The COVID-19 vaccine approvals were expedited as an emergency response to the global pandemic. As with any other drug, the vaccines were required to undergo post-authorisation safety surveillance to monitor safety and efficacy data and collect additional information for vaccine use in wider populations, including pregnant women, persons with autoimmune disorders or comorbidities, etc. The pharmacovigilance plans for the COVID-19 vaccines faced several additional, compounded challenges: large-scale data collection, analysis and management and difficulty determining long-term side effects. These issues, compounding from clinician visits through data analysis, complicate the current process of detangling long COVID and vaccine side effects.
Symptoms or side effects?
Clinicians and health care professionals not only have to deal with the medical facts but also engage with patients that bring their own ideas, concerns and expectations to each visit. During the pandemic, there was incredible amounts of dis/misinformation saturating the news, social media and the internet at large. The novelty of the virus and the vaccine, the lack of a control group and the reporting challenges made it difficult for clinicians to identify between COVID, long COVID and vaccine side effects accurately. Clinicians had to comprehensively assess each patient through a diagnosis of exclusion to determine the cause, be it long COVID, vaccine side effects or comorbidity.
The industry relies on post-marketing reporting of side effects to continue safety surveillance. Still, the extensive analysis and examination required of clinicians combined with the overwhelming pressure put on healthcare systems as hospitalisations spiked during the pandemic led to further inconsistencies in reporting. There were cases early on when pericarditis was assumed to be coincidental, but with yellow card reporting, it was then included as a side effect and could be accurately monitored.
Difficulties in data collection
Collecting and assessing individual cases is critical in the greater pharmacovigilance process. These cases form the building blocks for broader aggregate analysis and understanding of the emerging safety profile, and the industry depends on reporting of adverse event reports by both clinicians and patients. However, neither party are obligated to do so, and both encounter obstacles to providing complete and accurate data. As mentioned, the overwhelming healthcare burden and lack of details for accurate assessment posed a reporting barrier for clinicians, while not all patients know their ability to report. If they are aware, patients may not know how to provide complete and accurate data. In addition, for physicians, the lack of feedback or acknowledgement of a report submission can be a demotivator to reporting. Despite these challenges, a vast amount of data is still available, though it may differ from database to database.
The vaccine’s safety surveillance had novel challenges in data collection based on the sheer volume of data available. Where other drugs may be administered to smaller groups or subpopulations, the COVID-19 vaccines were offered to all populations, not just those involved in the trials, to curb the rapidly worsening global pandemic. This means there is virtually no control group, and there is an immense pool of patients worldwide with important data – the next step is managing and analysing that data to provide actionable insights.
Big Data solutions
To facilitate data collection in addition to frontline case reporting from patients and clinicians, organisations launched data capture aids, like the CDC’s V-Safe, a post-vaccination health checker app for mobile phones. Data captured is then stored in associated databases, such as VigiBase, FAERs, VAERs or other registries that may differentiate between COVID-19 events in vaccinated versus unvaccinated patients to enable more accurate conclusions regarding vaccine safety. Identifying signals from multiple, large-scale datasets can be a complicated, time and resource-consuming process. However, automated solutions offer key opportunities for creating more routine data collection and more granularity and flexibility in data analysis.
ICON’s proprietary SIGNET technology is helping to tackle some of the data collection and analysis challenges by allowing for timely aggregation and pattern identifications within large databases. For example, starting with the VigiBase dataset containing more than 83 million rows of data, SIGNET identified cohorts of interest and provided interactive visuals that allowed for immediate appraisal and granular examination of the data using the generated details tables. We reviewed and analysed the data from multiple angles and intersected the criteria in different ways using the embedded and custom filters explicitly developed for the use case. We can thoroughly compare data from different cohorts, including vaccine-associated events and all patients with COVID-related symptoms. We can further divide and explore this data with clear visualisations to identify trends, but SIGNET can only provide as much detail as the data itself offers. The fast pace of development in the industry at the time meant there was no universal standardisation of coding in the data. As such, there are still missing elements, such as onset dates, limiting our ability to divine insights.
Conclusion
The dividing line between long COVID symptoms and COVID-19 vaccine side effects is not definitive – from patients’ and clinicians’ perspectives to insights mapped in several hundred-million-point databases, we are conducting good pharmacovigilance to develop a clearer picture of these afflictions. As the burden on the healthcare system has eased, we are collecting higher-quality case data and real world data from PASS. We are getting closer to answering whether these events are symptoms or side effects and are working towards insights in the near future.
For additional information on the challenges of assessing the long-term effects of COVID-19 vaccines and the details of the pharmacovigilance efforts, watch our on-demand webinar.
In this section
-
Digital Disruption
-
Clinical strategies to optimise SaMD for treating mental health
-
Digital Disruption whitepaper
- AI and clinical trials
-
Clinical trial data anonymisation and data sharing
-
AI at ICON
-
Clinical Trial Tokenisation
-
Closing the evidence gap: The value of digital health technologies in supporting drug reimbursement decisions
-
Digital disruption in biopharma
-
Disruptive Innovation
- Remote Patient Monitoring
-
Personalising Digital Health
- Real World Data
-
The triad of trust: Navigating real-world healthcare data integration
-
Clinical strategies to optimise SaMD for treating mental health
-
Patient Centricity
-
Agile Clinical Monitoring
-
Capturing the voice of the patient in clinical trials
-
Charting the Managed Access Program Landscape
-
Developing Nurse-Centric Medical Communications
- Diversity and inclusion in clinical trials
-
Exploring the patient perspective from different angles
-
Patient safety and pharmacovigilance
-
A guide to safety data migrations
-
Taking safety reporting to the next level with automation
-
Outsourced Pharmacovigilance Affiliate Solution
-
The evolution of the Pharmacovigilance System Master File: Benefits, challenges, and opportunities
-
Sponsor and CRO pharmacovigilance and safety alliances
-
Understanding the Periodic Benefit-Risk Evaluation Report
-
A guide to safety data migrations
-
Patient voice survey
-
Patient Voice Survey - Decentralised and Hybrid Trials
-
Reimagining Patient-Centricity with the Internet of Medical Things (IoMT)
-
Using longitudinal qualitative research to capture the patient voice
-
Agile Clinical Monitoring
-
Regulatory Intelligence
-
An innovative approach to rare disease clinical development
- EU Clinical Trials Regulation
-
Using innovative tools and lean writing processes to accelerate regulatory document writing
-
Current overview of data sharing within clinical trial transparency
-
Global Agency Meetings: A collaborative approach to drug development
-
Keeping the end in mind: key considerations for creating plain language summaries
-
Navigating orphan drug development from early phase to marketing authorisation
-
Procedural and regulatory know-how for China biotechs in the EU
-
RACE for Children Act
-
Early engagement and regulatory considerations for biotech
-
Regulatory Intelligence Newsletter
-
Requirements & strategy considerations within clinical trial transparency
-
Spotlight on regulatory reforms in China
-
Demystifying EU CTR, MDR and IVDR
-
Transfer of marketing authorisation
-
An innovative approach to rare disease clinical development
-
Therapeutics insights
- Endocrine and Metabolic Disorders
- Cardiovascular
- Cell and Gene Therapies
- Central Nervous System
-
Glycomics
- Infectious Diseases
- NASH
- Oncology
- Paediatrics
-
Respiratory
-
Rare and orphan diseases
-
Advanced therapies for rare diseases
-
Cross-border enrollment of rare disease patients
-
Crossing the finish line: Why effective participation support strategy is critical to trial efficiency and success in rare diseases
-
Diversity, equity and inclusion in rare disease clinical trials
-
Identify and mitigate risks to rare disease clinical programmes
-
Leveraging historical data for use in rare disease trials
-
Natural history studies to improve drug development in rare diseases
-
Patient Centricity in Orphan Drug Development
-
The key to remarkable rare disease registries
-
Therapeutic spotlight: Precision medicine considerations in rare diseases
-
Advanced therapies for rare diseases
-
Transforming Trials
-
Accelerating biotech innovation from discovery to commercialisation
-
Ensuring the validity of clinical outcomes assessment (COA) data: The value of rater training
-
Linguistic validation of Clinical Outcomes Assessments
-
Optimising biotech funding
- Adaptive clinical trials
-
Best practices to increase engagement with medical and scientific poster content
-
Decentralised clinical trials
-
Biopharma perspective: the promise of decentralised models and diversity in clinical trials
-
Decentralised and Hybrid clinical trials
-
Practical considerations in transitioning to hybrid or decentralised clinical trials
-
Navigating the regulatory labyrinth of technology in decentralised clinical trials
-
Biopharma perspective: the promise of decentralised models and diversity in clinical trials
-
eCOA implementation
- Blended solutions insights
-
Implications of COVID-19 on statistical design and analyses of clinical studies
-
Improving pharma R&D efficiency
-
Increasing Complexity and Declining ROI in Drug Development
-
Innovation in Clinical Trial Methodologies
- Partnership insights
-
Risk Based Quality Management
-
Transforming the R&D Model to Sustain Growth
-
Accelerating biotech innovation from discovery to commercialisation
-
Value Based Healthcare
-
Strategies for commercialising oncology treatments for young adults
-
US payers and PROs
-
Accelerated early clinical manufacturing
-
Cardiovascular Medical Devices
-
CMS Part D Price Negotiations: Is your drug on the list?
-
COVID-19 navigating global market access
-
Ensuring scientific rigor in external control arms
-
Evidence Synthesis: A solution to sparse evidence, heterogeneous studies, and disconnected networks
-
Global Outcomes Benchmarking
-
Health technology assessment
-
Perspectives from US payers
-
ICER’s impact on payer decision making
-
Making Sense of the Biosimilars Market
-
Medical communications in early phase product development
-
Navigating the Challenges and Opportunities of Value Based Healthcare
-
Payer Reliance on ICER and Perceptions on Value Based Pricing
-
Payers Perspectives on Digital Therapeutics
-
Precision Medicine
-
RWE Generation Cross Sectional Studies and Medical Chart Review
-
Survey results: How to engage healthcare decision-makers
-
The affordability hurdle for gene therapies
-
The Role of ICER as an HTA Organisation
-
Strategies for commercialising oncology treatments for young adults
-
Blog
-
Videos
-
Webinar Channel