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Background and Objective: Historically, dosing of tacrolimus is guided by therapeutic drug monitoring (TDM) of the whole blood concentration, which is strongly influenced by haematocrit. The therapeutic and adverse effects are however expected to be driven by the unbound exposure, which could be better represented by measuring plasma concentrations. Objective: We aimed to establish plasma concentration ranges reflecting whole blood concentrations within currently used target ranges. Methods: Plasma and whole blood tacrolimus concentrations were determined in samples of transplant recipients included in the TransplantLines Biobank and Cohort Study. Targeted whole blood trough concentrations are 4–6 ng/mL and 7–10 ng/mL for kidney and lung transplant recipients, respectively. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. Simulations were performed to infer plasma concentration ranges corresponding to whole blood target ranges. Results: Plasma (n = 1973) and whole blood (n = 1961) tacrolimus concentrations were determined in 1060 transplant recipients. A one-compartment model with fixed first-order absorption and estimated first-order elimination characterised observed plasma concentrations. Plasma was linked to whole blood using a saturable binding equation (maximum binding 35.7 ng/mL, 95% confidence interval (CI) 31.0–40.4 ng/mL; dissociation constant 0.24 ng/mL, 95% CI 0.19–0.29 ng/mL). Model simulations indicate that patients within the whole blood target range are expected to have plasma concentrations (95% prediction interval) of 0.06–0.26 ng/mL and 0.10–0.93 ng/mL for kidney and lung transplant recipients, respectively. Conclusion: Whole blood tacrolimus target ranges, currently used to guide TDM, were translated to plasma concentration ranges of 0.06–0.26 ng/mL and 0.10–0.93 ng/mL for kidney and lung transplant recipients, respectively. [ABSTRACT FROM AUTHOR]

Introduction: The optimal nadroparin dose in patients undergoing hemodialysis is difficult to determine in clinical practice. Anti-Xa levels ≥ 0.4 IU/mL and < 2.0 IU/mL are suggested to prevent thrombus formation within the extracorporeal circuit whilst minimizing bleeding risk. We aimed to characterize the variability in the association between dose and anti-Xa levels, identify patient and dialysis characteristics that explained this variability, and optimize nadroparin dosing based on the identified characteristics. Methods: Anti-Xa samples were collected in patients who received intravenous nadroparin as thromboprophylaxis during routine dialysis sessions. A population pharmacodynamic model was developed using non-linear mixed-effects modelling. The percentage of patients ≥ 0.4 IU/mL (efficacy) and < 2.0 IU/mL (safety) was simulated for different doses, patient and dialysis characteristics. Results: Patients (n = 137) were predominantly receiving standard hemodialysis (84.7% vs. hemodiafiltration 15.3%) and had a mean bodyweight of 76.3 kg (± 16.9). Lean body mass (LBM), mode of dialysis, and dialyzer partially explained between-subject variability in anti-Xa levels. Patients on hemodiafiltration and those receiving hemodialysis with a high LBM (≥ 80 kg) had a low probability (< 29%) of anti-Xa levels ≥ 0.4 IU/mL during the entire dialysis session. All patients, except hemodialysis patients with a low LBM (< 50 kg), had a high probability (> 70%) of peak anti-Xa levels < 2.0 IU/mL. Conclusion: Mainly patients receiving hemodiafiltration and those receiving hemodialysis with a high LBM can benefit from a higher nadroparin dose than currently used in clinical practice, while having anti-Xa levels < 2.0 IU/mL. [ABSTRACT FROM AUTHOR]

Background and Objective: Dapagliflozin, a sodium-glucose co-transporter inhibitor, was originally developed as an oral glucose-lowering drug for the treatment of type 2 diabetes mellitus. Emerging data suggest that cardiovascular and kidney benefits extend to patients without diabetes. Limited pharmacological data are, however, available in patients without diabetes. We aimed to characterise the pharmacokinetic profile of dapagliflozin in patients with chronic kidney disease without type 2 diabetes. Methods: Plasma samples were collected in a randomised, placebo-controlled, double-blind, cross-over trial (DIAMOND, NCT03190694, n = 53) that assessed the effects of 10 mg of dapagliflozin in patients with a glomerular filtration rate ≥ 25 mL/min/1.73 m2 and proteinuria > 500 mg/day. Mixed-effects models were used to develop a pharmacokinetic model and to evaluate the association between plasma exposure and response. Results: Plasma concentrations (n = 430 observations) from 48 patients (mean age 50.8 years, mean glomerular filtration rate 57.9 mL/min/1.73 m2, median proteinuria 1115 mg/24 h) were best described using a two-compartment model with first-order elimination. Apparent clearance and volume of distribution were 11.7 (95% confidence interval 10.7–12.7) L/h and 44.9 (95% confidence interval 39.0–50.9) L, respectively. Median dapagliflozin plasma exposure was 740.9 ng h/mL (2.5th–97.5th percentiles: 434.0–1615.3). Plasma exposure increased with decreasing kidney function. Every 100-ng h/mL increment in dapagliflozin plasma exposure was associated with a decrease in the urinary albumin:creatinine ratio (β = − 2.8%, p = 0.01), glomerular filtration rate (β = − 0.5 mL/min/1.73 m2, p < 0.01) and systolic blood pressure (β = − 0.4 mmHg, p = 0.03). Conclusions: The dapagliflozin plasma concentration–time profile in patients with non-diabetic kidney disease appears similar to the profile of patients with diabetic kidney disease described in the literature. Furthermore, the plasma exposure was associated with changes in risk markers for kidney disease. [ABSTRACT FROM AUTHOR]