Nadia Toffoletto 1, Iñaki F. Trocóniz 2, Silvia Pescina 1
1 ADDResLab, Department of Food and Drug, University of Parma (Parma, Italy), 2 Department of Pharmaceutical Sciences, School of Pharmacy and Nutrition, University of Navarra (Pamplona, Spain)
Introduction: Periocular injections represent an alternative route for ocular drug delivery, offering potential advantages in terms of efficacy, safety, and patient comfort compared with conventional eye drops [1] and intravitreal injections [2]. However, drug distribution to intraocular tissues following periocular administration is governed by multiple competing pathways and physiological barriers, making exposure in the posterior segment difficult to predict. Existing modeling approaches are often drug-specific and limited in scope. Therefore, a general mechanistic framework is needed to quantitatively describe systemic and ocular pharmacokinetics and to support prediction across compounds with different physicochemical properties.
Objectives: The objective of this work is to establish a broadly applicable physiologically-based pharmacokinetic (PBPK) model to characterize the distribution of small-molecule drugs after periocular administration. In contrast to previously published compound-specific models [3, 4], the proposed study was designed to support parameter estimation and to enable exploratory prediction of ocular exposure based on the physicochemical properties of the drugs.
Methods: A literature analysis was conducted to gather in vivo concentration-time profiles from seven studies (five in rabbits and two in rats) reporting drug levels in plasma, vitreous humor, and aqueous humor following periocular administration. Both hydrophilic and lipophilic molecules were considered. Drug administration was represented as a periocular depot. Model building followed a stepwise strategy: initially, a systemic compartmental model was developed using plasma data to determine systemic pharmacokinetic parameters; then, ocular compartments (vitreous and aqueous humor) were incorporated. As published data were reported as mean ± SD, the naïve pooled data approach was applied. A variability component was included to estimate the standard deviation and derive the coefficient of variation associated with the predicted concentration-time profiles. The final model was further applied to simulate ocular distribution for two additional drugs, not included in model development, using their logD7.4, unbound fraction, and molecular weight, and predictions were compared with ex vivo whole-eye data. Parameter estimation and model assessment were conducted with NONMEM v7.6.0.
Results: Across all compounds, transfer from the periocular depot to the systemic circulation exceeded direct ocular uptake, consistent with the administration route. Diffusion toward the anterior chamber via the sclera/cornea pathway was slower than transport toward the vitreous, reflecting longer diffusional distances. Clearance from the vitreous through the anterior pathway accounted for 0 – 51% of total vitreal elimination, emphasizing the important contributions of both anterior and posterior elimination routes. The estimated permeability coefficient (Papp) across the retinal pigment epithelium (RPE) ranged from 0.4 to 6.9e-5 cm/s, with celecoxib, the most lipophilic drug in the study, as the only outlier (Papp = 40e-5 cm/s). Such values are comparable to ex vivo literature data for other small drugs across bovine RPE-choroid (0.2 – 2e-5 cm/s) [5]. Simulations of ocular exposure based solely on compound properties showed concordance with independent ex vivo data, supporting the translational relevance of the model.
Conclusions: A PBPK model was developed to describe systemic and ocular drug distribution after periocular administration of small molecules. The model enabled estimation of key pharmacokinetic parameters and demonstrated its potential as a predictive tool, highlighting its utility in supporting ocular drug development.
References:
[1] Merkoudis N. et al. (2014). Comparison of peroperative subconjunctival injection of methylprednisolone and standard postoperative steroid drops after uneventful cataract surgery. Acta Ophthalmol. 92, 623-628. DOI: 10.1111/aos.12358.
[2] Li S. K. et al. (2012). MRI study of subconjunctival and intravitreal injections. Journal of Pharmaceutical Sciences 101 (7), 2353-2363. DOI:10.1002/jps.23127.
[3] Carcaboso A.M. et al. (2007). Topotecan vitreous levels after periocular or intravenous delivery in rabbits: an alternative for retinoblastoma chemotherapy. Invest Ophthalmol Vis Sci, 48 (8), 3761–3767. DOI: 10.1167/iovs.06-1152.
[4] Buitrago E. et al. (2010). Pharmacokinetic analysis of topotecan after intra-vitreal injection. Implications for retinoblastoma treatment. Exp Eye Res, 91 (1), 9–14. DOI: 10.1016/j.exer.2010.03.009.
[5] Pitkänen L. et al. (2005). Permeability of Retinal Pigment Epithelium: Effects of Permeant Molecular Weight and Lipophilicity. Invest Ophthalmol Vis Sci, 46, 641-646. DOI: 10.1167/iovs.04-1051.
Reference: PAGE 34 (2026) Abstr 12171 [www.page-meeting.org/?abstract=12171]
Poster: Drug/Disease Modelling - Absorption & PBPK