Simulation and Prediction of the Drug‐Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling
-
- D Zhou
- AstraZeneca Pharmaceuticals Waltham Massachusetts USA
-
- K Bui
- AstraZeneca Pharmaceuticals Waltham Massachusetts USA
-
- M Sostek
- AstraZeneca Pharmaceuticals Gaithersburg Maryland USA
-
- N Al‐Huniti
- AstraZeneca Pharmaceuticals Waltham Massachusetts USA
説明
<jats:p>Naloxegol, a peripherally acting μ‐opioid receptor antagonist for the treatment of opioid‐induced constipation, is a substrate for cytochrome P450 (CYP) 3A4/3A5 and the P‐glycoprotein (P‐gp) transporter. By integrating <jats:italic>in silico</jats:italic>, preclinical, and clinical pharmacokinetic (PK) findings, minimal and full physiologically based pharmacokinetic (PBPK) models were developed to predict the drug‐drug interaction (DDI) potential for naloxegol. The models reasonably predicted the observed changes in naloxegol exposure with ketoconazole (increase of 13.1‐fold predicted vs. 12.9‐fold observed), diltiazem (increase of 2.8‐fold predicted vs. 3.4‐fold observed), rifampin (reduction of 76% predicted vs. 89% observed), and quinidine (increase of 1.2‐fold predicted vs. 1.4‐fold observed). The moderate CYP3A4 inducer efavirenz was predicted to reduce naloxegol exposure by ∼50%, whereas weak CYP3A inhibitors were predicted to minimally affect exposure. In summary, the PBPK models reasonably estimated interactions with various CYP3A modulators and can be used to guide dosing in clinical practice when naloxegol is coadministered with such agents.</jats:p>
収録刊行物
-
- CPT: Pharmacometrics & Systems Pharmacology
-
CPT: Pharmacometrics & Systems Pharmacology 5 (5), 250-257, 2016-04-16
Wiley
