Abstract
Purpose :
The discovery of small-molecule drugs for intravitreal administration would benefit of simple methods to evaluate vitreal clearance for the screening of new drug candidates. The current methods available have limitations in their applicability to small-molecule drugs and suitability to predict vitreal clearance in human. Permeability of posterior eye tissues is often described as the rate-limiting step for small-molecule clearance and a suitable permeability assay would ease clearance prediction. Therefore, we evaluated the use of Caco-2 cell intrinsic permeability as a surrogate for the permeability of posterior ocular tissues to predict vitreal clearance.
Methods :
We measured Caco-2 permeability of a set of small-molecule drugs and predicted their vitreal clearance calculated from diffusion and permeability clearances for the rabbit eye. We used the geometric mean of the directional permeabilities as an estimate of intrinsic permeability to avoid the effect of transporters expressed in Caco-2 cells. We then compared the predicted clearances to rabbit vitreal clearances available in literature and in-house at Boehringer Ingelheim.
Results :
Most of the predicted clearances were within a two-fold range of the measured values. For low permeability compounds (<5×10-6 cm/s), diffusion to the aqueous humor was predicted as the major route of elimination in the rabbit. For high permeability compounds (>30×10-6 cm/s), diffusion to the posterior segment was predicted to be the rate-limiting step, suggesting that diffusion rate determines the upper limit of vitreal clearance for any compound when not considering possible degradation within the vitreous.
Conclusions :
Caco-2 intrinsic permeability is a suitable surrogate for posterior segment tissue permeability to predict vitreal clearance of small molecules in rabbits. For an accurate prediction, the effect of diffusion rates on the clearance should also be considered. The prediction can be applied to human by using human eye dimensions in the calculation.
This is a 2021 ARVO Annual Meeting abstract.