Physiologically-based pharmacokinetic modelling to predict oprozomib CYP3A drug-drug interaction potential in patients with advanced malignancies.

Ying Ou, Yang Xu, Lia Gore, R Donald Harvey, Alain Mita, Kyriakos P Papadopoulos, Zhengping Wang, Richard E Cutler, Dawn E Pinchasik, Apostolia M Tsimberidou

British journal of clinical pharmacology 2019 Mar

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Oprozomib is an oral, second-generation, irreversible proteasome inhibitor currently in clinical development for haematologic malignancies, including multiple myeloma and other malignancies. Oprozomib is a rare example of a small molecule drug that demonstrates cytochrome P450 (CYP) mRNA suppression. This unusual property elicits uncertainty regarding the optimal approach for predicting its drug-drug interaction (DDI) risk. The current study aims to understand DDI potential during early clinical development of oprozomib. To support early development of oprozomib (e.g. inclusion/exclusion criteria, combination study design), we used human hepatocyte data and physiologically-based pharmacokinetic (PBPK) modelling to predict its CYP3A4-mediated DDI potential. Subsequently, a clinical DDI study using midazolam as the substrate was conducted in patients with advanced malignancies. The clinical DDI study enrolled a total of 21 patients, 18 with advanced solid tumours. No patient discontinued oprozomib due to a treatment-related adverse event. The PBPK model prospectively predicted oprozomib 300 mg would not cause a clinically relevant change in exposure to CYP3A4 substrates (≤30%), which was confirmed by the results of this clinical DDI study. These results indicate oprozomib has a low potential to inhibit the metabolism of CYP3A4 substrates in humans. The study shows that cultured human hepatocytes are a more reliable system for DDI prediction than human liver microsomes for studying this class of compounds. Developing a PBPK model prior to a clinical DDI study has been valuable in supporting clinical development of oprozomib. © 2018 The British Pharmacological Society.

Citation

Ying Ou, Yang Xu, Lia Gore, R Donald Harvey, Alain Mita, Kyriakos P Papadopoulos, Zhengping Wang, Richard E Cutler, Dawn E Pinchasik, Apostolia M Tsimberidou. Physiologically-based pharmacokinetic modelling to predict oprozomib CYP3A drug-drug interaction potential in patients with advanced malignancies. British journal of clinical pharmacology. 2019 Mar;85(3):530-539