{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:22:55Z","timestamp":1790727775041,"version":"4.1.0"},"reference-count":43,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2020,10,9]],"date-time":"2020-10-09T00:00:00Z","timestamp":1602201600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clin Pharma and Therapeutics"],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:p>Endogenous biomarkers are emerging to advance clinical drug\u2010drug interaction (DDI) risk assessment in drug development. Twelve healthy subjects received a multidrug and toxin exclusion protein (MATE) inhibitor (pyrimethamine, 10, 25, and 75\u00a0mg) in a crossover fashion to identify an appropriate endogenous biomarker to assess MATE1\/2\u2010K\u2010mediated DDI in the kidneys. Metformin (500\u00a0mg) was also given as reference probe drug for MATE1\/2\u2010K. In addition to the previously reported endogenous biomarker candidates (creatinine and <jats:italic>N<\/jats:italic><jats:sup>1<\/jats:sup>\u2010methylnicotinamide (1\u2010NMN)), <jats:italic>N<\/jats:italic><jats:sup>1<\/jats:sup>\u2010methyladenosine (m<jats:sup>1<\/jats:sup>A) was included as novel biomarkers. 1\u2010NMN and m<jats:sup>1<\/jats:sup>A presented as superior MATE1\/2\u2010K biomarkers since changes in their renal clearance (CL<jats:sub>r<\/jats:sub>) along with pyrimethamine dose were well\u2010correlated with metformin CL<jats:sub>r<\/jats:sub> changes. The CL<jats:sub>r<\/jats:sub> of creatinine was reduced by pyrimethamine, however, its changes poorly correlated with metformin CL<jats:sub>r<\/jats:sub> changes. Nonlinear regression analysis (CL<jats:sub>r<\/jats:sub> vs. mean total concentration of pyrimethamine in plasma) yielded an estimate of the inhibition constant (<jats:italic>K<jats:sub>i<\/jats:sub><\/jats:italic>) of pyrimethamine and the fraction of the clearance pathway sensitive to pyrimethamine. The <jats:italic>in vivo<\/jats:italic> <jats:italic>K<jats:sub>i<\/jats:sub><\/jats:italic> value thus obtained was further converted to unbound <jats:italic>Ki<\/jats:italic> using plasma unbound fraction of pyrimethamine, which was comparable to the <jats:italic>in vitro<\/jats:italic> <jats:italic>K<jats:sub>i<\/jats:sub><\/jats:italic> for MATE1 (1\u2010NMN) and MATE2\u2010K (1\u2010NMN and m<jats:sup>1<\/jats:sup>A). It is concluded that 1\u2010NMN and m<jats:sup>1<\/jats:sup>A CL<jats:sub>r<\/jats:sub> can be leveraged as quantitative MATE1\/2\u2010K biomarkers for DDI risk assessment in healthy volunteers.<\/jats:p>","DOI":"10.1002\/cpt.2022","type":"journal-article","created":{"date-parts":[[2020,8,31]],"date-time":"2020-08-31T18:20:00Z","timestamp":1598898000000},"page":"507-516","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Identification of Appropriate Endogenous Biomarker for Risk Assessment of Multidrug and Toxin Extrusion Protein\u2010Mediated Drug\u2010Drug Interactions in Healthy Volunteers"],"prefix":"10.1111","volume":"109","author":[{"given":"Takeshi","family":"Miyake","sequence":"first","affiliation":[{"name":"Laboratory of Molecular Pharmacokinetics Graduate School of Pharmaceutical Sciences The University of Tokyo Tokyo Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emi","family":"Kimoto","sequence":"additional","affiliation":[{"name":"ADME Sciences, Medicine Design Pfizer Inc. 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