Julia Macente (1) Nina Nauwelaerts (1) Miao- Chan Huang (1) Bart Lammens (2) Justine Marine Badée (3) Frederico Severino Martins (1) Pieter Annaert (1,2)
KU Leuven, Leuven, Belgium1, BioNotus2 ,Novartis Institutes for BioMedical Research, Novartis, Basel Switzerland3
Objectives: This work is part of the Innovative medicines initiative (IMI) research consortium and project ConcePTION, with the main goal to reduce uncertainty about the use of medication (e.g. valproic acid, VPA) during pregnancy and breastfeeding. The aim of this study is to develop a lactation Physiologically-Based Pharmacokinetic (PBPK) model to predict the VPA concentrations in human milk and the systemic exposure in neonates (birth to 28 days) and infants (29 days to 3 months old). The application to 11 additional medicines, selected in the context of the ConcePTION project, will result in a generic workflow for PBPK-based prediction of drug milk excretion. VPA is a first generation antiepileptic drug widely used for the treatment of epilepsy, and one of the most indicated in lactating women. However there is gap of information about safety of this medicine for the breastfed infants1–3.Many post-partum women that require this pharmacotherapy frequently must discontinue breastfeeding or postpone their medication therapy due to insufficient information on the safety for the infants during lactation4. This is a major issue since breastfeeding has been demonstrated to provide physical and mental benefits to both mother and her infant5.
Methods:
First, a PBPK model for VPA in adult healthy volunteers (HV) was reproduced from a model previously published6 using the Simcyp Simulator V20 (Certara, Sheffield, UK). Then, a lactation PBPK model was established for lactating women using the built-in Simcyp lactation module to predict the milk concentration of VPA using available information on systemic and milk VPA exposure. The Milk-to-Plasma ratio of 0.03 was used as an input7. In the next step, the daily infant dose (DID) was calculated using the average milk concentration and the maximum milk concentration methods. Finally, the PBPK model was scaled-down from HV to pediatric subjects including neonates and infants. Simulations at steady state (SS) were performed with the calculated DID to estimate the average dose of maternal medication ingested via breastfeeding, and to calculate the relative infant exposure (RIE).
Results: The geometric mean of the predicted/observed plasma AUC and Cmax ratios of VPA in multiple studies with HV were 1.04 and 0.96, respectively This indicates that this PBPK model can describe the VPA exposure following both intravenous and oral administration. In addition, this PBPK model qualified as a base model to build a PBPK model for lactating women. The lactation PBPK model was able to predict the VPA exposure in plasma and human milk for lactating women. Based upon the Caverage,m method, the estimated DID calculated was 0.11 mg/kg/day and the relative infant dose (RID) was 0.96%. The average infant plasma concentration at SS was estimated to be 0.82 mg/L (RIE 1.9%). Based upon the Cmax,m method, the DID calculated was 0.16 mg/kg/day and the RID was 1.4%. The average infant plasma concentration at SS was estimated to be 1.19 mg/L (RIE 1.7%). Comparing with observed data that range from undetectable concentrations up to 41 mg/L, the results obtained using both methods are in the range reported7. Similar results were obtained with a lactation PBPK model developed using PK-Sim® (v 9.1) (Open Systems Pharmacology) (unpublished data). With the latter model VPA exposure in plasma and human milk was successfully predicted relying on an empirical model8 (to calculate bidirectional CL values across the blood-milk barrier). The DID calculated using the Caverage,m method was 0.16 mg/kg/day and the RID was 1.4%. The average infant plasma concentration at SS was estimated to be 0.83 mg/L (RIE 1.2%).
Conclusions:
A lactation PBPK model was established which described the exposure to VPA in plasma and human milk, as well as systemic exposure in breastfed children. This model will be further verified against clinical VPA plasma and human milk data. In vitro permeability data of VPA across cultured mammary epithelial cells are being generated in our laboratory and will be used for further refinement of the PBPK model. The example of VPA shows that PBPK modelling can be used to predict pharmacokinetics of medicines in human milk, along with systemic exposure in the breastfed infant. Ongoing efforts aim to create a generic, non-clinical workflow for (in vitro– and) PBPK-based predictions of the transfer of medicines into human milk.
Acknowledgement: This work has received support from the EU/EFPIA Innovative Medicines Initiative [2] Joint Undertaking ConcePTION grant No. 821520. The research leading to these Results was conducted as part of the ConcePTION consortium. This abstract only reflects the personal views of the stated authors.
References:
[1]EURAP — an international antiepileptic drugs and pregnancy registry. Interim Repor. http://www.eurapinternational.org
[2]Kacirova I, Grundmann M. Trend Analysis of the Utilization of Antiepileptic Drugs in Pregnant Women with Epilepsy in Moravian-Silesian Region of the Czech Republic. www.klinickafarmakologie.cz/KlinFarmakolFarm2016;30
[3]Bethesda (MD): National Library of Medicine (US); 2006-. Drugs and Lactation Database (LactMed)
[4]Saha MR, Ryan K, Amir LH. Postpartum women’s use of medicines and breastfeeding practices: A systematic review. International Breastfeeding Journal. 2015;10(1). doi:10.1186/s13006-015-0053-6
[5]World Health Organization. WHO . https://www.who.int/health-topics/breastfeeding#tab=tab_1.
[6]Conner TM, Nikolian VC, Georgoff PE, et al. Physiologically based pharmacokinetic modeling of disposition and drug-drug interactions for valproic acid and divalproex. European Journal of Pharmaceutical Sciences. 2018;111:465-481. doi:10.1016/j.ejps.2017.10.009
[7]Kacirova I, Grundmann M, Brozmanova H. Valproic acid concentrations in nursing mothers, mature milk, and breastfed infants in monotherapy and combination therapy. Epilepsy and Behavior. 2019;95:112-116. doi:10.1016/j.yebeh.2019.04.002
Reference: PAGE 30 (2022) Abstr 10113 [www.page-meeting.org/?abstract=10113]
Poster: Drug/Disease Modelling - Safety