The kidney plays a vital role in the body's defense against potentially toxic xenobiotics and metabolic waste products through elimination pathways. In particular, secretory transporters in the proximal tubule are major determinants of the disposition of xenobiotics, including many prescription drugs. In the past decade, considerable progress has been made in understanding the impact of renal transporters on the disposition of many clinically used drugs. In addition, renal transporters have been implicated as sites for numerous clinically important drug-drug interactions. This review begins with a description of renal drug handling and presents relevant equations for the calculation of renal clearance, including filtration and secretory clearance. In addition, data on the localization, expression, substrates, and inhibitors of renal drug transporters are tabulated. The recent US Food and Drug Administration drug-drug interaction draft guidance as it pertains to the study of renal drug transporters is presented. Renal drug elimination in special populations and transporter splicing variants are also described.

This white paper provides updated International Transporter Consortium (ITC) recommendations on transporters that are important in drug development following the 3 ITC workshop. New additions include prospective evaluation of organic cation transporter 1 (OCT1) and retrospective evaluation of organic anion transporting polypeptide (OATP)2B1 because of their important roles in drug absorption, disposition, and effects. For the first time, the ITC underscores the importance of transporters involved in drug-induced vitamin deficiency (THTR2) and those involved in the disposition of biomarkers of organ function (OAT2 and bile acid transporters).

Interindividual variation in response to metformin, first-line therapy for type 2 diabetes, is substantial. Given that transporters are determinants of metformin pharmacokinetics, we examined the effects of promoter variants in both multidrug and toxin extrusion protein 1 (MATE1) (g.−66T→C, rs2252281) and MATE2 (g.−130G→A, rs12943590) on variation in metformin disposition and response. The pharmacokinetics and glucose-lowering effects of metformin were assessed in healthy volunteers (n = 57) receiving metformin. The renal and secretory clearances of metformin were higher (22% and 26%, respectively) in carriers of variant MATE2 who were also MATE1 reference (P < 0.05). Both MATE genotypes were associated with altered post-metformin glucose tolerance, with variant carriers of MATE1 and MATE2 having an enhanced (P < 0.01) and reduced (P < 0.05) response, respectively. Consistent with these results, patients with diabetes (n = 145) carrying the MATE1 variant showed enhanced metformin response. These findings suggest that promoter variants of MATE1 and MATE2 are important determinants of metformin disposition and response in healthy volunteers and diabetic patients.

Allopurinol is the drug most widely used to lower the blood concentrations of urate and, therefore, to decrease the number of repeated attacks of gout. Allopurinol is rapidly and extensively metabolised to oxypurinol (oxipurinol), and the hypouricaemic efficacy of allopurinol is due very largely to this metabolite. The pharmacokinetic parameters of allopurinol after oral dosage include oral bioavailability of 79 +/- 20% (mean +/- SD), an elimination half-life (t((1/2))) of 1.2 +/- 0.3 hours, apparent oral clearance (CL/F) of 15.8 +/- 5.2 mL/min/kg and an apparent volume of distribution after oral administration (V(d)/F) of 1.31 +/- 0.41 L/kg. Assuming that 90 mg of oxypurinol is formed from every 100mg of allopurinol, the pharmacokinetic parameters of oxypurinol in subjects with normal renal function are a t((1/2)) of 23.3 +/- 6.0 hours, CL/F of 0.31 +/- 0.07 mL/min/kg, V(d)/F of 0.59 +/- 0.16 L/kg, and renal clearance (CL(R)) relative to creatinine clearance of 0.19 +/- 0.06. Oxypurinol is cleared almost entirely by urinary excretion and, for many years, it has been recommended that the dosage of allopurinol should be reduced in renal impairment. A reduced initial target dosage in renal impairment is still reasonable, but recent data on the toxicity of allopurinol indicate that the dosage may be increased above the present guidelines if the reduction in plasma urate concentrations is inadequate. Measurement of plasma concentrations of oxypurinol in selected patients, particularly those with renal impairment, may help to decrease the risk of toxicity and improve the hypouricaemic response. Monitoring of plasma concentrations of oxypurinol should also help to identify patients with poor adherence. Uricosuric drugs, such as probenecid, have potentially opposing effects on the hypouricaemic efficacy of allopurinol. Their uricosuric effect lowers the plasma concentrations of urate; however, they increase the CL(R) of oxypurinol, thus potentially decreasing the influence of allopurinol. The net effect is an increased degree of hypouricaemia, but the interaction is probably limited to patients with normal renal function or only moderate impairment.

Impaired renal function and increased plasma levels of oxypurinol and granulysin correlated with the poor prognosis of allopurinol-SCAR. Allopurinol prescription is suggested to be avoided in subjects with renal insufficiency and HLA-B*58:01 carriers. An early intervention to increase the clearance of plasma oxypurinol may improve the prognosis of allopurinol-SCAR.

Objectives: Vancomycin is a vital treatment option for patients suffering from critical infections, and therapeutic drug monitoring is recommended. Bayesian forecasting is reported to improve trough concentration monitoring for dose adjustment. However, the predictive performance of pharmacokinetic models that are utilized for Bayesian forecasting has not been systematically evaluated. Method: Thirty-one published population pharmacokinetic models for vancomycin were encoded in NONMEM ® 7.4. Data from 292 hospitalized patients were used to evaluate the predictive performance (forecasting bias and precision, visual predictive checks) of the models to forecast vancomycin concentrations and area under the curve (AUC) by (a) a priori prediction, i.e., solely by patient characteristics, and (b) also including measured vancomycin concentrations from previous dosing occasions using Bayesian forecasting. Results: A priori prediction varied substantiallydrelative bias (rBias): e122.7e67.96%, relative root mean squared error (rRMSE) 44.3e136.8%, respectivelydand was best for models which included body weight and creatinine clearance as covariates. The model by Goti et al. displayed the best predictive performance with an rBias of e4.41% and an rRMSE of 44.3%, as well as the most accurate visual predictive checks and AUC predictions. Models with less accurate predictive performance provided distorted AUC predictions which may lead to inappropriate dosing decisions. Conclusion: There is a diverse landscape of population pharmacokinetic models for vancomycin with varied predictive performance in Bayesian forecasting. Our study revealed the Goti model as suitable for improving precision dosing in hospitalized patients. Therefore, it should be used to drive vancomycin dosing decisions, and studies to link this finding to clinical outcomes are warranted.

Kidney disease is an increasingly common comorbidity that alters the pharmacokinetics of many drugs. Prescribing to patients with kidney disease requires knowledge about the drug, the extent of the patient's altered physiology, and pharmacokinetic principles that influence the design of dosing regimens. There are multiple physiologic effects of impaired kidney function, and the extent to which they occur in an individual at any given time can be difficult to define. Although some guidelines are available for dosing in kidney disease, they may be on the basis of limited data or not widely applicable, and therefore, an understanding of pharmacokinetic principles and how to apply them is important to the practicing clinician. Whether kidney disease is acute or chronic, drug clearance decreases, and the volume of distribution may remain the same or increase. Although in CKD, these changes progress relatively slowly, they are dynamic in AKI, and recovery is possible depending on the etiology and treatments. This, and the use of kidney replacement therapies further complicate attempts to quantify drug clearance at the time of prescribing and dosing in AKI. The required change in the dosing regimen can be estimated or even quantitated in certain instances through the application of pharmacokinetic principles to guide rational drug dosing. This offers an opportunity to provide personalized medical care and minimizes adverse drug events from either under- or overdosing. We discuss the principles of pharmacokinetics that are fundamental for the design of an appropriate dosing regimen in this review.

Metformin, the most widely prescribed antidiabetic drug, requires transporters to enter tissues involved in its pharmacologic action, including liver, kidney, and peripheral tissues. Organic cation transporter 3 (OCT3, SLC22A3), expressed ubiquitously, transports metformin, but its in vivo role in metformin response is not known. Using Oct3 knockout mice, the role of the transporter in metformin pharmacokinetics and pharmacodynamics was determined. After an intravenous dose of metformin, a 2-fold decrease in the apparent volume of distribution and clearance was observed in knockout compared with wild-type mice (P , 0.001), indicating an important role of OCT3 in tissue distribution and elimination of the drug. After oral doses, a significantly lower bioavailability was observed in knockout compared with wild-type mice (0.27 versus 0.58, P , 0.001). Importantly, metformin's effect on the plasma glucose concentration-time curve was reduced in knockout compared with wild-type mice (12 versus 30% reduction, respectively, P , 0.05) along with its accumulation in skeletal muscle and adipose tissue (P , 0.05). Furthermore, the effect of metformin on phosphorylation of AMP activated protein kinase, and expression of glucose transporter type 4 was absent in the adipose tissue of Oct3 2/2 mice. Additional analysis revealed that an OCT3 39 untranslated region variant was associated with reduced activity in luciferase assays and reduced response to metformin in 57 healthy volunteers. These findings suggest that OCT3 plays an important role in the absorption and elimination of metformin and that the transporter is a critical determinant of metformin bioavailability, clearance, and pharmacologic action.