Use of an electronic health record training environment with a longitudinal patient case as a teaching tool in an APPE-readiness course.

Background: The integration of Electronic Health Records (EHRs) in healthcare has changed how healthcare is performed, necessitating a comprehensive understanding of these systems among pharmacists. The ability to navigate EHRs is crucial for pharmacy students' success in introductory and advanced pharmacy practice experiences (IPPEs and APPEs). This manuscript describes the development and use of an EHR training environment in an APPE-readiness course.

Sex Differences in the Anxiolytic Properties of Common Cannabis Terpenes, Linalool and β-Myrcene, in Mice.

Volatile organic compounds, colloquially referred to as "terpenes", have been proposed to impact the therapeutic qualities that are traditionally ascribed to cannabis. However, the contribution of these terpenes in anxiety, at relevant levels and exposure methods common with cannabis use, is lacking empirical assessment. We tested the anxiolytic properties of two prominent cannabis terpenes, linalool and β-myrcene, in male and female mice using short duration vapor pulls to model human inhalation when combusting flower or vaping cannabis oil.

All Together Now: Data Work to Advance Privacy, Science, and Health in the Age of Synthetic Data.

There is a disconnect between data practices in biomedicine and public understanding of those data practices, and this disconnect is expanding rapidly every day (with the emergence of synthetic data and digital twins and more widely adopted Artificial Intelligence (AI)/Machine Learning tools). Transparency alone is insufficient to bridge this gap. Concurrently, there is an increasingly complex landscape of laws, regulations, and institutional/ programmatic policies to navigate when engaged in biocomputing and digital health research, which makes it increasingly difficult for those wanting to "get it right" or "do the right thing.

Implications of An Evolving Regulatory Landscape on the Development of AI and ML in Medicine.

The rapid advancement of artificial intelligence and machine learning (AI/ML) technologies in healthcare presents significant opportunities for enhancing patient care through innovative diagnostic tools, monitoring systems, and personalized treatment plans. However, these innovative advancements might result in regulatory challenges given recent Supreme Court decisions that impact the authority of regulatory agencies like the Food and Drug Administration (FDA). This paper explores the implications of regulatory uncertainty for the healthcare industry related to balancing innovation in biotechnology and biocomputing with ensuring regulatory uniformity and patient safety.