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.

Immune checkpoint inhibitors (ICIs) have demonstrated significant clinical impact in improving overall survival of several malignancies associated with poor outcomes; however, only 20-40% of patients will show long-lasting survival. Further clarification of factors related to treatment response can support improvements in clinical outcome and guide the development of novel immune checkpoint therapies. In this article, we have provided an overview of the pharmacokinetic (PK) aspects related to current ICIs, which include target-mediated drug disposition and time-varying drug clearance. In response to the variation in treatment exposure of ICIs and the significant healthcare costs associated with these agents, arguments for both dose individualization and generalization are provided. We address important issues related to the efficacy and safety, the pharmacodynamics (PD), of ICIs, including exposure-response relationships related to clinical outcome. The unique PK and PD aspects of ICIs give rise to issues of confounding and suboptimal surrogate endpoints that complicate interpretation of exposure-response analysis. Biomarkers to identify patients benefiting from treatment with ICIs have been brought forward. However, validated biomarkers to monitor treatment response are currently lacking.

When mycophenolic acid (MPA) was originally marketed for immunosuppressive therapy, fixed doses were recommended by the manufacturer. Awareness of the potential for a more personalized dosing has led to development of methods to estimate MPA area under the curve based on the measurement of drug concentrations in only a few samples. This approach is feasible in the clinical routine and has proven successful in terms of correlation with outcome. However, the search for superior correlates has continued, and numerous studies in search of biomarkers that could better predict the perfect dosage for the individual patient have been published. As it was considered timely for an updated and

Aims The aims of this study were to describe the pharmacokinetics of tacrolimus immediately after kidney transplantation, and to develop a clinical tool for selecting the best starting dose for each patient. Methods Data on tacrolimus exposure were collected for the first 3 months following renal transplantation. A population pharmacokinetic analysis was conducted using nonlinear mixed‐effects modelling. Demographic, clinical and genetic parameters were evaluated as covariates. Results A total of 4527 tacrolimus blood samples collected from 337 kidney transplant recipients were available. Data were best described using a two‐compartment model. The mean absorption rate was 3.6 h−1, clearance was 23.0 l h–1 (39% interindividual variability, IIV), central volume of distribution was 692 l (49% IIV) and the peripheral volume of distribution 5340 l (53% IIV). Interoccasion variability was added to clearance (14%). Higher body surface area (BSA), lower serum creatinine, younger age, higher albumin and lower haematocrit levels were identified as covariates enhancing tacrolimus clearance. Cytochrome P450 (CYP) 3A5 expressers had a significantly higher tacrolimus clearance (160%), whereas CYP3A4*22 carriers had a significantly lower clearance (80%). From these significant covariates, age, BSA, CYP3A4 and CYP3A5 genotype were incorporated in a second model to individualize the tacrolimus starting dose: Dose0.25em()mg=2220.25emng0.25emnormalh0.25emml–1*0.5em22.50.25emnormall0.25emnormalh–1*[](),1.0if0.25emCYP3normalA5*3/*30.25emor0.25em(),1.62if0.25emCYP3normalA5*1/*30.25emor0.25emCYP3normalA5*1/*1*[](),1.0if0.25emCYP3normalA4*10.25emor unknown0.25emor0.25em(),0.814if0.25emCYP3normalA4*22*Age56−0.50*BSA1.930.72/1000 Both models were successfully internally and externally validated. A clinical trial was simulated to demonstrate the added value of the starting dose model. Conclusions For a good prediction of tacrolimus pharmacokinetics, age, BSA, CYP3A4 and CYP3A5 genotype are important covariates. These covariates explained 30% of the variability in CL/F. The model proved effective in calculating the optimal tacrolimus dose based on these parameters and can be used to individualize the tacrolimus dose in the early period after transplantation.

PURPOSE Tamoxifen is widely prescribed as adjuvant therapy in patients with early-stage breast cancer. It has been postulated that concentrations of endoxifen, the active metabolite of tamoxifen, are a better predictor of tamoxifen efficacy than CYP2D6 genotypes. Although in a retrospective study, an endoxifen threshold of 5.9 ng/mL for efficacy was described, confirmation based on prospective studies is lacking. The objective of the prospective CYPTAM (The Netherlands National Trial Register: NTR1509) study was to associate endoxifen concentrations and CYP2D6 genotypes with clinical outcome in patients with early-stage breast cancer receiving tamoxifen. PATIENTS AND METHODS From February 2008 to December 2010, patients with breast cancer treated with adjuvant tamoxifen were included. Patients could be enrolled up to a maximum of 12 months after tamoxifen initiation. Blood samples were retrieved for CYP2D6 genotyping and endoxifen measurements by Amplichip (Roche Diagnostics, Indianapolis, IN) and high-performance liquid chromatography–tandem mass spectrometry, respectively. Endoxifen concentrations were analyzed as a continuous variable, classifying patients into quartiles and using an endoxifen threshold of 5.9 ng/mL. Endoxifen concentrations and CYP2D6 genotypes were associated with relapse-free survival (censored at the time of tamoxifen discontinuation; RFSt) by Cox regression analysis. RESULTS A total of 667 pre- and postmenopausal patients were enrolled and had received tamoxifen for a median time of 0.37 years (range, 0.23 to 0.6 years) before study entry. No association was found between endoxifen concentrations and RFSt (adjusted hazard ratio, 0.991; 95% CI, 0.946 to 1.038; P = .691). Also, neither categorizing endoxifen concentrations into quartiles nor using 5.9 ng/mL as threshold altered these results. In addition, no association was found between CYP2D6 genotype and RFSt (adjusted hazard ratio, 0.929; 95% CI, 0.525 to 1.642; P = .799). CONCLUSION This prospective clinical study shows no association between endoxifen concentrations or CYP2D6 genotypes and clinical outcome in patients with early-stage breast cancer receiving adjuvant tamoxifen.