Philippe Pierrillas (1), Pietro Scalfaro (2), Patrice André (3) Raphaël Darteil (2), Elise Roy (2), Diane Sampson (2), Jacky Vonderscher (2), Christian Laveille (1)
(1) Calvagone, Liergues, France / (2) ENYO Pharma SA, Lyon, France / (3) Centre International de Recherche en Infectiologie (CIRI) - INSERM U1111 – CNRS UMR5308 - Université Lyon 1- ENS de Lyon
Objectives:
EYP001a is an agonist of the nuclear farnesoid X receptor (FXR) which binds bile acids. FXR agonists, originally discovered for a therapy of non-alcoholic steato-hepatitis, primary biliary cholangitis and metabolic syndrome, were found to have anti-viral activity on Hepatitis B virus (HBV) [1].
The objective of this analysis was to develop a population Pharmacokinetic-Pharmacodynamic model (PK-PD) using biomarker data to assess the influence of EYP001a on FXR pathway in both healthy volunteers and HBV infected patients.
Methods:
Data from two phase 1 studies (including a 4-arm cross-over study to evaluate the impact of food intake and a potential nycthemeral rhythm) conducted in healthy volunteers and HBV-infected patients were included in this analysis. Plasma samples from 91 individuals after single and repeated administrations of EYP001a at 7 different dose levels (from 30 to 800mg) and placebo were analysed for EYP001a and FGF19 concentrations (i.e. fibroblast growth factor 19, the intestinal protein leading to transcriptional repression of the cholesterol 7 alpha-hydroxylase (CYP7A1) and consequently reduced bile salt synthesis and whose transcription is stimulated by FXR receptor). A covariate analysis, using a stepwise approach, was performed to assess the impact of food effect, age, sex, weight-derived covariates (i.e. body mass index…) and also to investigate the potential differences between healthy volunteers and HBV infected patients.
Parameters were estimated with the First-Order Conditional Estimation method with Interaction (FOCE-I method) implemented in NONMEM 7.3 (ICON) and model development was guided by residual- and simulation-based diagnostics.
Results:
Plasma pharmacokinetics of EYP001 was best described with a 2-compartment model and an absorption phase modelled using 5 transit compartments. Bioavailability appeared to decrease after repeated administrations and to decrease as dose increases. A lower clearance was found in HBV infected patients (~25%) compared to healthy volunteers, and administration of EYP001a under fed condition decreased the absorption rate by a 2-fold factor but with a similar exposure.
FGF19 time-course in the placebo arm was modelled using a turn-over model and a Kinetic-Pharmacodynamic (K-PD) approach [2] was used to describe the increase of FGF19 production induced by meal intake. EYP001 drug effect was best described using an effect compartment [3] and a steep sigmoidal function (coefficient of sigmoïdicity>2) on the FGF19 production. No difference between HBV infected patients and healthy volunteers was detected for the pharmacodynamic part.
Model evaluation by goodness-of-fit and Visual Predictive Check, were satisfactory.
Conclusions:
EYP001a and FGF19 concentrations were adequately described by the proposed approach and confirm the impact of EYP001a on FXR pathway. This model will be expanded to other biomarkers, such as C4 concentrations (intermediate in the synthesis of bile acids from cholesterol located in the liver) and biliary acids, as they will be available.
References:
[1] Radreau, P. et al. Reciprocal regulation of farnesoid X receptor activity and hepatitis B virus replication in differentiated HepaRG cells and primary human hepatocytes. FASEB J. 30, 2016 Sep;30(9):3146-54.
[2] Jacqmin, P et al, Modelling response time profiles in the absence of drug concentrations: definition and performance evaluation of the K-PD model. J Pharmacokinet Pharmacodyn. 2007; 34(1):57-85.
[3] Sheiner, L.B. et al, Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine. Clin. Pharmacol. Ther. 1979; 25:358–371.
Reference: PAGE 27 (2018) Abstr 8475 [www.page-meeting.org/?abstract=8475]
Poster: Drug/Disease Modelling - Infection