Benjamin K. Schneider (1), Jessica Ward (2), Samantha Sotillo (2), Charles Johnson (3), Emilie Guillot (4), Jon P. Mochel (1)
(1) SMART Pharmacology, Iowa State University, 50011-1250 Ames, IA (USA); (2) Veterinary Clinical Sciences, Iowa State University, 50011-1250 Ames, IA (USA); (3) Ceva Animal Health, 66215 Lenexa, Kansas (USA); (4) Ceva Santé Animale, Companion Animal Franchise, 33 500 Libourne (France)
Introduction: Similar to humans, the renin-angiotensin-aldosterone-system (RAAS) plays a central role in the pathophysiology of congestive heart failure (CHF) in dogs, justifying the use of ACE inhibitors (ACEi) in this indication (2, 5, 6). Benazepril hydrochloride is a non-sulphydryl ACEi prodrug converted in vivo by esterases into its active metabolite, benazeprilat, a highly potent and selective inhibitor of ACE. Little is known about the optimal dosing of ACE inhibitors in dogs with CHF.
Seminal studies (3, 7) had initially suggested that the pharmacological action of benazepril was relatively independent of doses > 0.2 mg/kg P.O, thereby providing a rationale for the current European label dose of 0.25 mg/kg P.O q24h in dogs with cardiovascular diseases. However, most of these earlier studies on benazepril pharmacodynamics relied on measures of ACE activity, which is a sub-optimal endpoint to characterize the effect of benazepril on the RAAS. Today, the ACVIM recommends benazepril at a daily dose of 0.5 mg/kg PO q12h when used to treat canine CHF (2).
Objectives: The objectives of this study were (i). to characterize the dose-exposure-response relationship of benazepril(at) on biomarkers of the RAAS which are relevant to CHF pathophysiology and associated with morbidity/mortality {aldosterone (ALD) and angiotensins (I, II, III, IV, Ang1-7, Ang1-5)} using a quantitative systems pharmacology (QSP) modeling approach; and (ii). to develop a software implementation of the benazeprilat-RAAS QSP model, which is capable of rapidly simulating clinical trials in benazepril HCL in dogs for optimal dosing at the bedside.
Methods:nUsing a low-sodium (0.5% Na) diet model of RAAS activation, 9 healthy Beagle dogs were divided into 3 separate dosing groups using a full cross-over (ABC/BCA/CAB) design with a 10-day washout between periods, as follows: (i). 0.125 mg/kg P.O q12h, (ii). 0.25 mg/kg P.O q12h, and (iii). 0.5 mg/kg P.O q24h. Blood specimens were collected for benazeprilat, angiotensins, and aldosterone determination at: 0 (pre-dose), 0.5, 1, 2, 4, 8, 12, 12.5, 13, 14, 16, 20, and 24 hours after dosing. Samples were analyzed using validated HPLC MS/MS methods, as previously described (1, 4).
Experimental data were collated and imported into the Monolix Suite 2020R1 for data exploration, model development and evaluation. Quality of fit was evaluated using standard goodness-of-fit diagnostics (e.g., observed vs. predictions, scatter plot of residuals) as well as numerical summaries of fit, such as the corrected Bayesian information criteria (BICc). Precision of parameter estimates were determined using residual standard error (RSE%). Simulations were performed using the deSolve 1.28 package in R 4.0.5, while the user interface for the simulation engine was developed using Shiny 1.6.0.
Results: Benazeprilat pharmacokinetics were modeled using a 2-compartment mammillary model of distribution with a mixed 0- and 1-order absorption from the depot compartment. A Michaelis-Menten kinetic model of inhibitor, substrate, and enzyme interaction was used to describe the competitive inhibition of ACE by benazeprilat. The effect of ACE inhibition on angiotensins and ALD was further modeled using a series of direct response models with feedback mechanisms to account for the complex biological interactions within the RAAS.
Inspection of the SAEM search and a sensitivity analysis on initial parameter choices revealed a stable and precise search for parameter estimates. The final model had high precision in parameter estimates as evaluated via RSE (majority of estimates <35%). Using the simulation engine developed from the model, we predicted that the optimal dosage schedule, as defined as minimizing angiotensin II and aldosterone production, for benazepril HCL in dogs was 0.25 mg/kg P.O q12h.
Conclusions: Our results suggest that QSP modeling of the RAAS in response to ACEi administration is an efficient method for optimizing scheduling of benazepril HCL in veterinary cardiology. By developing an easy-to-use simulation interface for our model, we were able to make a first prediction of the optimal dosing of benazepril HCL in dogs with CHF.
References:
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Reference: PAGE 29 (2021) Abstr 9877 [www.page-meeting.org/?abstract=9877]
Poster: Drug/Disease Modelling - Other Topics