Volume : 13, Issue : 06, June – 2026

Title:

PHARMACIST-LED MANAGEMENT OF ALZHEIMER’S DISEASE: EVIDENCE-BASED INDIVIDUALIZED CARE AND AI-AUGMENTED DECISION SUPPORT IN INDIAN HOSPITAL SETTINGS

Authors :

Mohammed Baqtiyar Ahmed, Adiba Fathima, Syed Mohammed Hussain, Rahila Amjad, Dr. P. Soma Shekhar

Abstract :

Background: Alzheimer’s disease (AD) is the foremost neurodegenerative disorder affecting populations globally, responsible for 60–70% of all dementia diagnoses. With an estimated 55 million individuals living with dementia worldwide in 2024 — a figure projected to surpass 153 million by 2050 — and over 8.8 million affected in India alone, AD constitutes an immense and escalating public health burden. Despite this prevalence, AD remains substantially underdiagnosed and undertreated in resource-limited government hospital settings. The unique pharmacotherapeutic complexity of AD — encompassing symptomatic treatment with acetylcholinesterase inhibitors (AChEIs) and memantine, judicious neuropsychiatric symptom management, polypharmacy and anticholinergic burden reduction, caregiver-dependent adherence, and monitoring requirements for emerging disease-modifying immunotherapies — creates a multifaceted care imperative that clinical pharmacists are distinctively positioned to fulfil. The integration of artificial intelligence (AI)-driven frameworks, including machine learning-based risk prediction, natural language processing (NLP)-assisted clinical decision support systems (CDSS), and AI-powered mHealth adherence tools, presents a transformative opportunity to amplify pharmacist-led AD care.
Objectives: This review aims to: (1) characterize the pathophysiology and current pharmacological treatment landscape of AD with emphasis on pharmacist-relevant monitoring responsibilities; (2) critically appraise evidence supporting pharmacist-led polypharmacy review, anticholinergic burden reduction, and deprescribing interventions; (3) delineate the scope of AI-driven tools applicable within pharmacist-led AD
management; (4) describe the pharmacist’s emerging role in disease-modifying therapy monitoring; and (5) propose a structured, AI-integrated, stage-specific pharmacist care framework applicable to ESI Hospital and analogous Indian government hospital settings.
Methods: A narrative review of published literature was conducted, drawing on randomized controlled trials, prospective cohort studies, systematic reviews, and published international consensus guidelines. Evidence from Indian and lower-middle-income country (LMIC) settings was specifically prioritized. Literature was sourced from PubMed, Cochrane Library, and reference lists of included studies, encompassing publications from 2015 through early 2024.
Key Findings: Pharmacist-led comprehensive medication reviews have demonstrated reductions in anticholinergic drug burden by 30–45%, improvements in caregiver medication competence by 22–38%, and reductions in potentially inappropriate medication (PIM) prescribing by up to 44% in dementia populations. AI-assisted CDSS improved guideline-concordant prescribing by 34%, while mHealth-based adherence platforms reduced missed doses by 53% in community-dwelling AD patients. Integration of pharmacist judgment with AI-generated recommendations — the human-AI synergy model — achieved superior outcomes compared to either pharmacist or AI intervention alone.
Conclusion: Clinical pharmacists represent a critical and largely unrealized resource in AD management within Indian hospital settings. The structured AI-integrated pharmacist care framework proposed in this review — encompassing individualized pharmacotherapy optimization, polypharmacy screening, caregiver education, and progressive CDSS integration — provides a practical, evidence-based roadmap for improving Alzheimer’s disease outcomes in ESI hospitals and comparable resource-limited environments.
Keywords: Alzheimer’s disease; clinical pharmacist; acetylcholinesterase inhibitors; memantine; polypharmacy; anticholinergic burden; deprescribing; CDSS; artificial intelligence; mHealth; caregiver; lecanemab; ESI Hospital; disease-modifying therapy.

Cite This Article: