Artificial Intelligence in Pharmaceutical Care Management for Anxiety, Depression, and Schizophrenia: A Narrative Review

Abstract

Background
Mental health disorders like anxiety, depression, and schizophrenia are one of the leading causes of disability globally, causing a considerable global health and financial burden. Pharmaceutical care planning (PCP) is important in optimizing medication treatment, improving medication adherence, and reducing adverse therapeutic outcomes. However, traditional therapies often have challenges such as disintegrated care, inadequate personalization, and disparities in availability. Artificial intelligence (AI) offers innovative opportunities & address these limitations by supporting analytical model predicting the disease, personalized therapy selection, and delivery of integrated care.

Objective
The aim of this review is to analyze the implementation of AI in pharmaceutical care management of anxiety, depression, and schizophrenia, emphasizing innovations, improved clinical outcomes, and future opportunities for improving delivery of mental health care.

Methods
Literature review was conducted across PubMed, Scopus, Web of Science, and Google Scholar to identify studies. Eligible publications included cohort studies, randomized controlled trials, reviews, case studies, and guideline documents that includes AI-based tools or pharmacist-based AI programs in mental health pharmaceutical care plan.

Results
Applications of AI in PCP include accurately predicting & early diagnosing of psychiatric disorders, pharmacogenomics-based medication optimization, use of digital phenotyping to track symptoms & monitor treatment, AI-based telepsychiatry, and technologies supporting adherence. Evidence from clinical trials & case studies suggests that these AI tools augment treatment accuracy, improve medication adherence, limits hospitalizations, and support management of severe mental health disorders. Despite these developments, challenges regarding data privacy, algorithm transparency, uniform implementation across varied health systems & regulatory frameworks persists.

Conclusion
AI-driven technology to pharmaceutical care management hold substantial potential to transform mental health care by providing personalized medication treatment, improving patient outcomes, and reducing inconsistencies. Future research should prioritize integrating AI technology with electronic health data, rigorous real-world validation, ethical safety, and pharmacist-led program to enhance their societal & clinical impact