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Trending M Pharm Pharmacy Practice Dissertation Topics (2025–2026)

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1. 🔬 Pharmacovigilance & Drug Safety

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2. 💊 Medication Adherence & Patient Counseling

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3. 🏥 Clinical Pharmacy & Pharmacist Interventions

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4. 💉 Antimicrobial Stewardship Programs (ASP)

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5. 📋 Drug Utilization Studies (DUS)

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6. 🤖 Emerging/Innovative Topics (High Novelty)

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7. 📊 Health Outcomes & Pharmacoeconomics

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Quick Tips for Choosing Your Topic

1. Feasibility first — choose a topic where you can collect data in your institution (hospital/pharmacy/OPD)
2. Prefer prospective over retrospective if time allows — higher quality evidence
3. Pair with a validated tool (Naranjo scale, WHO indicators, Morisky scale, Beers criteria) — easier to publish
4. AMR + pharmacovigilance + pharmacist-led interventions are the top three areas getting funding and journal acceptance in 2025–2026
5. Check your PG guide's ongoing projects — aligning with them smooths approvals

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FAERS Pharmacovigilance: Methodology & Recent Research Papers

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📐 Core Methodology: How FAERS Analysis Works

• Query the publicly available FAERS quarterly data (ASCII files) or via tools like OpenVigil 2.1-MedDRA or AERSMine
• Filter by drug name (using MedDRA/NCBI MeSH synonyms), role code = "Primary Suspect" (PS), and deduplicate reports

• Adverse events are coded using MedDRA (Medical Dictionary for Regulatory Activities) at:
  • PT (Preferred Term) — specific event
  • SOC (System Organ Class) — body system grouping

Best practice (2024–2025): Combine all four methods — a signal is considered robust only when positive in ≥2–3 algorithms. This is now the standard in published literature.

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📄 Key Recent Research Papers (PubMed, 2023–2026)

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🔬 Methodology Exemplar Papers

Muhammed A et al. Expert Opin Drug Saf. 2024 Jun. PMID: 37986140

• Used PRR, ROR (LB), IC025 from FAERS + VigiBase
• Also performed signal refinement via OpenVigil 2.1 (removing co-drug confounders)
• Paired with meta-analysis of RCTs — gold standard hybrid design
• ✅ Model paper for dissertation methodology

Liu H et al. Int J Surg. 2025 Feb. PMID: 39715164

• Extracted FAERS Q1 2008–Q4 2023 (~1,505 reports, 3,562 ADEs)
• Used ROR as primary metric; MedDRA re-encoding for standardization
• Detected cardiovascular, allergic, neurological signals (laryngospasm, DIC, bronchospasm)

Caruso I et al. J Endocrinol Invest. 2024 Nov. PMID: 39141075 | PMC: PMC11473560

• Used OpenVigil 2.1 + AERSMine (FAERS 2004Q1–2023Q3)
• Compared tirzepatide vs. insulin, SGLT2i, metformin, GLP-1RA using ROR with 95% CI
• Detected pancreatitis (ROR 3.63), diabetic retinopathy (ROR 4.14), medullary thyroid cancer (ROR 13.67)

Liu Q et al. Front Pharmacol. 2024. PMID: 39635439

• Cross-validated signals using both US (FAERS) and Japanese (JADER) databases
• Emerging trend: multi-national database corroboration

Yan L et al. Front Pharmacol. 2025. PMID: 40242445

• Real-world disproportionality analysis on a recently approved drug (2023)
• Trend: FAERS is being applied to newly approved drugs within 1–2 years of market entry

Dong Y et al. Front Med (Lausanne). 2024. PMID: 39882521

• Compared dapagliflozin, empagliflozin, canagliflozin across FAERS
• Methodology: class-level comparative analysis

Xiao S et al. Endocr Metab Immune Disord Drug Targets. 2025. PMID: 40849770

• Combined FAERS disproportionality with network pharmacology to identify molecular mechanisms of drug-induced insulin autoimmune syndrome
• ✅ Innovative hybrid approach gaining traction in 2025

Hong X et al. Int J Surg. 2025. PMID: 41405272

• Pharmacovigilance integrated with clinical insights for bleeding management

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🛠️ Tools & Resources for FAERS Analysis

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⚠️ Methodological Limitations to Discuss in Your Dissertation

1. Underreporting bias — only a fraction of real ADRs are ever reported
2. Notoriety bias — high-profile drugs get more reports (e.g., COVID vaccines in 2021–2023)
3. Missing clinical data — dose, duration, comorbidities often absent
4. Confounding by indication — drug-event pairing may reflect disease, not drug
5. Duplicate reports — same event reported by patient + physician + manufacturer
6. No denominator — cannot calculate true incidence rates; only relative reporting
7. Association ≠ causation — disproportionality signals require clinical validation

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💡 Dissertation Design Tip

Drug class (e.g., GLP-1 agonists / CDK4/6 inhibitors / newer antibiotics) → FAERS extraction → disproportionality using ROR + PRR + BCPNN → identify new/unlabeled signals → compare with drug prescribing information → conclude on pharmacovigilance gaps

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Clinical Pharmacy & Pharmacist Intervention — Dissertation Topics (2025–2026)

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🏥 CATEGORY 1: Hospital-Based Clinical Pharmacy

1.1 Drug-Related Problems (DRPs) Identification & Resolution

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1.2 Medication Error Prevention

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1.3 Medication Reconciliation at Care Transitions

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1.4 Clinical Pharmacist in ICU/Critical Care

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💊 CATEGORY 2: Chronic Disease Management

2.1 Diabetes

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2.2 Hypertension

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2.3 Cardiovascular Disease

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2.4 COPD & Asthma

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2.5 CKD / Renal Disease

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🧠 CATEGORY 3: Psychiatry & Mental Health

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🎗️ CATEGORY 4: Oncology Pharmacy

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👴 CATEGORY 5: Geriatrics & Polypharmacy

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🆘 CATEGORY 6: Emergency & Transitions of Care

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🌐 CATEGORY 7: Emerging / High-Novelty Topics

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✅ Top 5 Recommended Topics for M Pharm Dissertation (Feasibility + Novelty)

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📋 Full Research Proposal

Pharmacist-Led Medication Review in Elderly Inpatients: Detection of Potentially Inappropriate Medications Using STOPP/START v3 and 2023 Beers Criteria

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1. TITLE

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2. BACKGROUND & RATIONALE

• PIMs are detected in 20–80% of elderly inpatients depending on criteria used — SR evidence, PMID [39350081]
• Benzodiazepines, NSAIDs, and anticholinergics account for the most common PIMs in hospital settings
• In a 16-hospital Spanish multicenter study (n=4,183), PIMs prevalence was 23.5%, with benzodiazepines comprising 70% of all PIMs — PMID [39350081]
• PIM prevalence in Asian inpatient settings ranges from 34–66% depending on criteria version used (Beers 2023 identifies more PIMs than older versions)
• Pharmacist-led deprescribing reduces PIM burden (RR 1.85 for effective deprescribing) — SR+meta-analysis, PMID [41514446], BMC Geriatr, Jan 2026

• Very few Indian studies use the 2023 AGS Beers Criteria (most use 2015 or 2019 versions)
• STOPP/START version 3 (2023 update with expanded criteria) has not been applied in most Indian hospital settings
• Pharmacist intervention acceptance rates and clinical impact remain under-reported in Indian geriatric inpatients

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3. OBJECTIVES

Primary Objective

• To identify and assess the prevalence of PIMs in elderly inpatients using STOPP/START v3 and 2023 AGS Beers Criteria

Secondary Objectives

• To identify Potential Prescribing Omissions (PPOs) using the START criteria
• To categorize PIMs by drug class, organ system, and clinical risk
• To document clinical pharmacist recommendations and measure the acceptance rate by treating physicians
• To assess polypharmacy prevalence (≥5 drugs) and hyperpolypharmacy (≥10 drugs)
• To identify predictors of PIMs (age, sex, number of drugs, comorbidities, ward type)

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4. STUDY DESIGN

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5. INCLUSION & EXCLUSION CRITERIA

Inclusion Criteria

• Age ≥ 60 years
• Admitted to general medicine / geriatric ward
• Prescribed ≥ 2 medications
• Inpatient stay ≥ 48 hours
• Patient/caregiver willing to give informed consent

Exclusion Criteria

• Age < 60 years
• ICU/critical care patients (complex variables may confound)
• Patients on palliative care only
• Patients discharged within 48 hours of admission
• Pregnant/lactating women (already excluded by age but stated explicitly)
• Patients who are unable to communicate and have no caregiver

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6. SAMPLE SIZE

n = Z²× P × (1-P) / d²

• Z = 1.96 (95% confidence), P = 0.54 (54% PIM prevalence from Asian inpatient studies), d = 0.07 (7% precision)
• n ≈ 195 patients (add 10% for dropouts → ~215 patients)

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7. METHODOLOGY / STUDY PROCEDURE

Step 1 — Patient Enrollment

• Screen all newly admitted patients aged ≥60 years daily
• Obtain written informed consent
• Record demographic data: age, sex, diagnosis, comorbidities, duration of hospital stay

Step 2 — Medication Data Collection

• Collect complete medication list at admission from:
  • Case records / medication charts
  • Previous discharge summaries
  • Patient-carried medication lists
• Record: drug name, dose, frequency, route, indication, duration

Step 3 — PIM Screening

🔴 2023 AGS Beers Criteria

• Section A: PIMs in most older adults (e.g., first-generation antihistamines, benzodiazepines, NSAIDs)
• Section B: PIMs in certain conditions (e.g., anticholinergics in BPH, NSAIDs in CKD)
• Section C: Drug-drug interactions (e.g., warfarin + NSAIDs)
• Section D: Drugs with special renal dosing requirements
• Section E: Quality indicators (drugs that should be used with caution)

🟡 STOPP/START v3 (2023)

• STOPP (80+ criteria) — identify PIMs to stop/avoid
• START (34 criteria) — identify PPOs (drugs that should have been prescribed but weren't)

Step 4 — Pharmacist Intervention

• Prepare written/verbal recommendations for each PIM/PPO identified
• Communicate to the treating physician/team (via clinical ward rounds, written intervention forms, or electronic notes)
• Document: type of intervention, drug involved, reason, physician response

Step 5 — Outcome Assessment

• Record: acceptance / partial acceptance / non-acceptance of each recommendation
• Note if the PIM was discontinued, dose adjusted, or substituted
• Track: length of hospital stay, any ADR recorded, 30-day readmission (if feasible)

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8. DATA COLLECTION TOOLS

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9. DATA ANALYSIS

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10. OUTCOME MEASURES

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11. CRITERIA TOOL OVERVIEW

2023 AGS Beers Criteria — Key Categories

STOPP/START v3 — Key Updates (2023)

• Expanded from v2 (87 STOPP, 34 START) to v3 (131 STOPP, 46 START criteria)
• New additions: SGLT2 inhibitors in frail elderly, bisphosphonates with CKD, long-term PPI use
• START additions: SGLT2i for T2DM + CKD/CVD, statin for CVD

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12. ETHICAL CONSIDERATIONS

• IEC/IRB approval from your institution's Ethics Committee
• Written informed consent from patient / legal guardian
• Patient data de-identified for analysis
• No additional tests or interventions beyond standard care
• Voluntary participation; withdrawal at any time

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13. EXPECTED OUTCOMES & SIGNIFICANCE

• Will generate institution-specific PIM prevalence data — valuable for hospital formulary review
• Will demonstrate the clinical pharmacist's role as a patient safety advocate in geriatric care
• Physician acceptance rate data will inform pharmacist-physician collaboration models
• Comparing STOPP/START v3 vs. 2023 Beers — generates comparison data rarely available from Indian settings
• Publishable in indexed journals (IJCP, Drugs & Aging, Geriatrics, BMC Geriatrics)

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14. SUPPORTING LITERATURE (Key References)

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15. TIMELINE (12-Month Plan)

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1. A literature review draft for this topic?
2. The data collection forms / CRF templates?
3. A PowerPoint presentation of this proposal for your guide submission?