Sophie Fischer-Holzhausen: No financial relationships to disclose
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Objectives: We developed a physiologically based pharmacokinetic (PBPK) model extension for the female reproductive tract (FRT) in PK-Sim/MoBi [1] to predict tissue concentrations and evaluate drug exposure following systemic and local administration routes such as intrauterine devices (IUD) and vaginal rings. Since the FRT is often missing in standard models and FRT tissue drug distribution is rarely quantified, this extension addresses a critical gap to enable data-driven, female-specific decision-making.
Methods: A comprehensive literature review was conducted to gather physiological data (e.g., blood flow and compartment volumes) to inform model parameters for the FRT organs, along with pharmacokinetic data to validate the FRT model extension. The model was implemented as a separate module in MoBi V12 [2], allowing flexible integration with PK-Sim compound models. We validated the model for levonorgestrel and metronidazole by comparing predictions to clinical data, using goodness-of-fit plots and pharmacokinetic parameters. Publicly available models were extended for both compounds [3, 4].
Results: Based on our literature review, we parametrized four tissue compartments (cervix, vagina, endometrium, and myometrium) and two fluid compartments (uterine and cervicovaginal fluid) within the FRT. The ovaries and fallopian tubes are excluded due to limited tissue-specific data. For levonorgestrel, two drug-release models from an IUD were evaluated: (I) zero-order release and (II) a Weibull function. Both were parametrized with in-vivo release data [5]. The Weibull function provided a better description of the observed release dynamics. Based on an AUC comparison, we conclude that a zero-order release description can also be applied. Simulations of plasma and tissue concentrations following oral and IUD administration of levonorgestrel are summarized as follows: oral plasma concentrations were predicted with a 0.92-fold error in AUC; IUD-based predictions had a 0.87-fold error using the zero-order model and a 0.63-fold error using the Weibull function. Despite a larger AUC deviation, the Weibull model better characterized the plasma profile shape. Uterine tissue concentrations for oral and IUD administration were predicted within a 2-fold deviation. For metronidazole, simulations of plasma and tissue concentrations following oral and IV administration [5, 6] yielded the following results: plasma AUC was predicted with a 0.78-fold error for IV administration and within a 0.81- to 1.11-fold error range for oral dosing. Endometrium and myometrium tissue concentrations were within 1.5-fold deviation for both administration routes. Cervicovaginal fluid concentrations were predicted with a 0.64-fold error after the first dose and a 0.66-fold error after five days of twice-daily oral dosing. Simulations investigating vaginal administration are currently in development and undergo further calibration before results can be reported.
Conclusions: The presented model extension enables the prediction of FRT tissues and plasma concentration for several routes of administration, including oral and IUD. During validation, only minor adjustments were needed to achieve satisfactory model accuracy.
Citations: [1] Lippert, J., Burghaus, R., Edginton, A., Frechen, S., Karlsson, M., Kovar, A., Lehr, T., Milligan, P., Nock, V., Ramusovic, S. and Riggs, M., 2019. Open systems pharmacology community—an open access, open source, open science approach to modeling and simulation in pharmaceutical sciences. CPT: pharmacometrics & systems pharmacology, 8(12), p.878. [2] https://github.com/Open-Systems-Pharmacology/Suite/releases [3] Cicali, B., Lingineni, K., Cristofoletti, R., Wendl, T., Hoechel, J., Wiesinger, H., Chaturvedula, A., Vozmediano, V. and Schmidt, S., 2021. Quantitative assessment of levonorgestrel binding partner interplay and drug‐drug interactions using physiologically based pharmacokinetic modeling. CPT: Pharmacometrics & Systems Pharmacology, 10(1), pp.48-58. [4] Dallmann, A., Ince, I., Coboeken, K., Eissing, T. and Hempel, G., 2018. A physiologically based pharmacokinetic model for pregnant women to predict the pharmacokinetics of drugs metabolized via several enzymatic pathways. Clinical pharmacokinetics, 57, pp.749-768. [5] https://labeling.bayerhealthcare.com/html/products/pi/Mirena_PI.pdf [6] Männistö, P., Karhunen, M., Mattila, J., Koskela, O., Suikkari, A.M., Heinonen, P., Tuimala, R. and Haataja, H., 1984. Concentrations of metronidazole and tinidazole in female reproductive organs after a single intravenous infusion and after repeated oral administration. Infection, 12(3), pp.197-201. [7] Salas-Herrera, I.G., Pearson, R.M., Jhonston, A. and Turner, P., 1991. Concentration of metronidazole in cervical mucus and serum after single and repeated oral doses. Journal of Antimicrobial Chemotherapy, 28(2), pp.283-289.
