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Pharmacovigilance Comprehensive Concepts and Methodologies

B.Pharm 8th Semester PCI Syllabus – Core Systems and ADR Detection

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Pharmacovigilance Comprehensive Concepts and Methodologies
B.Pharm 8th Semester (PCI Syllabus) – Core Systems and ADR Detection
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Pharmacovigilance Comprehensive Concepts and Methodologies
B.Pharm 8th Semester (PCI Syllabus) – Core Systems and ADR Detection
Pharmacovigilance Comprehensive Concepts and Methodologies1 / 38
Agenda and Learning Objectives
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    Understand the role of pharmacovigilance in global drug safety
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    Master ATC classification and its hierarchical structure
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    Explore ADR classification systems (Rawlins-Thompson and DoTS)
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    Learn DDD methodology and its applications in drug utilization studies
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    Dive into MedDRA terminology and its regulatory importance
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    Examine ADR detection methods and their strategic applications
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Introduction to Pharmacovigilance
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What is Pharmacovigilance?
WHO Definition and Scope
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    Science of detecting, assessing, understanding, and preventing adverse drug effects
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    Goal: Ensure patient safety and promote rational drug use
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    Scope: Post-marketing surveillance, clinical trials, and risk-benefit assessment
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    Standardized systems (ATC, MedDRA, DDD) enable global tracking and comparison
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Why Pharmacovigilance Matters
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    Clinical trials cannot detect all ADRs due to limited sample size and duration
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    Post-marketing surveillance uncovers rare, delayed, or chronic ADRs
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    Regulatory agencies rely on PV data for labeling updates and withdrawals
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    Public health impact: Prevents epidemics (e.g., thalidomide, opioids)
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Pharmacovigilance is the public health science that ensures the benefits of medicines outweigh their risks.
World Health Organization (WHO)
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Topic 1: ATC Classification System
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ATC Classification System Overview
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    Developed by WHO Collaborating Centre for Drug Statistics Methodology (Oslo, Norway)
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    Classifies active ingredients based on organ/system, therapeutic, pharmacological, and chemical properties
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    Global standard for drug utilization research and monitoring
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    Used in over 100 countries for PV, epidemiology, and health economics
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The ATC Classification System divides drugs into groups according to the organ or system on which they act and their therapeutic, pharmacological, and chemical properties.
WHO Collaborating Centre for Drug Statistics Methodology
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Strategic Objectives of ATC
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    Standardize drug nomenclature globally
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    Facilitate high-quality drug utilization research
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    Enable cross-border comparison of medicine consumption
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    Support pharmacovigilance by grouping drugs for ADR signal detection
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    Improve prescription auditing and pharmacoeconomic studies
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Core Principles of ATC Assignment
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    Hierarchical classification from anatomical system to chemical substance
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    One Drug, One Primary Code: Based on principal therapeutic indication
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    Exceptions for drugs with entirely different uses (e.g., topical vs. systemic)
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    ATC code does not imply efficacy, safety, or recommendation for use
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The 5 Hierarchical Levels of ATC
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Diagram of ATC hierarchy with levels 1-5 labeled (Anatomical → Therapeutic → Pharmacological → Chemical → Substance)
Diagram of ATC hierarchy with levels 1-5 labeled (Anatomical → Therapeutic → Pharmacological → Chemical → Substance)
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ATC Level 1: Anatomical Main Groups
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    A: Alimentary tract and metabolism
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    B: Blood and blood-forming organs
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    C: Cardiovascular system
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    D: Dermatologicals
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    G: Genito-urinary system and sex hormones
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    H: Systemic hormonal preparations
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    J: Anti-infectives for systemic use
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    L: Antineoplastic and immunomodulating agents
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    M: Musculoskeletal system
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    N: Nervous system
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ATC Level 1: Additional Groups
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    P: Antiparasitic products, insecticides, and repellents
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    R: Respiratory system
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    S: Sensory organs
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    V: Various (e.g., diagnostic agents, antidotes)
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    Note: Level 1 codes are single letters (A-V)
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    Each letter represents a broad anatomical or therapeutic category
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    Helps in quickly identifying the primary use of a drug class
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Decoding ATC: Metformin Example
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    ATC Code: A10BA02
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    A: Alimentary tract and metabolism (Level 1)
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    A10: Drugs used in diabetes (Level 2)
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    A10B: Blood glucose lowering drugs, excl. insulins (Level 3)
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    A10BA: Biguanides (Level 4)
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    A10BA02: Metformin (Level 5)
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Decoding ATC: Omeprazole Example
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    ATC Code: A02BC01
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    A: Alimentary tract and metabolism (Level 1)
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    A02: Drugs for acid-related disorders (Level 2)
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    A02B: Drugs for peptic ulcer and GORD (Level 3)
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    A02BC: Proton pump inhibitors (Level 4)
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    A02BC01: Omeprazole (Level 5)
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Applications of ATC Classification
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    Pharmacovigilance: Track class-wide ADRs (e.g., all A02BC PPIs)
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    Drug utilization studies: Monitor prescribing trends (e.g., rise in A10B diabetes drugs)
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    Pharmacoepidemiology: Population-based studies on drug exposure
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    Public health: Estimate national medicine consumption for policy planning
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    EHR integration: Automate drug-drug interaction alerts
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Advantages and Disadvantages of ATC
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    Universally accepted and standardized
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    Enables robust cross-country comparisons
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    Seamless integration with DDD methodology
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    Crucial for macroscopic drug utilization tracking
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    Rigid: One primary code per drug may not capture all uses
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    Requires updates as new drugs/indications emerge
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    Does not indicate safety, efficacy, or pediatric dosing
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    Complex for fixed-dose combination products
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ATC in Pharmacovigilance
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    Class effect detection: Group drugs to identify class-wide ADRs
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    Signal validation: Filter noise by grouping similar drugs in databases
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    Regulatory action: Quickly identify related drugs if one is withdrawn
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    Example: Withdrawal of rofecoxib (M01AH01) led to review of all COX-2 inhibitors (M01AH)
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Topic 2: Adverse Drug Reaction (ADR) Classification
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Defining an ADR
WHO Definition
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    A response to a drug that is noxious, unintended, and occurs at normal doses
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    Noxious and unintended: Separates ADRs from intentional overdoses or abuse
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    Normal doses: Distinguishes ADRs from toxicity due to overdose
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    Example: Hypoglycemia from insulin (normal dose) vs. coma from insulin overdose
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Purpose of Classifying ADRs
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    Mechanistic understanding: Explain why the reaction occurred
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    Predictability: Determine if the reaction could have been anticipated
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    Clinical management: Guide dose adjustment or discontinuation
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    Regulatory action: Inform labeling changes or market withdrawal
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Rawlins and Thompson Classification
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    Introduced in 1977 by M.D. Rawlins and J.W. Thompson
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    Initially categorized ADRs into Type A (Augmented) and Type B (Bizarre)
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    Later expanded to include Types C, D, E, and F
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    Most widely taught and clinically utilized system
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Type A (Augmented) Reactions
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    Dose-dependent, related to known pharmacological action
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    Common (80% of ADRs), predictable, low mortality but high morbidity
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    Examples: Hypoglycemia (insulin), bleeding (warfarin), GI ulcers (NSAIDs)
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    Management: Dose reduction or adjustment
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Type B (Bizarre) Reactions
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    Unpredictable, unrelated to pharmacological action
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    Rare, severe, high mortality, not strictly dose-dependent
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    Examples: Anaphylaxis (penicillin), Stevens-Johnson Syndrome (carbamazepine)
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    Management: Immediate and permanent discontinuation
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Type C (Chronic) Reactions
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    Result from prolonged, continuous drug therapy
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    Related to cumulative dose and duration
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    Examples: Cushing’s syndrome (steroids), tardive dyskinesia (antipsychotics)
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    Management: Gradual tapering or alternative therapies
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Type D (Delayed) Reactions
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    Appear months or years after treatment or in the next generation
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    Very rare, difficult to detect in trials, devastating consequences
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    Examples: Teratogenicity (thalidomide), carcinogenicity (chemotherapy)
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    Management: Long-term monitoring and risk communication
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Type E (End of Use) Reactions
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    Occur after sudden discontinuation or rapid tapering
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    Uncommon, predictable, preventable with proper tapering
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    Examples: Withdrawal seizures (benzodiazepines), rebound hypertension (clonidine)
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    Management: Reintroduce drug and taper slowly
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Type F (Failure of Therapy)
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    Unexpected failure of a drug to produce its intended effect
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    Common, often due to interactions, resistance, or genetic factors
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    Examples: Oral contraceptive failure (enzyme inducers), antimicrobial resistance
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    Management: Identify and address the underlying cause
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DoTS Classification System
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    Developed to address limitations of Rawlins-Thompson
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    DoTS: Dose-relatedness, Time-course, Susceptibility
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    Multidimensional approach considering drug and patient factors
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    More scientifically rigorous but complex
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Breaking Down DoTS
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    Dose (Do): Supratherapeutic, therapeutic, or subtherapeutic
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    Time (T): Time-independent or time-dependent (rapid, early, intermediate, late, delayed)
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    Susceptibility (S): Genetics, age, gender, disease states, exogenous factors
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    Example: HLA-B*1502 genotype increases susceptibility to SJS with carbamazepine
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Comparing ADR Classification Systems
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    Rawlins-Thompson: Simple, intuitive, clinically actionable
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    Pros: Directly informs management (dose reduction vs. discontinuation)
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    Cons: Oversimplified, many ADRs overlap categories
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    DoTS: Scientifically rigorous, patient-specific
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    Pros: Accounts for complex interactions (dose, time, susceptibility)
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    Cons: Highly complex, less intuitive for rapid clinical decisions
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Topic 3: Defined Daily Dose (DDD)
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Defined Daily Dose (DDD) Introduction
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    Statistical measure of drug consumption, not a recommended dose
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    WHO Definition: Assumed average maintenance dose per day for a drug’s main indication in adults
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    Maintained by WHO Collaborating Centre for Drug Statistics Methodology
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    Unit of measurement: Grams or international units (e.g., insulin)
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Objectives of the DDD System
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    Standardize drug consumption measurement globally
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    Enable cross-country comparisons of drug utilization
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    Track prescribing trends over time (e.g., antibiotic stewardship)
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    Assess impact of healthcare interventions or regulatory warnings
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Core Characteristics of DDD
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    Adult focus: Based on assumed average adult weight (70 kg)
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    Main indication: DDD assigned based on primary therapeutic use (ATC code)
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    Formulation independent: Standardizes active ingredient mass across formulations
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    Stability: DDDs rarely change once assigned, ensuring longitudinal consistency
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The DDD Formula
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    Drug utilization expressed as DDDs per 1,000 inhabitants per day (DID)
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    Formula: DID = (Total drug used × 1000) / (DDD × Population × Days)
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    Example: 10 DID = 10 out of 1,000 people received a standard daily dose daily
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    Allows comparison of drug use across populations and time
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Practical DDD Calculation Example
Metformin in a Hospital
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    Scenario: Hospital pharmacy calculates Metformin consumption for April (30 days)
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    Total Metformin dispensed: 30,000 tablets
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