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The human microbiome is associated with human health and disease. Exogenous compounds, including pharmaceutical products, are also known to be affected by the microbiome, and this discovery has led to the field of pharmacomicobiomics. The microbiome can also alter drug pharmacokinetics and pharmacodynamics, possibly resulting in side effects, toxicities, and unanticipated disease response. Microbiome-mediated effects are referred to as drug-microbiome interactions (DMI). Rapid advances in the field of pharmacomicrobiomics have been driven by the availability of efficient bacterial genome sequencing methods and new computational and bioinformatics tools. The success of fecal microbiota transplantation for recurrent Clostridioides difficile has fueled enthusiasm and research in the field. This review focuses on the pharmacomicrobiome in transplantation. Alterations in the microbiome in transplant recipients are well documented, largely because of prophylactic antibiotic use, and the potential for DMI is high. There is evidence that the gut microbiome may alter the pharmacokinetic disposition of tacrolimus and result in microbiome-specific tacrolimus metabolites. The gut microbiome also impacts the enterohepatic recirculation of mycophenolate, resulting in substantial changes in pharmacokinetic disposition and systemic exposure. The mechanisms of these DMI and the specific bacteria or communities of bacteria are under investigation. There are little or no human DMI data for cyclosporine A, corticosteroids, and sirolimus. The available evidence in transplantation is limited and driven by small studies of heterogeneous designs. Larger clinical studies are needed, but the potential for future clinical application of the pharmacomicrobiome in avoiding poor outcomes is high., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

African American (AA) kidney transplant recipients (KTRs) have poor outcomes, which may in-part be due to tacrolimus (TAC) sub-optimal immunosuppression. We previously determined the common genetic regulators of TAC pharmacokinetics in AAs which were CYP3A5 *3, *6, and *7. To identify low-frequency variants that impact TAC pharmacokinetics, we used extreme phenotype sampling and compared individuals with extreme high (n = 58) and low (n = 60) TAC troughs (N = 515 AA KTRs). Targeted next generation sequencing was conducted in these two groups. Median TAC troughs in the high group were 7.7 ng/ml compared with 6.3 ng/ml in the low group, despite lower daily doses of 5 versus 12 mg, respectively. Of 34,542 identified variants across 99 genes, 1406 variants were suggestively associated with TAC troughs in univariate models (p-value < 0.05), however none were significant after multiple testing correction. We suggest future studies investigate additional sources of TAC pharmacokinetic variability such as drug-drug-gene interactions and pharmacomicrobiome., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

The transplantation of organ(s) across species may alleviate the shortage of available donor kidneys for an ever-growing number of patients on transplant waiting lists. However, this potential remains limited by uncharacterized physiologic and immune effects of xenotransplants in recipients, which Pan et al. 1 investigated in the current study., Competing Interests: Declaration of interests A.K.I. has served on an advisory board for Avera Pharmaceuticals and Novartis, receives consulting fees from the Medical Review Institute of America, and has family members that are employees of Novartis pharmaceutical company, all of which are unrelated to this work., (Copyright © 2024. Published by Elsevier Inc.)

Background: Therapeutic drug monitoring for mycophenolic acid (MPA) is challenging due to difficulties in measuring the area under the curve (AUC). Limited sampling strategies (LSSs) have been developed for MPA therapeutic drug monitoring but come with risk of unacceptable performance. The authors hypothesized that the poor predictive performance of LSSs were due to the variability in MPA enterohepatic recirculation (EHR). This study is the first to evaluate LSSs models performance in the context of EHR., Methods: Adult kidney transplant recipients (n = 84) receiving oral mycophenolate mofetil underwent intensive MPA pharmacokinetic sampling. MPA AUC0-12hr and EHR were determined. Published MPA LSSs in kidney transplant recipients receiving tacrolimus were evaluated for their predictive performance in estimating AUC0-12hr in our full cohort and separately in individuals with high and low EHR., Results: None of the evaluated LSS models (n = 12) showed good precision or accuracy in predicting MPA AUC0-12hr in the full cohort. In the high EHR group, models with late timepoints had better accuracy but low precision, except for 1 model with late timepoints at 6 and 10 hours postdose, which had marginally acceptable precision. For all models, the good guess of predicted AUC0-12hr (±15% of observed AUC0-12hr) was highly variable (range, full cohort = 19%-61.9%; high EHR = 4.5%-65.9%; low EHR = 27.5%-62.5%)., Conclusions: The predictive performance of the LSS models varied according to EHR status. Timepoints ≥5 hours postdose in LSS models are essential to capture EHR. Models and strategies that incorporate EHR during development are required to accurately ascertain MPA exposure., Competing Interests: The authors declare no conflict of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Kidney transplant recipients carrying the CYP3A5*1 allele have lower tacrolimus troughs, and higher dose requirements compared to those with the CYP3A5*3/*3 genotype. However, data on the effect of CYP3A5 alleles on post-transplant tacrolimus management are lacking. The effect of CYP3A5 metabolism phenotypes on the number of tacrolimus dose adjustments and troughs in the first 6 months post-transplant was evaluated in 78 recipients (64% Caucasians). Time to first therapeutic concentration, percentage of time in therapeutic range (TTR), and estimated glomerular filtration rate (eGFR) were also evaluated. Fifty-five kidney transplant recipients were CYP3A5 poor metabolizers (PM), 17 were intermediate metabolizers (IM), and 6 were extensive metabolizers (EM). Compared to PMs, EMs/IMs had significantly more dose adjustments (6.1 vs. 8.1, p = .015). Overall, 33.82% of trough measurements resulted in a dose change. There was no difference in the number of tacrolimus trough measurements between PMs and EM/IMs. The total daily tacrolimus dose requirements were higher in EMs and IMs compared to PMs (<.001). TTR was ∼50% in the PMs and EMs/IMs groups. CYP3A5 EM/IM metabolizers have more tacrolimus dose changes and higher dose requirements which increases clinical management complexity. Larger studies are needed to assess the cost and benefits of including genotyping data to improve clinical management., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)