Title:Prescription Precision: A Comprehensive Review of Intelligent Prescription Systems
Volume: 30
Issue: 34
Author(s): Junaid Tantray, Akhilesh Patel, Shahid Nazir Wani, Sourabh Kosey and Bhupendra G. Prajapati*
Affiliation:
- Department of Pharmaceutics and Pharmaceutical Technology, Faculty of
Pharmacy, Shree S.K. Patel College of Pharmaceutical Education & Research, Ganpat University, Gujarat, India
Keywords:
Intelligent prescription systems, precision medicine, artificial intelligence, electronic health records, personalized medicine, biomarkers.
Abstract: Intelligent Prescription Systems (IPS) represent a promising frontier in healthcare, offering the potential
to optimize medication selection, dosing, and monitoring tailored to individual patient needs. This comprehensive
review explores the current landscape of IPS, encompassing various technological approaches, applications,
benefits, and challenges. IPS leverages advanced computational algorithms, machine learning techniques,
and big data analytics to analyze patient-specific factors, such as medical history, genetic makeup, biomarkers,
and lifestyle variables. By integrating this information with evidence-based guidelines, clinical decision
support systems, and real-time patient data, IPS generates personalized treatment recommendations that
enhance therapeutic outcomes while minimizing adverse effects and drug interactions. Key components of IPS
include predictive modeling, drug-drug interaction detection, adverse event prediction, dose optimization, and
medication adherence monitoring. These systems offer clinicians invaluable decision-support tools to navigate
the complexities of medication management, particularly in the context of polypharmacy and chronic disease
management. While IPS holds immense promise for improving patient care and reducing healthcare costs, several
challenges must be addressed. These include data privacy and security concerns, interoperability issues, integration
with existing electronic health record systems, and clinician adoption barriers. Additionally, the regulatory
landscape surrounding IPS requires clarification to ensure compliance with evolving healthcare regulations.
Despite these challenges, the rapid advancements in artificial intelligence, data analytics, and digital
health technologies are driving the continued evolution and adoption of IPS. As precision medicine gains momentum,
IPS is poised to play a central role in revolutionizing medication management, ultimately leading to
more effective, personalized, and patient-centric healthcare delivery.