Physiologically Based Pharmacokinetic Model Predictions of Panobinostat (LBH589) as a Victim and Perpetrator of Drug-Drug Interactions

Panobinostat (Farydak) is an orally active hydroxamic acid–derived histone deacetylase inhibitor used for the treatment of relapsed or refractory multiple myeloma. Based on recombinant cytochrome P450 (P450) kinetic analyses in vitro, panobinostat oxidative metabolism in human liver microsomes was mediated primarily by CYP3A4 with lower contributions by CYP2D6 and CYP2C19. Panobinostat was also an in vitro reversible and time-dependent inhibitor of CYP3A4/5 and a reversible inhibitor of CYP2D6 and CYP2C19. Based on a previous clinical drug-drug interaction study with ketoconazole (KTZ), the contribution of CYP3A4 in vivo was estimated to be ∼40%. Using clinical pharmacokinetic (PK) data from several trials, including the KTZ drug-drug interaction (DDI) study, a physiologically based pharmacokinetic (PBPK) model was built to predict panobinostat PK after single and multiple doses (within 2-fold of observed values for most trials) and the clinical DDI with KTZ (predicted and observed area under the curve ratios of 1.8). The model was then applied to predict the drug interaction with the strong CYP3A4 inducer rifampin (RIF) and the sensitive CYP3A4 substrate midazolam (MDZ) in lieu of clinical trials. Panobinostat exposure was predicted to decrease in the presence of RIF (65%) and inconsequentially increase MDZ exposure (4%). Additionally, PBPK modeling was used to examine the effects of stomach pH on the absorption of panobinostat in humans and determined that absorption of panobinostat is not expected to be affected by increases in stomach pH. The results from these studies were incorporated into the Food and Drug Administration–approved product label, providing guidance for panobinostat dosing recommendations when it is combined with other drugs.

[1]  J. Nedelman,et al.  Population pharmacokinetics of intravenous and oral panobinostat in patients with hematologic and solid tumors , 2015, European Journal of Clinical Pharmacology.

[2]  J. Verweij,et al.  Effect of ketoconazole-mediated CYP3A4 inhibition on clinical pharmacokinetics of panobinostat (LBH589), an orally active histone deacetylase inhibitor , 2011, Cancer Chemotherapy and Pharmacology.

[3]  Andy Z. X. Zhu,et al.  Utilizing In Vitro Dissolution-Permeation Chamber for the Quantitative Prediction of pH-Dependent Drug-Drug Interactions with Acid-Reducing Agents: a Comparison with Physiologically Based Pharmacokinetic Modeling , 2016, The AAPS Journal.

[4]  F. Shepherd,et al.  A clinical investigation of inhibitory effect of panobinostat on CYP2D6 substrate in patients with advanced cancer , 2013, Cancer Chemotherapy and Pharmacology.

[5]  K Rowland-Yeo,et al.  Prediction of in vivo drug clearance from in vitro data. II: Potential inter-ethnic differences , 2006, Xenobiotica; the fate of foreign compounds in biological systems.

[6]  C. Lines,et al.  Effects of the neurokinin1 receptor antagonist aprepitant on the pharmacokinetics of dexamethasone and methylprednisolone , 2003, Clinical pharmacology and therapeutics.

[7]  H. Einolf Comparison of different approaches to predict metabolic drug–drug interactions , 2007, Xenobiotica; the fate of foreign compounds in biological systems.

[8]  E. Graul,et al.  Dose-dependent pharmacokinetics of dexamethasone , 2004, European Journal of Clinical Pharmacology.

[9]  G. Rossi,et al.  Effect of netupitant, a highly selective NK1 receptor antagonist, on the pharmacokinetics of midazolam, erythromycin, and dexamethasone , 2013, Supportive Care in Cancer.

[10]  P. Jordaan,et al.  Disposition and metabolism of [14C] Sacubitril/Valsartan (formerly LCZ696) an angiotensin receptor neprilysin inhibitor, in healthy subjects , 2016, Xenobiotica; the fate of foreign compounds in biological systems.

[11]  Critique of the Two-Fold Measure of Prediction Success for Ratios: Application for the Assessment of Drug-Drug Interactions , 2011, Drug Metabolism and Disposition.

[12]  J. Holst,et al.  A double-blind placebo-controlled study on the effects of omeprazole on gut hormone secretion and gastric emptying rate. , 1997, Scandinavian journal of gastroenterology.

[13]  S. Clive,et al.  Characterizing the disposition, metabolism, and excretion of an orally active pan-deacetylase inhibitor, panobinostat, via trace radiolabeled 14C material in advanced cancer patients , 2012, Cancer Chemotherapy and Pharmacology.

[14]  Karthik Venkatakrishnan,et al.  Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions , 2007, Drug Metabolism and Disposition.

[15]  K. Morrissey,et al.  Modeling, Prediction, and in Vitro in Vivo Correlation of CYP3A4 Induction , 2008, Drug Metabolism and Disposition.

[16]  M. Hino,et al.  Panobinostat PK/PD profile in combination with bortezomib and dexamethasone in patients with relapsed and relapsed/refractory multiple myeloma , 2015, European Journal of Clinical Pharmacology.

[17]  Karly P Garnock-jones Panobinostat: First Global Approval , 2015, Drugs.

[18]  N Parrott,et al.  Physiologically based pharmacokinetic modeling in drug discovery and development: A pharmaceutical industry perspective , 2015, Clinical pharmacology and therapeutics.

[19]  B. Déprez,et al.  Hydroxamates: relationships between structure and plasma stability. , 2009, Journal of medicinal chemistry.

[20]  J. Mccafferty,et al.  Bioavailability of oral dexamethasone during high dose steroid therapy in neurological patients , 2004, European Journal of Clinical Pharmacology.

[21]  Shiew-Mei Huang,et al.  The utility of modeling and simulation in drug development and regulatory review. , 2013, Journal of pharmaceutical sciences.

[22]  P. Richardson,et al.  Phase Ib study of panobinostat and bortezomib in relapsed or relapsed and refractory multiple myeloma. , 2013, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[23]  C. Bauguess,et al.  The pharmacokinetics of single high doses of dexamethasone in cancer patients , 2006, European Journal of Clinical Pharmacology.

[24]  Mikiko Nakamura,et al.  Physiologically Based Absorption Modeling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Alectinib , 2016, The AAPS Journal.

[25]  T. Cheng,et al.  Panobinostat, a pan-histone deacetylase inhibitor: rationale for and application to treatment of multiple myeloma. , 2015, Drugs of today.

[26]  G. Shapiro,et al.  The effect of food on the bioavailability of panobinostat, an orally active pan-histone deacetylase inhibitor, in patients with advanced cancer , 2012, Cancer Chemotherapy and Pharmacology.

[27]  Vikram Sinha,et al.  Predicting the Effect of CYP3A Inducers on the Pharmacokinetics of Substrate Drugs Using Physiologically Based Pharmacokinetic (PBPK) Modeling: An Analysis of PBPK Submissions to the US FDA , 2016, Clinical Pharmacokinetics.

[28]  P. Neuvonen,et al.  The cytochrome P450 3A4 inhibitor itraconazole markedly increases the plasma concentrations of dexamethasone and enhances its adrenal‐suppressant effect , 2000, Clinical pharmacology and therapeutics.

[29]  P. Neuvonen,et al.  The effect of dexamethasone on the pharmacokinetics of triazolam. , 1998, Pharmacology & toxicology.

[30]  C. Ditzler,et al.  Bioavailability of oral dexamethasone , 1975, Clinical pharmacology and therapeutics.

[31]  L Zhang,et al.  Applications of Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation During Regulatory Review , 2011, Clinical pharmacology and therapeutics.

[32]  M. Jamei,et al.  Prediction of Drug-Drug Interactions Arising from CYP3A induction Using a Physiologically Based Dynamic Model , 2016, Drug Metabolism and Disposition.

[33]  Amin Rostami-Hodjegan,et al.  The effects of portal shunts on intestinal cytochrome P450 3A activity , 2002, Hepatology.

[34]  P. Atadja,et al.  Phase Ia/II, two-arm, open-label, dose-escalation study of oral panobinostat administered via two dosing schedules in patients with advanced hematologic malignancies , 2013, Leukemia.

[35]  M Rowland,et al.  The Role of Physiologically Based Pharmacokinetic Modeling in Regulatory Review , 2012, Clinical pharmacology and therapeutics.

[36]  M Rowland,et al.  Best Practice in the Use of Physiologically Based Pharmacokinetic Modeling and Simulation to Address Clinical Pharmacology Regulatory Questions , 2012, Clinical pharmacology and therapeutics.

[37]  Masoud Jamei,et al.  Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance , 2016, Current Pharmacology Reports.

[38]  Jingjing Yu,et al.  Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification , 2015, Drug Metabolism and Disposition.