Anam Fayyaz (1, 2), Veli-Pekka Ranta (2), Eva M. del Amo (3), Iain Gardner (1), Arto Urtti (2), Masoud Jamei (1)
Institution: (1) Certara UK Ltd, Simcyp Division, Sheffield, United Kingdom, (2) School of Pharmacy, University of Eastern Finland, Kuopio, Finland, (3) School of Pharmacy, University of Manchester, Manchester, United Kingdom
Introduction:
Eye drops and topical drug dosage forms are among the most convenient ocular drug administration routes, as they are non-invasive, self-administered and show high patient compliance (1, 2). However, poor corneal permeability and drainage through the tear outflow can cause poor bioavailability (3). A predictive mechanistic model integrating eye anatomical and physiological parameters with the active pharmaceutical ingredient properties and formulation characteristics can assist with getting better insight into drug bioavailability and disposition in the interior eye which is currently lacking (4,5). In vitro in vivo extrapolation approaches linked with physiologically based pharmacokinetic (PBPK) modeling provides a powerful tool to serve this purpose. Such models can reduce, refine and replace animal studies and inform and speed up ocular drug development (5).
Objectives:
To build a general semi-physiologically based pharmacokinetic model for topical ocular drug delivery of small molecule drugs to rabbit eyes. Further, to assess the model predictive performance for topically administered pilocarpine and timolol to the rabbit eyes.
Material and Methods:
The rabbit eye anatomical and physiological data were collated from literature and analysed. A semi physiologically based model for simulating topical ocular drug administration to rabbit eyes was developed considering four compartments, namely the tear fluid, cornea, aqueous humor and a reservoir compartment. Currently, the eye is represented using a compartmental structure with three compartments (tear fluid, cornea, and aqueous humor) representing sites where drug concentration can be measured and a reservoir compartment used to model peripheral distribution. The movement of the drug between the compartments is described by a series of ODEs. Although this is a simplified representation of the processes occurring in the eye, – it can provide an appropriate balance of model complexity and computational time for the purposes of this modelling exercise. The model was built in Matlab and used to predict the concentration profiles in different ocular compartments.
Pilocarpine and timolol (both in solution) were selected as two model drugs – due to availability of observed concentration time profiles in different rabbit eye tissues.
The model parameters and their sources are presented in Table 1.
|
Parameter |
Timolol |
Pilocarpine |
|
Permeability from tear fluid to cornea |
Estimated from corneal epithelial rabbit study |
Fitted |
|
Clearance from tear fluid to conjunctiva |
Estimated from in-vivo precorneal clearance study |
Estimated from in-vitro precorneal clearance study |
|
Clearance from cornea to aqueous humor |
Fitted |
Fitted |
|
Clearance from aqueous humor |
Estimated from intracameral injection study |
Estimated from intracameral injection study |
|
Volume and flows in and out of the reservoir |
Estimated from intracameral injection study |
Estimated from intracameral injection study |
Results:
The model performance for pilocarpine and timolol were compared against the observed values. The observed Cmax and AUC in aqueous humor for pilocarpine were 1.1 µg/mL and 63.2 µg.min/mL. While the predicted values are 1.20 µg/mL and 76.0 µg.min/mL respectively. The observed Cmax and AUC in aqueous humor for timolol were 3.0 µg/mL and 322.1 µg.min/mL. While the predicted values are 3.6 µg/mL and 420.3 µg.min/mL respectively. These results show that the simulations results were within 2-fold of the observations.
Conclusion:
A semi-PBPK model for topical ocular drug delivery of small molecules in rabbit eyes was developed. The model is able to simulate the distribution of drugs in different tissues of the eye after instillation of a drug solution in the eye (with acceptable performance). We aim to develop predictive models/algorithms to determine the rest of the model parameters and assess its performance for a wider range of drugs.
References:
[1] Le Bourlais, C., et al. (1998). “Ophthalmic drug delivery systems—recent advances.” Prog Retin Eye Res 17(1): 33-58.
[2] Patel, A., et al. (2013). “Ocular drug delivery systems: an overview.” World journal of pharmacology 2(2): 47.
[3] Sasaki, H., et al. (1997). “In vivo ocular pharmacokinetic model for designing dosage schedules and formulations of ophthalmic drugs in human.” Acta medica Nagasakiensia 42(3-4): 45-50.
[4] Agrahari, Vibhulti, et al (2016).” A comprehensive insight on ocular pharmacokinetics.” Drug delivery and translational research 6.6:735-754.
[5] Del Amo, E. M., et al. (2017). “Pharmacokinetic aspects of retinal drug delivery.” Prog Retin Eye Res 57: 134-185.
Reference: PAGE 28 (2019) Abstr 9205 [www.page-meeting.org/?abstract=9205]
Poster: Drug/Disease Modelling - Other Topics