Quantitative Prediction of Human Renal Clearance and Drug-Drug Interactions of Organic Anion Transporter Substrates Using In Vitro Transport Data: A Relative Activity Factor Approach

Mathialagan, Sumathy; Piotrowski, Mary A.; Tess, David A.; Feng, Bo; Litchfield, John; Varma, Manthena V.

doi:10.1124/dmd.116.074294

Cited by 128Drug Transport and Resistance MechanismsPharmacogenetics and Drug MetabolismComputational Drug Discovery Methods

Quantitative Prediction of Human Renal Clearance and Drug-Drug Interactions of Organic Anion Transporter Substrates Using In Vitro Transport Data: A Relative Activity Factor Approach

Mathialagan, Sumathy, Piotrowski, Mary A., Tess, David A., Feng, Bo, Litchfield, John, Varma, Manthena V.·2017·Drug Metabolism and Disposition

DOI 10.1124/dmd.116.074294

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Abstract

Organic anion transporters (OATs) are important in the renal secretion, and thus, the clearance, of many drugs; and their functional change can result in pharmacokinetic variability. In this study, we applied transport rates measured in vitro using OAT-transfected human embryonic kidney cells to predict human renal secretory and total renal clearance of 31 diverse drugs. Selective substrates to OAT1 (tenofovir), OAT2 (acyclovir and ganciclovir), and OAT3 (benzylpenicillin, oseltamivir acid) were used to obtain relative activity factors (RAFs) for these individual transporters by relating in vitro transport clearance (after physiologic scaling) to in vivo secretory clearance. Using the estimated RAFs (0.64, 7.3, and 4.1, respectively, for OAT1, OAT2, and OAT3, respectively) and the in vitro active clearances, renal secretory clearance and total renal clearance were predicted with average fold errors (AFEs) of 1.89 and 1.40, respectively. The results show that OAT3-mediated transport play a predominant role in renal secretion for 22 of the 31 drugs evaluated. This mechanistic static approach was further applied to quantitatively predict renal drug-drug interactions (AFE ∼1.6) of the substrate drugs with probenecid, a clinical probe OAT inhibitor. In conclusion, the proposed in vitro-in vivo extrapolation approach is the first comprehensive attempt toward mechanistic modeling of renal secretory clearance based on routinely employed in vitro cell models.

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Measurements in OAT-transfected HEK cells successfully predicted renal clearance of 31 diverse drugs.
“For renal secretion, measurements in organic anion transporter-transfected human embryonic kidney cells successfully predicted renal clearance of 31 diverse drugs [42] while a mechanistic model for passive tubular reabsorption was verified with a large dataset of drugs [43].”
From Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies (2019) · cites this paper as [42]

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Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies
Miller, N. A., Reddy, M. B., Heikkinen, A. T., Lukacova, V., & Parrott, N. (2019) · Clinical Pharmacokinetics · doi:10.1007/s40262-019-00741-9 · Cited by 142 · see citing works

Authors: Mathialagan, S., Piotrowski, M. A., Tess, D. A., Feng, B., Litchfield, J., & Varma, M. V.
Affiliations: Pfizer (United States) (US)
ORCID: Mathialagan, Sumathy
Tess, David A.
Feng, Bo
Varma, Manthena V.
Venue: Drug Metabolism and Disposition
Publisher: Elsevier BV
Published: 2017-04
Volume: 45
Issue: 4
Pages: 409-417
ISSN: 0090-9556 (ISSN-L)
DOI: 10.1124/dmd.116.074294
OpenAlex: W2586590687
Cited by: 128
References: 46
Citations by year: 2026: 4 · 2025: 15 · 2024: 11 · 2023: 14 · 2022: 24 · 2021: 17 · 2020: 11 · 2019: 15 · 2018: 14 · 2017: 2 · 2013: 1
FWCI: 5.06
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Drug Metabolism and Disposition (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Keywords: organic anion transporters, renal clearance, drug-drug interactions, in vitro-in vivo extrapolation, renal secretion, OAT1, OAT2, OAT3, probenecid, tenofovir, acyclovir, ganciclovir, penicillin G, oseltamivir, human embryonic kidney cells, pharmacokinetic variability
MeSH terms: Tenofovir, Acyclovir, Anti-Bacterial Agents, Antiviral Agents, Drug Interactions, Humans, Kidney, Models, Biological, Penicillin G, Probenecid, Transfection, Ganciclovir, Organic Anion Transport Protein 1, Organic Anion Transporters, Sodium-Independent, Oseltamivir, HEK293 Cells, Renal Elimination

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Quantitative Prediction of Human Renal Clearance and Drug-Drug Interactions of Organic Anion Transporter Substrates Using In Vitro Transport Data: A Relative Activity Factor Approach

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