Periklis Tsiros1, Paraskevi Papakyriakopoulou2, Vasileios Minadakis1, Haralambos Sarimveis1, Georgia Valsami2
1School of Chemical Engineering, National Technical University of Athens, 2Department of Pharmacy, National and Kapodistrian University of Athens
Introduction/Objectives: Fingolimod hydrochloride (FH) is a sphingosine-1-phosphate (S1P) receptor modulator approved for the treatment of multiple sclerosis (MS). Despite its high apparent oral bioavailability (~93%), its slow absorption (Tmax = 8–12 h) and extensive hepatic metabolism pose significant challenges, prolonging the time to reach peak concentrations and affecting systemic exposure. However, the absolute bioavailability could not be determined due to the reversible metabolism of FH to its active phosphate form. Intranasal (IN) administration offers a promising alternative, enabling rapid nose-to-brain delivery while bypassing hepatic metabolism and reducing peripheral side effects [1-3]. To better understand the pharmacokinetics (PK) of fingolimod following nasal film and oral solution administration, we developed a pharmacokinetic model using R programming language [4]. PK modeling allows us to better understand the underlying kinetics of FH exposure and assess the delivery efficiency of different administration schemes. Methods: FH concentration-time data from PK study in C57BL/6 J Mice, administered either nasally (via two different formulations, F3 and F4 nasal films) or orally (as an FH solution) were all averaged across individuals and fitted simultaneously to a semi-mechanistic PK model. The F3 and F4 nasal formulations were developed through an optimization process in previous work [5], with F3 containing 3% hydroxypropyl methylcellulose (HPMC) and F4 comprising 3% HPMC and 6% methyl-beta-cyclodextrin (Me-ß-CD) to enhance drug solubility and absorption. The serum concentration-time profiles generated after oral administration included a fast absorption phase and a second, more pronounced peak occurring 8-10 hours post administration. To capture this pattern, both blood and lymphatic absorption pathways were included in the model. Specifically, the model incorporates six compartments: blood, lymph, brain, olfactory bulb, small intestine (SI) lumen and nasal cavity. Perfusion-limited kinetics were assumed for tissue partitioning and a low fraction unbound was used to account for the low amount of free drug in the serum. Physiological parameters were derived either directly from experimental measurements or obtained from the literature. The in vivo data were used to estimate 1) the clearance rate from serum, 2) the absorption rate constants from SI lumen to blood and lymph, 3) the absorption rate from the nasal cavity to blood, 4) the serum-to-brain partition coefficient, as well as 5) the parameters characterizing the direct nose-to-brain transport via the olfactory bulb. Results: Several optimization schemes and objective functions were tested to derive the best parameter solution. The lymph compartment was divided into seven subcompartments, sharing the same transit time, to simulate the slower absorption component. The absorption from SI lumen to lymph (0.012 h-1) was about ten times higher than the absorption to serum (0.0009 h-1). For nasal administration, separate absorption pathways into serum and translocation to the olfactory bulb were implemented for each formulation to account for their distinct absorption kinetics. Absorption to serum for the F3 nasal film (0.011 h-1) was more than double in relation to the absorption for F4 film (0.005 h-1). The differences were less profound for the translocation through the olfactory nerve; 3.8e-4 h-1 for F3 compared to 2.2e-4 h-1 for F4. Finally, the contribution of direct CNS uptake through the olfactory nerve was estimated to be 32% for the F3 film compared to 41% for the F4 film. Conclusions: Pharmacokinetic modeling allowed quantification of differences among the administration routes. Oral administration showed predominant absorption via the lymphatic compartment, while nasal administration revealed comparable contributions from olfactory nerve translocation and direct absorption into the bloodstream. To further elucidate the distinctions between these administration pathways, population pharmacokinetic modeling can be employed, providing insights into the variability associated with each absorption route.
[1] David OJ, Kovarik JM, Schmouder RL. Clinical pharmacokinetics of fingolimod. Clin Pharmacokinet. 2012;51(1):15–28. https:// doi.org/ 10. 2165/ 11596 550- 00000 0000- 00000. [2] Laffleur F, Bauer B. Progress in nasal drug delivery systems. Int J Pharm. 2021;607:120994. https:// doi. org/ 10.1016/j. ijpha rm. 2021. 120994. [3] Dhuria SV, Hanson LR, Frey WH 2nd. Intranasal delivery to the central nervous system: mechanisms and experimental considerations. J Pharmaceut Sci. 2010;99(4):1654–73. https:// doi. org/ 10.1002/ jps. 21924. [4] https://cran.r-project.org/ [5] Papakyriakopoulou P, Balafas E, Kostomitsopoulos N, Rekkas DM, Dev KK, Valsami G. Pharmacokinetic Study of Fingolimod Nasal Films Administered via Nose-to-Brain Route in C57BL/6 J Mice as Potential Treatment for Multiple Sclerosis. Pharm Res. 2024 Oct;41(10):1951-1963. https://doi.org/10.1007/s11095-024-03745-8 [6] Tsiros P, Minadakis V, Li D, Sarimveis H. Parameter grouping and co-estimation in physiologically based kinetic models using genetic algorithms. Toxicol Sci. 2024;200(1):31-46. doi:10.1093/toxsci/kfae051
Reference: PAGE 33 (2025) Abstr 11612 [www.page-meeting.org/?abstract=11612]
Poster: Drug/Disease Modelling - CNS