| Summary: |
The optimization of pharmacotherapy during pregnancy remains a critical challenge due to the complex physiological changes that alter drug pharmacokinetics and pharmacodynamics. Despite the increasing recognition of the importance of tailoring drug therapy to maternal and fetal needs, there is a significant knowledge gap regarding the safe and effective use of antidepressants in pregnant women. Current guidelines rely on limited data, leading to uncertainty in clinical decision-making and potential risks for both mother and fetus. This project
aims to address these gaps by developing novel, clinically relevant pharmacokinetic (PK) models and decision-support tools to optimize antidepressant therapy during pregnancy. By integrating state-of-the-art pharmacokinetic modeling with real-world data, this research seeks to enhance drug safety and efficacy for pregnant women, ultimately reducing the risk of adverse pregnancy outcomes.
The primary objective of this project is to develop robust population pharmacokinetic (PopPK) and physiologically based pharmacokinetic (PBPK) models for key antidepressants, particularly sertraline and fluoxetine, during pregnancy. These models will be used to characterize drug exposure variations across gestational stages, providing crucial insights into dose optimization. Furthermore, the project will implement a clinical decision-support system (CDSS) integrated into the Obscare software, enabling real-time guidance for healthcare providers on maternal-fetal drug exposure and risk assessment.
The project team comprises highly skilled researchers with expertise in pharmacokinetics, clinical data collection, computational modeling, and software development. Professor Nuno Vale, an expert in in silico modeling, will provide critical guidance on the development of PK models. Bárbara Costa and Lara Marques will lead the PopPK and PBPK modeling efforts, leveraging their extensive experience in pharmacokinetics and clinical research. Ma  |
Summary
The optimization of pharmacotherapy during pregnancy remains a critical challenge due to the complex physiological changes that alter drug pharmacokinetics and pharmacodynamics. Despite the increasing recognition of the importance of tailoring drug therapy to maternal and fetal needs, there is a significant knowledge gap regarding the safe and effective use of antidepressants in pregnant women. Current guidelines rely on limited data, leading to uncertainty in clinical decision-making and potential risks for both mother and fetus. This project
aims to address these gaps by developing novel, clinically relevant pharmacokinetic (PK) models and decision-support tools to optimize antidepressant therapy during pregnancy. By integrating state-of-the-art pharmacokinetic modeling with real-world data, this research seeks to enhance drug safety and efficacy for pregnant women, ultimately reducing the risk of adverse pregnancy outcomes.
The primary objective of this project is to develop robust population pharmacokinetic (PopPK) and physiologically based pharmacokinetic (PBPK) models for key antidepressants, particularly sertraline and fluoxetine, during pregnancy. These models will be used to characterize drug exposure variations across gestational stages, providing crucial insights into dose optimization. Furthermore, the project will implement a clinical decision-support system (CDSS) integrated into the Obscare software, enabling real-time guidance for healthcare providers on maternal-fetal drug exposure and risk assessment.
The project team comprises highly skilled researchers with expertise in pharmacokinetics, clinical data collection, computational modeling, and software development. Professor Nuno Vale, an expert in in silico modeling, will provide critical guidance on the development of PK models. Bárbara Costa and Lara Marques will lead the PopPK and PBPK modeling efforts, leveraging their extensive experience in pharmacokinetics and clinical research. Mariana Pereira will oversee opportunistic sampling, ensuring high-quality data collection and ethical compliance. The collaboration with VirtualCare will facilitate the integration of pharmacokinetic models into the Obscare software, ensuring the clinical applicability of the decision-support system. The clinical expertise of Dra Marina Moucho will help to guide our research and modelling efforts.
The project's methodology is structured into five key tasks. The first task involves a retrospective analysis of antidepressant use during pregnancy at Hospital São João, assessing maternal and fetal health outcomes based on existing medical records. This analysis will provide a foundational dataset for modeling efforts. The second task involves the development of a flag system within Obscare to identify pregnant patients on antidepressants, ensuring systematic data collection. Task three establishes protocols for opportunistic sampling to refine PK models, starting with maternal blood sampling and later evaluating the possibility of neonatal blood sampling and breastfeeding transfer.
This is crucial, as only about half of antidepressants have been studied in pregnancy, with many lacking complete PK characterization across all trimester. Task four is dedicated to the development of PopPK and PBPK models, incorporating retrospective, opportunistic, and literaturebased data to simulate maternal-fetal drug exposure dynamics. The final task centers on the development of a CDSS, integrating the pharmacokinetic models into clinical workflows to provide actionable insights for healthcare providers. Expected outcomes of the project include the development of validated PopPK and PBPK models for antidepressants, providing a detailed understanding of inter-individual variability in drug exposure during pregnancy. The implementation of a flag system within Obscare will streamline data collection and improve monitoring of antidepressant use in pregnant patients. The conceptualization and prototyping of a CDSS will lay the groundwork for future clinical implementation, with the long-term goal of reducing adverse pregnancy outcomes associated with antidepressant therapy.
The proposed research plan is structured to ensure feasibility within the 18-month project timeline. Potential challenges, such as delays in ethical approvals or technical difficulties in model integration, will be mitigated through proactive plannin. The structured approach, combined with the expertiseg of the research team, ensures that the project is well-positioned to achieve its objectives and contribute significantly to the field of maternal pharmacotherapy. Moreover, the methodologies developed in this project can be adapted for other drug classes, extending the impact of this research beyond antidepressants. |