Ricardo Diaz de Leon Ortega (1), Ajay Saxena (2), Jonathan Brown (3), Dannielle Ravenhill (1), Kevser Sevim (1), Zoe Kane (1)
(1) Quotient Sciences, UK, (2) Bristol Myers Squibb, USA, (3) Bristol Myers Squibb, UK
Introduction: Compound A is highly soluble at physiological pH, highly bound to proteins (%PPB >99.9%) and has poor permeability (Caco-2 Papp < 1 nm/s). In dog, the volume of distribution is low (50 mL/kg), clearance is 0.835 mL/h/kg and a mono-exponential decline in plasma concentration is observed. In clinical trials, compound A is administered subcutaneously, thus, to improve patience compliance, a solid oral dosage form of compound A was developed. Due to its negligible intestinal permeability, the permeability enhancer Salcaprozate sodium (SNAC) was incorporated into the formulation. One mechanism proposed to explain the action of permeability enhancers is the transient opening of intestinal tight junctions (during a time window of ~20 minutes), leading to a temporary increase of paracellular permeability [1].
Objectives: The objective of this work was to develop a PBPK model for the oral administration of compound A in dogs, focusing on the alteration of paracellular permeability caused by SNAC.
Methods: A PBPK model for compound A was developed and verified in PKSim v10 (Open Systems Pharmacology [2]) using dog plasma concentration profiles (Cp-t), comprising intravenous (IV) bolus dosing (1 mg/kg) and oral administration of two enteric coated tablets. Tablet A) 20 mg compound A + 600 mg SNAC, and Tablet B) 20 mg compound A + 300 mg SNAC. Distribution of compound A was limited to plasma (endothelial permeability set to zero). First order elimination was mediated by a non-specific enzyme in plasma and the clearance was adjusted using the IV data (expression = 1 μmol/L, Intrinsic Clearance = 0.08L/min). For the oral formulations, SNAC physicochemical properties were predicted with ADMET predictor v9.5.0.0 (Simulation Plus Inc, Lancaster, CA, USA) [3] and input in PKSim v10. In addition, a dummy molecule named “Excipient” was created to allow simulation of a delayed release (enteric coated) dosage form [4]. In vitro dissolution was investigated for 90 minutes in the USP apparatus 2. Dissolution was quick with 91% dissolved at 15 mins. Throughout the 20 minutes activity window of the permeability enhancer, both compounds are dissolved at least to 90%. A Weibull function was fitted to the in vitro dissolution data and was used as dissolution input in the model: b (shape factor) = 1.6 and A (scale factor) = 0.04649 h (which was input in PKSim as Dissolution time (50% dissolved) = 7 min). The model assumes that compound A and SNAC dissolve simultaneously and that the amount of SNAC does not impact the dissolution rate and extent. A simulation with the administration of compound A, SNAC and Excipient was created in PKSim v 10 and exported to MoBi v10 (Open Systems Pharmacology [2]). The “Excipient” was used to simulate the enteric coat and trigger dissolution of the SNAC and compound A in the duodenum. A linear relationship was established between the concentration of SNAC in duodenum and the paracellular permeability of compound A (intercept = 0, slope = 1.9×10-12 cm/min/μM) using dissolution and Cp-t data of Tablet A (only SNAC concentration in duodenum was used as its effect window is ~ 20 minutes when given orally). This was then used to verify the approach by simulating the Tablet B dog Cp-t.
Results: The PBPK model predicts the observed Cmax and AUC0-t geometric means, and Tmax median of compound A. Oral dog pharmacokinetics were explained by changing paracellular permeability in the duodenum as a function of the predicted concentration of SNAC in duodenum. For tablet A, observed vs predicted PK parameters values were Cmax = 0.48 vs 0.45 μg/mL, AUC0-72h= 16.2 vs 19.2 μg*h/mL, Tmax = 2 and 1.5h, and for tablet B Cmax = 0.22 vs 0.23 μg/mL, AUC0-72h= 8.55 vs 9.66 μg*h/mL, Tmax = 2.5 and 1.5h. Compound A exposure increases linearly with the SNAC dose increment. Observed vs predicted individual concentrations R^2 were 0.58 and 0.35 for tablet A and B, respectively, this could be due to the variability of absorption caused by SNAC; however, all the profiles share the same shape, and this is predicted by the model.
Conclusions: A PBPK model that predicts the PK of compound A based on the duodenal concentration of SNAC was developed. The principle of modifying intestinal permeability based on the concentration of the permeability enhancer in the intestine, can be used to model the effect of SNAC on other poorly permeable compounds.
References:
[1] Twarog C, et al. Pharmaceutics (2019) 11, 78
[2] https://www.open-systems-pharmacology.org/
[3] Ghosh, J., et al. (2016). Modeling ADMET. In: In Silico Methods for Predicting Drug Toxicity. Humana Press, New York, NY.
[4] https://github.com/Open-Systems-Pharmacology/Forum/discussions/1186
Reference: PAGE 32 (2024) Abstr 10793 [www.page-meeting.org/?abstract=10793]
Poster: Drug/Disease Modelling - Absorption & PBPK