Pharmacovigilance PDF

PHARMACOVIGILANCE Pharmacovigilance An essential component of pharmacy practice dedicated to the monitoring and assessment of adverse effects associated with pharmaceutical products Critical field that safeguards public health by identifying, evaluating, and mitigating the risks associat...

PHARMACOVIGILANCE Pharmacovigilance An essential component of pharmacy practice dedicated to the monitoring and assessment of adverse effects associated with pharmaceutical products Critical field that safeguards public health by identifying, evaluating, and mitigating the risks associated with medicinal products Pharmacovigilance Importance of Pharmacovigilance in Pharmacy Practice Ensuring patient safety Supporting regulatory requirement Enhancing therapeutic outcome Improving public health Advancing clinical knowledge Professional responsibility  Historical Background Of Pharmacovigilance Sulfanilamide Disaster (1937): In the United States, over 100 people died after consuming sulfanilamide elixir, which contained toxic diethylene glycol. This tragedy led to the enactment of the 1938 Federal Food, Drug, and Cosmetic Act, which required proof of safety before a drug could be marketed. Thalidomide Disaster (1960s): Thalidomide, a drug marketed for morning sickness in pregnant women, caused severe birth defects in thousands of babies worldwide. This catastrophe highlighted the need for rigorous drug safety monitoring and led to the establishment of stricter regulatory controls.  Historical Background Of Pharmacovigilance Establishment of the WHO Programme for International Drug Monitoring (1968): In response to the thalidomide disaster, the World Health Organization (WHO) launched the Programme for International Drug Monitoring. Objectives: To collect and evaluate data on adverse drug reactions from participating countries. To enhance the safety of medicines by identifying and analyzing new safety signals. Initially, 10 countries joined the program, which has now expanded to over 150 countries. VigiBase: The program operates VigiBase, a global database of ADR reports, which is managed by the Uppsala Monitoring Centre in Sweden.  Historical Background Of Pharmacovigilance Introduction of Spontaneous Reporting Systems: National spontaneous reporting systems were established in many countries, encouraging healthcare professionals and patients to report adverse drug reactions. Examples include the FDA’s MedWatch program in the United States (1993) and the Yellow Card Scheme in the United Kingdom (1964). Formation of Regulatory Frameworks and Guidelines: Various international guidelines and frameworks were developed to standardize pharmacovigilance practices. International Council for Harmonisation (ICH): Formed in 1990, ICH develops harmonized guidelines on the technical requirements for the registration of pharmaceuticals, including pharmacovigilance  Historical Background Of Pharmacovigilance Good Pharmacovigilance Practices (GVP): The European Medicines Agency (EMA) introduced GVP guidelines to ensure a consistent approach to pharmacovigilance across Europe. Advancements in Technology and Data Analysis: The advent of information technology revolutionized pharmacovigilance by enabling sophisticated data collection and analysis. Development of electronic health records (EHRs), pharmacovigilance software, and the use of artificial intelligence (AI) for signal detection and data mining. Drug Regulatory Authority of Pakistan (DRAP): The Drug Regulatory Authority of Pakistan (DRAP) is the primary regulatory body responsible for overseeing drug safety, efficacy, and quality in Pakistan.DRAP was established under the DRAP Act of 2012  Recent Developments and Future Directions Global Collaboration Enhanced collaboration between international regulatory agencies to improve drug safety monitoring. Initiatives such as the International Pharmacovigilance Network (IPVN) promote global harmonization and sharing of pharmacovigilance data. Patient-Centric Approaches: Increased involvement of patients in reporting ADRs through patient-centric platforms and mobile applications. Integration of Real-World Data: Utilization of real-world data (RWD) from sources like electronic health records, insurance claims, and patient registries to enhance pharmacovigilance activities.  Recent Developments and Future Directions Emerging Technologies: Implementation of advanced technologies such as machine learning, natural language processing, and blockchain to improve the efficiency and accuracy of pharmacovigilance processes.  National Pharmacovigilance Systems and Reporting Mechanisms in Pakistan Drug Regulatory Authority of Pakistan (DRAP): The primary regulatory body overseeing drug safety, efficacy, and quality. Responsible for implementing and coordinating pharmacovigilance activities across the country. National Pharmacovigilance Centre (NPC): Established within DRAP to manage the national pharmacovigilance system. Coordinates with regional centers and other stakeholders to collect, analyze, and act on ADR data. Regional Pharmacovigilance Centers (RPCs): Located in various regions to facilitate local reporting and monitoring. Aim to enhance the reach and effectiveness of pharmacovigilance activities at the regional level.  National Pharmacovigilance Systems and Reporting Mechanisms in Pakistan Drug Regulatory Authority of Pakistan (DRAP): The primary regulatory body overseeing drug safety, efficacy, and quality. Responsible for implementing and coordinating pharmacovigilance activities across the country. National Pharmacovigilance Centre (NPC): Established within DRAP to manage the national pharmacovigilance system. Coordinates with regional centers and other stakeholders to collect, analyze, and act on ADR data. Regional Pharmacovigilance Centers (RPCs): Located in various regions to facilitate local reporting and monitoring. Aim to enhance the reach and effectiveness of pharmacovigilance activities at the regional level. Reporting Mechanisms Reporting Mechanisms Reporting Mechanisms  ADR Reporting Mechanisms in Pakistan Who can report ADRs? Who Can Report ADRs? Healthcare professionals (doctors, pharmacists, nurses). Pharmaceutical companies (as part of their regulatory obligations). Patients and consumers. Methods of Reporting: Manual Reporting: ADR reporting forms available in healthcare institutions. Completed forms can be sent to the National Pharmacovigilance Centre.  ADR Reporting Mechanisms in Pakistan Electronic Reporting: Online submission through the DRAP website. Email submissions to designated addresses provided by DRAP. Mobile Applications: Apps designed to facilitate easy ADR reporting by healthcare professionals and patients Key Elements of an ADR Report: Patient information (age, gender, medical history). Details of the suspected drug (name, dosage, route of administration). Description of the adverse reaction (onset, severity, outcome). Reporter’s information (contact details, professional background).  Signal Detection and Management in Pharmacovigilance Signal detection in pharmacovigilance refers to the process of identifying new or rare adverse events (AEs) or changes in the frequency of known adverse events associated with a drug. A "signal" is defined as information that suggests a new, potentially causal association, or a new aspect of a known association, between a drug and an adverse event  Signal Detection and Management in Pharmacovigilance Process of Signal Detection: Data Collection: Collect adverse event reports from various sources, such as healthcare professionals, patients, clinical trials, and literature. Reports are stored in databases like VigiBase (WHO), FAERS (FDA), and EudraVigilance (EMA). Data Entry and Coding: Ensure that adverse event reports are accurately entered into the database. Use standardized coding systems such as the Medical Dictionary for Regulatory Activities (MedDRA) to classify adverse events.  Signal Detection and Management in Pharmacovigilance Process of Signal Detection: Data Analysis: Conduct regular reviews and analyses of the data to identify potential signals. Use both qualitative and quantitative methods to detect unusual patterns or trends. Signal Validation: Assess the clinical relevance and plausibility of the potential signals. Conduct further investigations, including literature reviews and consultations with clinical experts Signal Prioritization: Prioritize signals based on factors like the severity of the adverse event, the number of cases, and the public health impact.  Signal Detection and Management in Pharmacovigilance Process of Signal Detection Signal Communication: Communicate validated signals to relevant stakeholders, including regulatory authorities, healthcare professionals, and the public. Update product labels, issue safety warnings, or take regulatory actions if necessary. Signal Management: Continuously monitor the signal to gather more data and reassess the risk. Implement risk minimization strategies and evaluate their effectiveness  Causality Assessment in Pharmacovigilance Principles of Causality Assessment Causality assessment is the process of determining whether a suspected adverse drug reaction (ADR) is likely to be related to a specific drug. This assessment is crucial in pharmacovigilance to ensure accurate identification and management of drug-related risks. Temporal Relationship: The timing of the adverse event should coincide with drug administration. Dechallenge and Rechallenge Biological Plausibility: The ADR should be biologically plausible based on the known pharmacology and toxicology of the drug..  Causality Assessment in Pharmacovigilance Principles of Causality Assessment Consistency with Known Data: The ADR should be consistent with known adverse effects of the drug from clinical trials or post- marketing surveillance. Lack of consistency may warrant further investigation but does not rule out causality Alternative Explanations: Other potential causes (e.g., underlying diseases, other medications) should be considered and ruled out. Dose-Response Relationship: An increase in dose should correspond to an increase in the severity or likelihood of the ADR.  Causality Assessment in Pharmacovigilance Algorithms and Methods for Causality Assessment Naranjo Algorithm: A widely used tool for causality assessment that uses a questionnaire format with ten questions. Each question is scored, and the total score determines the likelihood of a causal relationship: Definite: Score > 9 Probable: Score 5-8 Possible: Score 1-4 Doubtful: Score ≤ 0.  Causality Assessment in Pharmacovigilance Algorithms and Methods for Causality Assessment WHO-UMC (World Health Organization - Uppsala Monitoring Centre) System: A standardized method used by WHO for global pharmacovigilance. Classifies causality into six categories: Certain: Clear evidence, including rechallenge, no other explanation. Probable/Likely: Reasonable time relationship, unlikely other causes, positive dechallenge. Possible: Reasonable time relationship, but could be explained by other factors. Unlikely: Time relationship improbable, other factors more likely. Conditional/Unclassified: More data needed. Unassessable/Unclassifiable: Insufficient or contradictory information.  Risk Management and Minimization in Pharmacovigilance Risk Management: Risk management in pharmacovigilance involves identifying, assessing, and mitigating risks associated with pharmaceutical products to ensure their safe and effective use. It is a proactive process designed to prevent or minimize adverse drug reactions (ADRs) and enhance patient safety. Risk Identification: Detecting potential safety concerns through clinical trials, post-marketing surveillance, and pharmacovigilance activities. Risk Assessment: Evaluating the severity, frequency, and impact of identified risks. Determining the benefit-risk balance of the drug.  Risk Management and Minimization in Pharmacovigilance Risk Mitigation: Implementing strategies to minimize identified risks. Risk Communication: Informing healthcare professionals and patients about the risks and safe use of the drug Risk Management Plans (RMPs) A Risk Management Plan (RMP) is a detailed document outlining the strategies for identifying, assessing, minimizing, and monitoring the risks associated with a drug throughout its lifecycle  Risk Minimization Measures (RMMs) Risk Minimization Measures (RMMs) are strategies implemented to prevent or reduce the occurrence of adverse drug reactions or to reduce their severity. Types of RMMs: Routine Risk Minimization Measures: Labeling Patient Information Leaflets Packaging  Pharmacovigilance in Special Populations Pediatric Pharmacovigilance Dosing and Formulation Adverse Drug Reactions (ADRs) Communication Geriatric Pharmacovigilance Polypharmacy Comorbidities Fraility Pharmacovigilance in Pregnant and Lactating Women  Pharmacovigilance and Herbal Medicines Lack of standardization Complex mixtures Limited regulatory oversight Under reporting of ADR  Safety Monitoring and Reporting in Clinical Trials Baseline Assessments: Collecting initial health data to identify pre-existing conditions and establish a baseline for comparison. Regular Monitoring: Scheduled assessments (e.g., physical exams, lab tests) to monitor participants’ health and detect AEs early. Using patient diaries and questionnaires to capture subjective symptoms. Adverse Event Recording: Documenting all AEs in detail, including onset, duration, severity, outcome, and causality assessment.  Safety Monitoring and Reporting in Clinical Trials Adverse Event Reporting: Serious Adverse Events (SAEs): Any event that results in death, is life-threatening, requires hospitalization or prolongation of existing hospitalization, results in persistent or significant disability/incapacity, or is a congenital anomaly/birth defect. SAEs must be reported to regulatory authorities, ethics committees, and sponsors within specific timelines (usually 24-48 hours for initial reports). Non-Serious AEs: Reported as part of regular safety updates and interim reports  Safety Monitoring and Reporting in Clinical Trials Development Safety Update Reports (DSURs): Annual reports providing a comprehensive overview of the safety profile of the investigational drug, including cumulative safety data and an assessment of the benefit-risk balance. Expedited Safety Reporting: Immediate reporting of unexpected SAEs (not listed in the Investigator’s Brochure) to regulatory authorities and ethics committees. Ensuring timely communication to all investigators involved in the trial. Safety Monitoring and Reporting in Clinical Trials Safety Monitoring and Reporting in Clinical Trials Safety Monitoring and Reporting in Clinical Trials Safety Monitoring and Reporting in Clinical Trials Pharmacovigilance and Information Technology Data Collection and Management Adverse Event Reporting Signal Detection and Analysis Regulatory Compliance Communication and Collaboration  Use of Artificial Intelligence and Machine Learning in PV Signal Detection: ML algorithms analyze large datasets to identify patterns and correlations indicative of new safety signals. AI-driven tools can process diverse data sources, including spontaneous reports, clinical trials, and social media. Case Processing: Natural Language Processing (NLP) extracts relevant information from unstructured data, such as clinical notes and patient narratives. AI systems automate the coding and classification of ADRs, reducing manual workload and errors.  Use of Artificial Intelligence and Machine Learning in PV Causality Assessment: ML models predict the likelihood that a drug caused an adverse event by analyzing historical data and known associations. AI systems provide decision support to pharmacovigilance experts, enhancing the accuracy of causality assessments. Predictive Analytics: AI and ML predict potential ADRs before they occur, enabling proactive risk management. Predictive models identify high-risk patient populations and guide targeted safety interventions.  Future Directions in Pharmacovigilance Personalized Medicine and Its Impact on PV Individualized Safety Monitoring. Personalized medicine necessitates monitoring ADRs specific to individual patient profiles. Pharmacovigilance systems must incorporate genetic and biomarker data to assess drug safety in specific subpopulations. Pharmacogenomics: Understanding genetic variations that influence drug response can predict and prevent ADRs. Integration of pharmacogenomic data into PV systems helps identify patients at risk for adverse reactions.