Revolutionizing Obstetric and Pediatric Pharmacology through Artificial Intelligence and Digital Health Innovations

Artificial intelligence (AI) and digital health technologies are rapidly transforming clinical pharmacology, introducing novel approaches to overcome traditional drug development challenges and optimize patient care in obstetric and pediatric populations. Despite notable advancements, such as predictive modeling for pharmacokinetics (PK) and pharmacodynamics (PD) tailored for these specific groups and wearable technologies enabling real-time patient monitoring of obstetric and pediatric populations, significant hurdles remain. These include regulatory constraints specific to vulnerable populations, ethical considerations with heightened sensitivity, data standardization, and effective integration of diverse datasets like electronic health records (EHRs) into clinical practice.

This Research Topic aims to examine how AI and digital health technologies can enhance drug development, optimize therapeutic precision, and improve patient outcomes in clinical pharmacology for obstetric and pediatric patients. It seeks to identify practical implementation strategies, address key regulatory issues tailored to these populations, and discuss ethical and technical barriers that limit broader clinical application. Key questions to explore include how AI-driven innovations could streamline drug development processes specific to obstetric and pediatric needs and how digital health tools can effectively personalize pharmacological therapies for mothers and children.
To gather further insights into the effective integration of AI and digital health in clinical pharmacology for obstetric and pediatric populations, we welcome articles addressing, but not limited to, the following themes:

-Application of AI in pharmacokinetic and pharmacodynamic modeling specifically for pregnancy and children
- Wearable devices and mobile health (mHealth) technologies for patient data collection in obstetric and pediatric care
- Real-world data (RWD) and evidence (RWE) generation strategies using digital health tools tailored for mothers and children
- Integration and harmonization of diverse datasets, including EHRs, specific to obstetric and pediatric settings
- Regulatory, ethical, and practical considerations for implementing AI and digital health innovations in clinical pharmacology focused on obstetric and pediatric populations

This topic welcomes original research, reviews, brief reports and case studies. Dr. Jeff Barrett is Chief Science Officer of Aridhia Bioinformatics which is a cloud-based data sharing service provider and Dr. Catherine Sherwin is Clinical Pharmacology & Pharmacometrics VP of Differentia Bio who works with various clients providing pharmacometric services.