Physiologically Based Pharmacokinetic Modeling for Predicting the Effect of Intrinsic and Extrinsic Factors on Darunavir or Lopinavir Exposure Coadministered With Ritonavir

Abstract

Management of comorbidities and medications is complex in HIV-1 infected patients. The overall objective of this project was to develop separate physiologically-based pharmacokinetic (PBPK) substrate models for the protease inhibitors darunavir and lopinavir. These protease inhibitors are used in the treatment of HIV infection. Both darunavir and lopinavir are coadministered with another medication that inhibits cytochrome (CYP) 3A. The current project focused on PBPK modeling for darunavir and lopinavir coadministered with ritonavir. Darunavir and lopinavir PBPK models that accounted for ritonavir CYP3A inhibition effects (linked PBPK models) were developed. The linked PBPK models were then used to predict the effect on darunavir or lopinavir exposure from CYP modulators. In the next step, the predicted effect of hepatic impairment was evaluated. Additional exploratory analyses predicted CYP3A inhibition effects on darunavir or lopinavir exposure in simulated hepatically impaired subjects. The linked PBPK models reasonably predict darunavir or lopinavir exposure based on simulations with CYP inhibitors or inducers. Exploratory simulations using the linked darunavir or lopinavir PBPK models indicate CYP3A inhibition may further increase darunavir or lopinavir exposure in patients with hepatic impairment.

Inhibition and induction of CYP enzymes in humans: an update

“… No significant in vitro Cattaneo et al ( 2019 ), Sherman et al ( 2015 ), Tseng et al ( 2017 ) Ritonavir E: > 50% M: 3A4, 2D6 (minor) Strong 3A4 inhibitors ketoconazole (minor) Strong 3A4 inducers rifampicin (moderate) 3A4 (mechanism-based), 2D6, 2C9 3A4-, 2D6- and 2C9-substrates variable effects 1A2, 2B6, 2C8, 2C9, 2C19 in vitro; in vivo minor or moderate effects Cattaneo et al ( 2019 ), Cooper et al ( 2003 ), Tseng et al ( 2017 ) Protease inhibitors Atazanavir (+cobicistat) M: 3A4 Strong 3A4 inducers rifampicin (strong) Efavirenz (moderate) 3A4 (mechanism-based), 2C8 (weak) 3A4 substrates (from weak to strong) No effect in vitro or in vivo Tseng et al ( 2017 ) Darunavir (+ritonavir) M: 3A4, 2D6 3A4-inducers and inhibitors (variable observed or predicted effects) 3A4, 2D6 3A4 substrates (from weak to moderate) 2C9? warfarin Tseng et al ( 2017 ), Wagner et al ( 2017 ) Fosamprenavir (amprenavir) (+ritonavir) M: 3A4 3A4-inducers and inhibitors (variable observed or predicted effects) 3A4 3A4 substrates (from weak to moderate) 3A4; in vivo effect minor or moderate Justesen et al ( 2003 ), Sale et al ( 2002 ), Tran et al ( 2002 ) Lopinavir (+ritonavir) M: 3A4 3A4-inducers and inhibitors (variable observed or predicted effects) 3A4 3A4 substrates (from weak to moderate) …”

Verification of a physiologically based pharmacokinetic model of ritonavir to estimate drug–drug interaction potential of CYP3A4 substrates

“…Some PBPK models for ritonavir, i.e. established to predict systemic exposure changes of CYP3A4 substrates as antiretroviral and antineoplastic drugs (Moltó et al, ; Wagner et al, ), under‐predict the DDI effect with the probe substrate midazolam by comparison with the clinical observations (Greenblatt et al, ).…”

Effect of Hepatic Impairment on the Pharmacokinetics of Alectinib

“…PBPK modeling has been applied to provide mechanistic insights underlying absorption‐ or disposition‐related variability or even to support dosing recommendations in settings of drug‐drug interactions (DDIs) or in specific populations including pediatrics, geriatrics, and pregnancy . Use of PBPK to predict the effects of organ dysfunction has also been described and is currently an area of much investigation …”