Pyridoxic Acid as Endogenous Biomarker of Renal Organic Anion Transporter Activity: Population Variability and Mechanistic Modeling to Predict Drug–Drug Interactions - Aarzoo Thakur; Sumathy Mathialagan; Emi Kimoto; Manthena V. S. Varma (CPT: Pharmacometrics & Systems Pharmacology)
ABSTRACT Pyridoxic acid (PDA) was suggested as a potential endogenous biomarker to assess in vivo renal organic anion transporter (OAT) 1 and 3 activity. Here, we first investigated the population variability in the plasma baseline levels of PDA using data from five independent studies (conducted/supported by Pfizer), and subsequently developed mechanistic physiologically based pharmacokinetic (PBPK) model to assess its effectiveness in biomarker‐informed drug–drug interaction (DDI) predictions. Meta‐analysis suggested that the inter‐individual variability in PDA plasma concentration was ~40% across all five studies (n = 71 subjects). While sex‐dependent differences were not evident, the baseline plasma PDA levels were significantly higher (38%, p < 0.05) in White males compared to Japanese males. Correspondingly, the amount of PDA excreted in urine and renal clearance were significantly higher (p < 0.05) in Japanese males (1.5‐ and 2.2‐fold, respectively), compared to White males. A PBPK model considering relative activity factor‐based scaling of in vitro transport data indicated > 80% contribution by OAT3 to the renal clearance of PDA. The baseline plasma concentrations across multiple studies were recovered by the model; and using in vitro inhibition potency data, the model predicted effect of OAT inhibitors (probenecid, ritlecitinib and tafamidis) on PDA pharmacokinetics. Furthermore, DDIs with OAT3 object drug, furosemide, were well‐predicted by the biomarker‐informed PBPK model. PDA data and the modeling approach indicated lack of clinically‐relevant OAT inhibition with ritlecitinib and tafamidis. Overall, this study presents PDA as a reliable biomarker to assess OAT3‐mediated renal DDIs with moderate inter‐subject and inter‐study variability.