Post Marketing surveillance

Post-Marketing Surveillance (PMS):

1. Introduction

• Definition:
  Post-Marketing Surveillance (PMS) is the monitoring of safety, efficacy, and quality of medicines after they are approved and marketed.
• Need:
• Pre-marketing clinical trials (Phase I–III) are limited by:
• Small sample size
• Short duration
• Selected patient population (excludes elderly, pregnant, comorbidities, polypharmacy)
• Hence, many rare, delayed, or long-term ADRs are detected only after marketing.
• Role: Protect public health by detecting risks → modify drug use (label changes, restricted use, or withdrawal).

2. Objectives of PMS

👉 Mnemonic: DR CARE DL

1. D – Detection of new, rare, or unexpected ADRs
2. R – Risk quantification (true incidence & severity)
3. C – Comparative safety assessment between drugs
4. A – Assessment of effectiveness in real-world use
5. R – Risk factor identification (age, comorbidities, drug interactions)
6. E – Evaluation of long-term & cumulative effects
7. D – Drug utilization studies (patterns, misuse, off-label use)
8. L – Look for drug–drug or drug–disease interactions

3. Methods of PMS

3.1 Spontaneous Reporting System (SRS)

• Definition:
  Voluntary reporting of ADRs by healthcare professionals, patients, or companies.
• Examples:
• USA: FAERS (FDA Adverse Event Reporting System)
• EU: EudraVigilance
• WHO: VigiBase (UMC, Sweden)
• India: PvPI (Pharmacovigilance Programme of India, IPC Ghaziabad)
• Advantages:
• Inexpensive
• Detects rare or unexpected ADRs
• Wide geographical coverage
• Disadvantages:
• Under-reporting (only 5–10% ADRs reported)
• Reporting bias (serious ADRs more likely reported)
• Cannot calculate incidence or risk (no denominator)
• Weak causality assessment

3.2 Cohort Studies

• Definition:
  Follow groups of exposed vs. unexposed patients over time.
• Types:
• Prospective (forward-looking)
• Retrospective (using past medical records)
• Advantages:
• Can calculate incidence rates & relative risk
• Establishes temporal relationship
• Useful for multiple outcomes
• Disadvantages:
• Expensive, time-consuming
• Requires large sample size
• Inefficient for rare ADRs
• Risk of loss to follow-up, confounding

3.3 Case-Control Studies

• Definition:
  Compare patients with ADR (cases) vs. without ADR (controls), looking for prior exposure.
• Measure: Odds Ratio (OR).
• Advantages:
• Best for rare ADRs
• Relatively fast & inexpensive
• Can study multiple exposures
• Disadvantages:
• Recall bias (patients may not remember exposures)
• Selection bias in choosing controls
• Cannot measure incidence
• Temporal relationship sometimes unclear

3.4 Prescription Event Monitoring (PEM)

• Definition:
  All patients prescribed a new drug are followed up (e.g., questionnaires sent to doctors).
• Example: UK PEM system.
• Advantages:
• Provides denominator (number of patients exposed) → event rates possible
• Covers large populations systematically
• Useful for detecting common ADRs
• Disadvantages:
• Relies on physician compliance → incomplete data
• Misses ADRs if patients do not report
• Time lag before results

3.5 Record Linkage Studies

• Definition:
  Linking existing healthcare databases (EHR, hospital records, mortality, insurance claims) to study drug safety.
• Examples: CPRD (UK Clinical Practice Research Datalink), US Medicare data.
• Advantages:
• Large population coverage
• Long-term follow-up possible
• Cost-effective (uses existing data)
• Useful for rare ADRs
• Disadvantages:
• Data quality varies
• Coding errors, missing information
• Confounding by indication
• Privacy and ethical concerns

3.6 Active Surveillance Systems

• Definition:
  Proactive collection of safety data (not passive like spontaneous reporting).
• Types:
• Sentinel systems (e.g., US FDA Sentinel Initiative)
• Disease/Drug Registries (e.g., pregnancy registries, vaccine safety monitoring)
• Advantages:
• Real-time monitoring
• Stronger causality
• Detects both common & rare ADRs
• Disadvantages:
• Very costly
• Resource-intensive
• Complex infrastructure needed

3.7 Meta-Analysis & Systematic Reviews

• Definition:
  Combine results from multiple clinical trials and observational studies to strengthen evidence.
• Advantages:
• Increased statistical power
• Resolves conflicting results
• More precise risk estimates
• Disadvantages:
• Dependent on quality of included studies
• Publication bias
• Heterogeneity between studies

4. Comparison Table

Method	Cost	Speed	Rare ADRs	Incidence Rates	Causality
Spontaneous Reporting	Low	Fast	✅ Good	❌ No	❌ Weak
Cohort Study	High	Slow	❌ Poor	✅ Yes	✅ Strong
Case-Control Study	Medium	Medium	✅ Excellent	❌ No	⚠ Fair
PEM	Medium	Medium	⚠ Fair	✅ Yes	⚠ Fair
Record Linkage	Low–Med	Fast	✅ Good	✅ Yes	⚠ Fair
Active Surveillance	High	Fast	✅ Good	✅ Yes	✅ Strong

5. Challenges in PMS

1. Statistical Issues:
• Confounding
• Missing data
• Small effect size detection
2. Regulatory Issues:
• Lack of harmonization globally
• Delayed regulatory action
• Uncertainty in signals
3. Methodological Issues:
• Causality difficult to establish
• Multiple drugs, multiple comorbidities
4. Practical Issues:
• Under-reporting
• Poor data quality
• Privacy & ethical concerns
• Limited resources in LMICs

6. Future Directions

1. Big Data & AI/ML → predictive safety analytics, real-time ADR signal detection.
2. Patient-Reported Outcomes → mobile apps, social media monitoring.
3. Pharmacogenomics → genetic predisposition to ADRs.
4. International Collaboration → global databases (e.g., VigiBase).
5. Integration with EHR & IoT → automatic ADR detection from routine care data.

7. Regulatory Framework

• ICH Guidelines (E2A–E2E) → cover expedited reporting, risk management, and pharmacovigilance planning.
• Good Pharmacovigilance Practices (GVP, EU) → structured safety monitoring guidelines.
• National Programmes:
• US: FDA Sentinel, MedWatch
• EU: EMA EudraVigilance
• India: PvPI (launched 2010, coordinated by IPC Ghaziabad)

8. Conclusion

• PMS is critical for drug safety throughout its lifecycle.
• Each method has strengths & limitations.
• Combination of methods provides best surveillance.
• The future lies in AI, genomics, digital health, and global collaboration for proactive and efficient pharmacovigilance.

PMS

Definition

🔹 Monitoring safety, efficacy & quality of drugs after approval → detect rare/long-term ADRs not seen in trials.

Objectives → DR CARE DL

• D → Detect new ADRs
• R → Risk quantification
• C → Compare drug safety
• A → Assess effectiveness
• R → Risk factor identification
• E → Evaluate long-term effects
• D → Drug utilization studies
• L → Look for interactions

Methods

1️⃣ Spontaneous Reporting (SRS)

• Eg: FAERS, VigiBase, PvPI
• ✅ Rare ADRs, cheap
• ❌ Under-reporting, no incidence

2️⃣ Cohort Study

• Exposed vs. unexposed
• ✅ Incidence, temporality
• ❌ Costly, large size, poor for rare ADRs

3️⃣ Case-Control Study

• Cases (ADR) vs. Controls
• ✅ Rare ADRs, quick
• ❌ Recall bias, no incidence

4️⃣ Prescription Event Monitoring (PEM)

• All patients on new drug tracked
• ✅ Denominator → event rates
• ❌ Depends on physician compliance

5️⃣ Record Linkage

• Connect EHR, claims, mortality data
• ✅ Large, long-term, rare ADRs
• ❌ Data errors, privacy issues

6️⃣ Active Surveillance

• Registries, FDA Sentinel
• ✅ Real-time, strong causality
• ❌ Expensive, resource-heavy

7️⃣ Meta-Analysis/Systematic Review

• Pool multiple studies
• ✅ High power, resolves conflicts
• ❌ Quality dependent, bias

Comparison Table

Method	Cost	Rare ADRs	Incidence	Causality
SRS	Low	✅	❌	❌
Cohort	High	❌	✅	✅
Case-Control	Med	✅✅	❌	⚠
PEM	Med	⚠	✅	⚠
Record Link	Low	✅	✅	⚠
Active Surv.	High	✅	✅	✅

Challenges

• Statistical → confounding, bias
• Regulatory → slow, non-uniform rules
• Practical → under-reporting, privacy, cost

Future

• AI/ML → predictive safety
• Genomics → personalized ADR risk
• Apps/IoT → real-time patient reporting
• Global databases → VigiBase, Sentinel

Regulatory Bodies

• US → FDA Sentinel, MedWatch
• EU → EMA (EudraVigilance)
• India → PvPI (IPC Ghaziabad)
• ICH → E2A–E2E, global harmonization