BACKGROUND: Dose modification of renally secreted drugs in patients with chronic kidney disease (CKD) has relied on serum creatinine concentration as a biomarker to estimate glomerular filtration (GFR) under the assumption that filtration and secretion decline in parallel. A discrepancy between actual renal clearance and predicted renal clearance based on GFR alone is observed in severe CKD patients with tenofovir, a compound secreted by renal OAT1/3. Uremic solutes that inhibit OAT1/3 may play a role in this divergence. METHODS: To examine the impact of transporter inhibition by uremic solutes on tenofovir renal clearance, we determined the inhibitory potential of uremic solutes hippuric acid, indoxyl sulfate, and p-cresol sulfate. The inhibition parameters (IC(50)) were incorporated into a previously validated mechanistic kidney model; simulated renal clearance and plasma PK profile were compared to data from clinical studies. RESULTS: Without the incorporation of uremic solute inhibition, the PBPK model failed to capture the observed data with an absolute average fold error (AAFE)â>â2. However, when the inhibition of renal uptake transporters and uptake transporters in the slow distribution tissues were included, the AAFE value was within the pre-defined twofold model acceptance criterion, demonstrating successful model extrapolation to CKD patients. CONCLUSION: A PBPK model that incorporates inhibition by uremic solutes has potential to better predict renal clearance and systemic disposition of secreted drugs in patients with CKD. Ongoing research is warranted to determine if the model can be expanded to include other OAT1/3 substrate drugs and to evaluate how these findings can be translated to clinical guidance for drug selection and dose optimization in patients with CKD.
Incorporating Uremic Solute-mediated Inhibition of OAT1/3 Improves PBPK Prediction of Tenofovir Renal and Systemic Disposition in Patients with Severe Kidney Disease.
将尿毒症溶质介导的 OAT1/3 抑制纳入 PBPK 预测,可改善重度肾病患者替诺福韦肾脏和全身分布情况
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作者:Chang Shih-Yu, Huang Weize, Chapron Alenka, Quiñones Antonio J López, Wang Joanne, Isoherranen Nina, Shen Danny D, Kelly Edward J, Himmelfarb Jonathan, Yeung Catherine K
| 期刊: | Pharmaceutical Research | 影响因子: | 4.300 |
| 时间: | 2023 | 起止号: | 2023 Nov;40(11):2597-2606 |
| doi: | 10.1007/s11095-023-03594-x | 研究方向: | 信号转导 |
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