Tutorial: Statistical analysis and reporting of clinical pharmacokinetic studies.

Pharmacokinetics is the cornerstone of understanding drug absorption, distribution, metabolism, and elimination. It is also the key to describing variability in drug response caused by drug-drug interactions (DDIs), pharmacogenetics, impaired kidney and liver function, etc. This tutorial aims to provide a guideline and step-by-step tutorial on essential considerations when designing clinical pharmacokinetic studies and reporting results. This includes a comprehensive guide on how to conduct the statistical analysis and a complete code for the statistical software R. As an example, we created a mock dataset simulating a clinical pharmacokinetic DDI study with 12 subjects who were administered 2 mg oral midazolam with and without an inducer of cytochrome P450 3A. We provide a step-by-step guide to the statistical analysis of this clinical pharmacokinetic study, including sample size/power calculation, descriptive statistics, noncompartmental analyses, and hypothesis testing. The different analyses and parameters are described in detail, and we provide a complete R code ready to use in supplementary files. Finally, we discuss important considerations when designing and reporting clinical pharmacokinetic studies. The scope of this tutorial is not limited to DDI studies, and with minor adjustments, it applies to all types of clinical pharmacokinetic studies. This work was done by early career researchers for early career researchers. We hope this tutorial may help early career researchers when getting started on their own pharmacokinetic studies. We encourage you to use this as an inspiration and starting point and continuously evolve your statistical skills.

No significant influence of OCT1 genotypes on the pharmacokinetics of morphine in adult surgical patients.

We investigated the impact of genetic variants in OCT1 (SLC22A1) on morphine, morphine-3-glucuronide (M3G) and morphine-6-glucuronide (M6G) pharmacokinetics in adult patients scheduled for major surgery. Blood samples were taken before and 5, 10, 15, 30, 45, 60 and 90 min after a bolus of morphine (0.15 mg/kg). Patients were genotyped for the genetic variants (rs12208357, rs34059508, rs72552763 and rs34130495) in OCT1. Eighty-six patients completed the trial. The mean difference (95% confidence interval) for dose adjusted morphine, M3G and M6G AUC was 0.9 (-0.7-2.4), -5.9 (-11.8 to -0.03) and -1.1 (-2.5-0.4) h/L*10-6 , respectively, in patients with two reduced function alleles compared to patients with no reduced function alleles in OCT1. Accordingly, the (AUCM3G/Dose )/(AUCmorphine/Dose ) and (AUCM6G/Dose )/(AUCmorphine/Dose ) ratio was reduced, -1.8 (-3.2 to -0.4) and -0.4 (-0.7 to -0.03), respectively, when comparing the same groups. OCT1 variants had no influence on the experience of pain, adverse events or the number of PCA doses used. In conclusion, genetic variants in OCT1 had a small and clinically unimportant impact on the exposure of morphine after intravenous administration. Our results do not support pre-emptive genotyping for OCT1 prior to morphine administration in patients scheduled for major surgery.

Oral and intravenous pharmacokinetics of metformin with and without oral codeine intake in healthy subjects: A cross-over study.

The aim of the study was to investigate if there is a clinically relevant drug interaction between metformin and codeine. Volunteers were randomized to receive on four separate occasions: (A) orally administered metformin (1 g), (B) intravenously administered metformin (0.5 g), (C) five doses of tablet codeine 25 mg; the last dose was administered together with oral metformin (1 g), and (D) five doses of tablet codeine 25 mg; the last dose was administered together with metformin (0.5 g) intravenously. Blood samples were drawn for 24 h after administration of metformin, and for 6 h after administration of codeine and analyzed using liquid chromatography and tandem mass spectrometry. Healthy volunteers genotyped as CYP2D6 normal metabolizers (*1/*1) without known reduced function variants in the OCT1 gene (rs12208357, rs34130495, rs34059508, and rs72552763) were invited. The median absorption fraction of metformin was 0.31 and was not influenced by codeine intake. The median time to maximum concentration ( T max ) after oral intake of metformin was 2 h without, and 3 h with codeine (p = 0.06). The geometric mean ratios of the areas under the plasma concentration time-curve (AUCs) for morphine and its metabolites M3G and M6G for oral intake of metformin-to-no metformin were 1.21, 1.31, and 1.27, respectively, and for i.v. metformin-to-no metformin 1.28, 1.34, and 1.30, respectively. Concomitant oral and i.v. metformin increased the plasma levels of morphine, M3G and M6G. These small pharmacokinetic changes may well contribute to an increased risk of early discontinuation of metformin. Hence, a clinically relevant drug-drug interaction between metformin and codeine seems plausible.

Using a limited sampling strategy to investigate the interindividual pharmacokinetic variability in metformin: A large prospective trial.

AIMS: Recently a limited sampling strategy (LSS) for determination of metformin' pharmacokinetics was developed. The LSS utilizes the plasma concentration of metformin 3 and 10 hours after oral intake of a single dose to estimate the area under the concentration-time curve up to 24 hours (AUC0-24h ). The main purpose of this study was to support the feasibility of this strategy in a large prospective trial. METHODS: Volunteers orally ingested two 500-mg tablets of metformin hydrochloride. A blood sample was drawn three and ten hours after the ingestion. Urine was collected for 0-10 and 10-24 hours and urine volumes recorded. The AUC0-24h was calculated using the equation AUC0-24h = 4.779 * C3 + 13.174 * C10 . Additionally, all participants were genotyped for the single-nucleotide polymorphism A270S in OCT2, g.-66 T > C in MATE1, R61C, G465R, G401S and the deletion M420del in OCT1. RESULTS: In total, 212 healthy volunteers participated. The median (25th - 75th interquartile range) AUC0 - 24h , CLrenal , C3 and C10 , were 10 600 (8470-12 500) ng* hr* mL-1 , 29 (24-34) L* hour-1 , 1460 (1180-1770) and 260 (200-330) ng* mL-1 , respectively, which is in agreement with our previous results. GFRi was correlated with metformin AUC and CLrenal (P < .001). As expected, we found a great pharmacokinetic interindividual variability among the volunteers and no effect of the OCT1 genotype on the AUC0 - 24h . We were unable to reproduce our previous finding of a gene-gene interaction (OCT2 and MATE1) effect on CLrenal in this cohort. CONCLUSION: This study further supports the use of the 2-point LSS algorithm in large pharmacokinetic trials.

Therapeutic Drug Monitoring of Venlafaxine in an Everyday Clinical Setting: Analysis of Age, Sex and Dose Concentration Relationships.

Venlafaxine is a commonly used antidepressant agent. We aimed to provide detailed information on the associations between venlafaxine dose and concentrations of venlafaxine, by patient age and sex. From a therapeutic drug monitoring (TDM) database located at Odense University Hospital, Denmark, we identified all adults for whom the treating physician had requested clinical advice on the TDM result for venlafaxine between 2002 and 2012. We identified 1077 TDM samples of venlafaxine from 334 males and 743 females (median age 45 years), and the median daily dose was 225 mg. Median plasma concentration of venlafaxine and o-desmethylvenlafaxine (ODV) was 306 nmol/L and 861 nmol/L, respectively. The median dose-corrected serum level for venlafaxine was 1.49 nmol/L/mg., while the dose-corrected serum level of men and women were 1.21 nmol/L/mg and 1.60 nmol/L/mg, respectively. The dose-corrected sum of venlafaxine and ODV was 8.91 nmol/L/mg (IQR 6.56-12.26) versus 5.52 nmol/L/mg (IQR 4.16-7.52) for patients above 64 years and below the age of 65 years, respectively. Dose-corrected plasma concentrations of venlafaxine and ODV are increased to a clinically significant degree in patients above the age of 64, and initiation of venlafaxine therapy in the elderly should be made cautiously and supported by drug measurements.