Within this repository, we distribute the physiologically-based whole-body models for pregnant individuals published in [1,2,3,4,5,6,7]. Additionally, this repository contains the refined passive transports building block which was used to build pregnancy PBPK models with different unbound drug fractions in maternal and fetal organism as described in [8] as well as the in silico cotyledon perfusion model presented in [9].

The pregnancy (and postpartum) PBPK model for amoxicillin published in [10] can be found here.

The pregnancy model structure comprises per default 27 compartments, including nine pregnancy-specific compartments as shown in the schema below.

The pregnancy PBPK models published in [1,2,3,4,5,6,7] are provided as ready-to-use MoBi^® and PK-Sim^® projects (subfolder Models). Evaluation of these model is described in the following publications:

• Cefazolin, cefuroxime and cefradine model evaluation is described in [2]
• Caffeine, midazolam, nifedipine, metoprolol, ondansetron, granisetron, diazepam and metronidazole model evaluation is described in [3]
• Acyclovir and emtricitabine model evaluation is described in [4]
• Dolutegravir and raltegravir model evaluation is described in [5]
• Acetaminophen model evaluation is described in [6,7,9]

The subfolder BuildingBlocks contains the MoBi^® building blocks for spatial structure and passive transports in pregnant individuals. Those building blocks can be used in MoBi^® to build new substance models (see below).

Note that the building block PassiveTransport_PregnantWoman.pkml includes the drug's fraction unbound as global parameter for both the maternal and fetal organism, i.e. differential protein binding in mother and fetus cannot be modeled with this building block.

The pkml file PassiveTransport_PregnantWoman_with-fetal-fu.pkml (subfolder BuildingBlocks) is a refined building block where the drug's fraction unbound was separately implemented in the maternal and fetal organism as described in [8].

When setting up a pregnancy PBPK model using this building block, the fetal fraction unbound needs to be added as new parameter called Fetal Fraction unbound (plasma, reference value) to the drug's parameter list in the Molecule building block as shown below:

The in silico cotyledon perfusion model presented in [9] is provided as MoBi^® file (subfolder CotyledonPerfusionModel). Note that this model was built with MoBi^® version 9.1 and is not updated with new releases of MoBi^®.

Currently, simulations based on pregnant individuals cannot be built up directly in PK-Sim^® (due to the fact that e.g. for the protein model structure not all required data was collected).

Steps 3 to 5 are performed in PK-Sim^®.

1. If a (MoBi^®) pregnancy model is available in pkml format, go to the step 3

2. If a (MoBi^®) pregnancy model is available in mbp3 format (MoBi^® project): open it in MoBi^®, select simulation of interest and save it in pkml format

3. Create an individual using the population Pregnant (Dallmann et al. 2017)

   Please note that in PK-Sim^®, the fertilization age (FA) is defined via the individual’s age, with 30 years corresponding to a FA of 0 weeks (i.e. just prior to conception). Hence, a pregnant woman with a FA of 38 weeks is defined using an age of 30.75 years.

4. Create a pregnancy population with the required settings based on the individual above

5. Import (MoBi^®) pregnancy model in pkml format and combine it with created population building block as described in the OSP Suite manual (Ch. 21.2 Importing Individual and Population Simulation)

The procedure is described in a comprehensive tutorial.

The physiology is based on the PBPK model implemented in PK-Sim^® version 6.0. The MoBi^® project files were created in version 6.0.

Everyone interacting in the Open Systems Pharmacology community (codebases, issue trackers, chat rooms, mailing lists etc...) is expected to follow the Open Systems Pharmacology code of conduct.

We encourage contribution to the Open Systems Pharmacology community. Before getting started please read the contribution guidelines. If you are contributing code, please be familiar with the coding standard.

The model code is distributed under the GPLv2 License.

[1] Dallmann A, Ince I, Meyer M, Willmann S, Eissing T, Hempel G. Gestation-Specific Changes in the Anatomy and Physiology of Healthy Pregnant Women: An Extended Repository of Model Parameters for Physiologically Based Pharmacokinetic Modeling in Pregnancy. Clin Pharmacokinet. 56(11), 2017: 1303-1330. doi: 10.1007/s40262-017-0539-z

[2] Dallmann A, Ince I, Solodenko J, Meyer M, Willmann S, Eissing T, Hempel G. Physiologically Based Pharmacokinetic Modeling of Renally Cleared Drugs in Pregnant Women. Clin Pharmacokinet. 56(12), 2017: 1525-1541. doi: 10.1007/s40262-017-0538-0

[3] Dallmann A, Ince I, Coboeken K, Eissing T, Hempel G. A Physiologically Based Pharmacokinetic Model for Pregnant Women to Predict the Pharmacokinetics of Drugs Metabolized Via Several Enzymatic Pathways. Clin Pharmacokinet. 57(6), 2018: 749-768. doi: 10.1007/s40262-017-0594-5

[4] Liu XI, Momper JD, Rakhmanina N, van den Anker JN, Green DJ, Burckart GJ, Best BM, Mirochnick M, Capparelli EV, Dallmann A. Physiologically based pharmacokinetic models to predict maternal pharmacokinetics and fetal exposure to emtricitabine and acyclovir. J Clin Pharmacol. 60(2), 2020: 240-255. doi: 10.1002/jcph.1515

[5] Liu XI, Momper JD, Rakhmanina NY, Green DJ, Burckart GJ, Cressey TR, Mirochnick M, Best BM, van den Anker JN, Dallmann A. Prediction of Maternal and Fetal Pharmacokinetics of Dolutegravir and Raltegravir Using Physiologically Based Pharmacokinetic Modeling. Clin Pharmacokinet. 59(11), 2020: 1433-1450. doi: 10.1007/s40262-020-00897-9

[6] Mian P, van den Anker JN, van Calsteren K, Annaert P, Tibboel D, Pfister M, Allegaert K, Dallmann A. Physiologically Based Pharmacokinetic Modeling to Characterize Acetaminophen Pharmacokinetics and N-Acetyl-p-Benzoquinone Imine (NAPQI) Formation in Non-Pregnant and Pregnant Women. Clin Pharmacokinet. 59(1), 2020: 97-110. doi: 10.1007/s40262-019-00799-5

[7] Mian P, Allegaert K, Conings S, Annaert P, Tibboel D, Pfister M, van Calsteren K, van den Anker JN, Dallmann A. Integration of Placental Transfer in a Fetal–Maternal Physiologically Based Pharmacokinetic Model to Characterize Acetaminophen Exposure and Metabolic Clearance in the Fetus. Clin Pharmacokinet. 59(7), 2020: 911-925. doi: 10.1007/s40262-020-00861-7

[8] Liu XI, Green DJ, van den Anker JN, Rakhmanina NY, Ahmadzia HK, Momper J, Park K, Burckart G, Dallmann A. Mechanistic Modeling of Placental Drug Transfer in Humans: How Do Differences in Maternal/Fetal Fraction of Unbound Drug and Placental Influx/Efflux Transfer Rates Affect Fetal Pharmacokinetics? Front Pediatr. 9, 2021: 723006. doi: 10.3389/fped.2021.723006

[9] Mian P, Nolan B, van den Anker JN, van Calsteren K, Allegaert K, Lakhi N, Dallmann A. Mechanistic coupling of a refined ex vivo cotyledon perfusion model and a physiologically based pharmacokinetic model to predict fetal acetaminophen pharmacokinetics at delivery. Front Pediatr. 9, 2021: 733520. doi: 10.3389/fped.2021.733520

[10] Dallmann A, Himstedt A, Solodenko J, Ince I, Hempel G, Eissing T. Integration of physiological changes during the postpartum period into a PBPK framework and prediction of amoxicillin disposition before and shortly after delivery. J Pharmacokinet Pharmacodyn. 47(4), 2020: 341-359. doi: 10.1007/s10928-020-09706-z