oral clearance than kidney transplant recipients (p < 0.001). In lung transplant recipients, the bioavailability was, on average, 31% lower in patients with cystic fibrosis than in patients without cystic fibrosis (p < 0.001). The Bayesian estimator developed using the population pharmacokinetic model--and taking into account ciclosporin co-treatment, cystic fibrosis and time post-transplantation, with concentrations measured at 0, 1 and 4 hours after mycophenolate mofetil dose administration--resulted in a non-significant bias and mean imprecision of 5.8 mg · h/L. This higher imprecision compared with those of similar estimators that have previously been developed in kidney transplantation might have been caused by the high MPA pharmacokinetic variability seen in the lung transplant recipients and by the fact that a large proportion of the patients did not receive ciclosporin, which reduces variability in the elimination phase of MPA by blocking its enterohepatic cycling. CONCLUSION: Lung transplant recipients have a slower MPA absorption rate and faster apparent oral clearance than kidney transplant recipients, while cystic fibrosis results in lower MPA bioavailability. A Bayesian estimator using MPA concentration-time samples at 0, 1 and 4 hours post-dose had the best predictive performance.