Smart healthcare: Artificial intelligences impact on drug development and patient care
The integration of artificial intelligence (AI) into healthcare has catalyzed significant advancements in drug development and patient care, revolutionizing traditional methodologies. This review explores the multifaceted impact of AI on critical areas, highlighting its transformative potential and addressing associated challenges. In drug development, AI facilitates accelerated discovery processes, enhances precision in predicting drug efficacy and safety, and optimizes clinical trial designs. AI-driven technologies such as machine learning (ML) algorithms and deep learning models enable the analysis of vast datasets, leading to the identification of novel therapeutic targets and personalized treatment strategies. In patient care, AI enhances diagnostic accuracy, enables predictive analytics for disease management, and supports telemedicine as well as remote monitoring, thereby improving patient outcomes and accessibility to healthcare services. Despite the promising advancements, the review critically examines the ethical, regulatory, and implementation challenges that accompany AI integration in healthcare. By providing a comprehensive overview of AI's current and potential contributions, this paper aims to provide an elaborative guide that future research and policymaking in smart healthcare.
Authors
- Sachin S. Mali (ORCID: https://orcid.org/0000-0002-8104-5854)
- Sudarshan Kumar Singh (ORCID: https://orcid.org/0000-0002-7929-3322)
- Sachin Mendhi
- Kuldeep Vinchurkar (ORCID: https://orcid.org/0000-0003-3572-0983)
- Amruta Shete
- Krutika Sawarkar
- Pooja V. Nagime (ORCID: https://orcid.org/0000-0002-3706-744X)
Institutions
- Prince of Songkla University (TH)
- Sandip Foundation (IN)
- Bombay College of Pharmacy (IN)
- Chiang Mai University (TH)
- Savitribai Phule Pune University (IN)
- Bharati Vidyapeeth (Deemed to be University) (IN)
Publication Details
- Journal
- Intelligent Pharmacy
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1016/j.ipha.2025.01.003
- Citations
- 8
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 5.23