Template-Type: ReDIF-Article 1.0
Author-Name: Shagufta Rafik Shikalgar
Author-Workplace-Name: Department of Pharmaceutics, Tatyasaheb Kore College of Pharmacy, Warananagar 416113, Maharashtra, India
Author-Name: Sakshi Prakash Kekalekar
Author-Workplace-Name: Department of Pharmaceutics, Tatyasaheb Kore College of Pharmacy, Warananagar 416113, Maharashtra, India
Author-Name: Sakshi Vijay Mane
Author-Workplace-Name: Department of Pharmaceutics, Tatyasaheb Kore College of Pharmacy, Warananagar 416113, Maharashtra, India
Author-Name: Popat S. Kumbhar
Author-Workplace-Name: Department of Pharmaceutics, Tatyasaheb Kore College of Pharmacy, Warana University, Warananagar 416113, Maharashtra, India
Title: Artificial Intelligence in Precision Pharmacotherapy: Optimizing Drug Selection and Dosing in Chronic Diseases
Abstract: Chronic disease is one of the major causes of death worldwide which generally not vaccine preventable are also don’t resolve spontaneously. The world health organization identifies four main types of chronic diseases including cardiovascular diseases (CVD, primarily heart disease and stroke), Cancer, chronic respiratory diseases and diabetes which are responsible for the majority of related deaths, while they can be treated, are seldom healed with medicine or other medical treatment. Chronic disease care is becoming increasingly confined, which frequently results in suboptimal therapeutic efficacy and adverse medication reactions. Pharmacotherapy involve in management and treatment of chronic diseases mainly associate with the dose and drug selection for the authorized treatment that significantly impact on outcomes. Artificial intelligence and machine learning are shifting pharmacotherapy from a reactive, standardize model to proactive personalized and data driven. Different AI driven software’s and technical platform along with their superiority in management of chronic diseases has elaborate in this review article. This article looks at the use of Artificial intelligence to optimize medicine selection and dosing for complicated, long-term illness. Apart from their promising outcomes, concern about mainly data privacy, model interpretability and also ethical regulatory barriers remain. This study explores the challenges emphasizing the significant importance of transparent, explainable AI in ensuring efficacy and safety in clinical practices. The use of AI in precision pharmacology has the potential to greatly improve therapeutic results, patient compliance and healthcare resource use for chronic conditions.
Keywords: artificial intelligence, chronic diseases, pharmacotherapy, AI driven software, dosing selection
Journal: Inventum Biologicum: An International Journal of Biological Research
Pages: 21-34
Volume: 6
Issue: 3
Year: 2026
File-URL: https://journals.worldbiologica.com/ib/article/view/220
File-Format: text/html
File-URL: https://journals.worldbiologica.com/ib/article/view/220/388
File-Format: Application/pdf
Handle: RePEc:adg:ibijbr:v:6:y:2026:i:3:p:21-34