Background and Objective When eye diseases are treated by topical administration, the success of treatment lies in the effective drug concentration in the target tissue. This is why the drug's pharmacokinetic, in the different sub-structures of the eye, needs to be explored more accurately during drug development. The aim of the present analysis was to describe by rabbit model, the distribution of a drug after ocular instillation in the selected eye tissues and fluids. Methods By a top-down population approach, we developed and validated a population pharmacokinetics (PopPK) model, using tissue concentrations (tear, naso-lacrymal duct, cornea and aqueous humor) of a new src tyrosine kinase inhibitor (FV-60165) in each anterior segment's tissue and fluid of the rabbit eye. Inter-individual variability was estimated and the impact of the formulation (solution or nanosuspension) was evaluated. Results The model structure selected for the eye is a 4-compartment model with the formulation as a significant covariate on the first-order rate constant between tears and the naso-lacrymal duct. The model showed a good pre-dictive performance and may be used to estimate the concentration-time profiles after single or repeated administration, in each substructure of the eye for each animal included in the analysis. Conclusions This analysis allowed describing the distribution of a drug in the different selected tissues and fluids in the rabbit's eyes after instillation of the prodrug as a solution or nanosuspension. Key Points This study shows the benefit of the population approach to describe pharmacokinetics in non-clinical studies of ophthalmic drugs after topical administration. The pharmacokinetics modeling is a particularly added value to provide tailored answers with sparse data. To improve the predictive performance of the models, sampling protocol must be optimized. When data are available, this approach could allow the prediction of drug concentrations in the target tissue (eye substructure) and the evaluation of drug efficacy.