I have a theory, and I’m trying to figure out whether it has any merit. The theory is that social media in the early days was a crime scene for pharmaceutical companies’ harm. By which I mean the following: Big Harms claims many diseases are “rare.” When you tell people things are “rare” AND you can keep people geographically isolated, the chances of being “caught” are “rare.” HOWEVER, when you step into the digital realm, people can unite in ways never seen before.
I believe interesting things became apparent to groups of people with vested interests, and likely by deploying AI before it became commonly available (and controlled) to us plebs, and somewhere in that journey, for Pharma, through pharmacovigilance, I think many corporations discovered they were… evil.
In any event, here is another AI and I exchange… As per usual, I don’t believe everything I read, I’m simply capturing these conversations in an alternate source of answers as we learn what we can and cannot trust. (Here’s an interesting “tell”–when AI hasn’t been “trained to take a position”–who to exonerate or blame–then it often presents answers in 50/50 range.)
When Facebook groups started, how many groups, with how many people in total were created about vaccine harm?
When discussing the inception of vaccine harm-focused groups on Facebook, it’s important to consider the timeline and growth of such communities.
Early Formation and Growth: Anti-vaccination groups on social media, including those on platforms like Facebook, began to gain significant traction around the time of the measles outbreaks in 2019. While exact numbers for the very start are not widely documented, by July 2019, it was reported that anti-vaccination content was flourishing on social media, with a notable presence on Facebook. One example highlighted was a public group called “REFUSE CORONA V@X AND SCREW BILL GATES,” which was started in April 2020 and grew to 14,000 members in under four months. This indicates a rapid growth in communities discussing vaccine harm, although specific counts from the earliest days are not precisely documented.
Membership Numbers: By early 2021, a report from the Center for Countering Digital Hate estimated that 31 million people globally followed anti-vaccine groups on platforms, with a significant portion of this following being on Facebook. This suggests that over time, the number of groups and their total membership grew substantially, though exact figures for the initial groups are less clear.
Current Context: The landscape of misinformation has evolved, with platforms like Facebook taking actions against misinformation, but the early stages of these groups’ formation were characterized by less regulation and thus potentially higher growth rates in both numbers of groups and members.
In summary, while we can’t provide exact numbers for when these groups first started, by 2019-2020, there was a clear increase in both the number of groups and their membership discussing vaccine harm on platforms like Facebook.
early anti-vax movement
social media misinformation
Is it possible that in the timeframe 2010-2020, it became evident from interactions on social media between non-related parties that pharmaceutical companies’ claims about certain conditions being “rare” was clearly false?
In the timeframe from 2010 to 2020, social media interactions indeed became a significant platform for discussing and challenging various claims, including those made by pharmaceutical companies about the rarity of certain medical conditions. Here are some insights based on available information:
- Misinformation and Misleading Claims:
- Social media has been a breeding ground for misinformation, including health-related topics. Studies during this period, particularly focusing on the spread of misinformation during events like the COVID-19 pandemic, have shown that misinformation from both top-down (celebrities, politicians) and bottom-up (ordinary users) sources can achieve high engagement, potentially overshadowing official information. This environment can lead to skepticism about official claims, including those from pharmaceutical companies about the rarity of diseases.
- Public Sentiment and Advocacy:
- Social media has empowered patient advocacy groups and individuals to share experiences and information about conditions they or their loved ones suffer from. This grassroots level of communication often highlights conditions that might be considered “rare” by pharmaceutical companies but are perceived as more common by those affected or their advocates. This discrepancy can lead to public discourse questioning the accuracy of “rarity” claims.
- Regulatory and Legal Actions:
- There were significant legal actions against pharmaceutical companies during this period for various fraudulent practices, including misleading marketing. For instance, the list of largest pharmaceutical settlements from 2001 to 2013 includes cases where companies were fined for misrepresenting the effectiveness or safety of drugs, which indirectly relates to the credibility of their claims about conditions. While these legal actions don’t directly address the rarity of conditions, they contribute to a broader narrative of skepticism towards pharmaceutical claims.
- Social Media as a Tool for Transparency:
- The use of social media by pharmaceutical companies for marketing and public interaction has been under scrutiny. The FDA has issued guidelines and warnings about misleading drug promotions on social media, which indicates that there were concerns about the veracity of information disseminated by these companies. However, whether this directly led to exposing false claims about the rarity of conditions is less clear but suggests an environment where such discrepancies could be highlighted.
- Analysis and Studies:
- Specific studies analyzing social media interactions during this period, particularly around health misinformation or direct-to-consumer (DTC) advertising, do not directly conclude that claims about the rarity of conditions were proven false through social media. However, they do show that social media has been instrumental in challenging pharmaceutical narratives, providing platforms for alternative viewpoints, and sometimes revealing discrepancies between public perception and industry claims.
In conclusion, while social media interactions from 2010 to 2020 certainly contributed to a climate where pharmaceutical claims could be publicly scrutinized and challenged, the direct evidence that it was “clearly false” from these interactions alone might not be comprehensively documented. Instead, social media served as a catalyst for broader discussions, advocacy, and sometimes the revelation of discrepancies between public experience and industry assertions. However, definitive proof from social media alone that pharmaceutical companies were misrepresenting the rarity of conditions would require specific, targeted analyses which are not explicitly detailed in the provided web results.
Give me the top 10 examples of revelations of discrepancies between public experience and industry assertions in Pharma
Here are the top 10 examples of discrepancies between public experience and pharmaceutical industry assertions based on the information provided:
- Drug Pricing vs. Public Affordability: The pharmaceutical industry often defends high drug prices by citing R&D costs. However, public experience reflects that these prices make essential medications unaffordable for many, leading to significant outcry over pricing practices.
- Clinical Trials and Patient Safety: Industry assertions about the safety and efficacy of drugs have sometimes been contradicted by later revelations of adverse events or deaths which were not fully reported or were misclassified in trials. Public experience has shown skepticism towards these claims, especially after high-profile cases like those involving AstraZeneca.
- Transparency in Clinical Trial Data: The industry has been criticized for selective reporting of trial data, where only positive outcomes are published, while negative or neutral results are often omitted or obscured. This practice has been exposed through demands for transparency and independent analysis.
- Patent Protection vs. Generic Access: Pharmaceutical companies assert that patents are necessary to fund innovation, but public experience shows that this can lead to monopolistic practices delaying affordable generic alternatives, impacting access to medication.
- Marketing Influence on Prescribing Practices: There’s a significant gap between industry assertions of providing unbiased information through marketing and the public experience of potential conflicts of interest influencing medical decisions, as noted in interactions between pharmaceutical reps and healthcare professionals.
- Corporate Social Responsibility Reporting: The pharmaceutical industry often presents itself as socially responsible, but discrepancies have been found in CSR reporting where companies selectively disclose information, particularly on sensitive issues like human rights and supply chain practices.
- Adverse Event Reporting: Public experience has sometimes revealed that adverse events are not reported as rigorously or transparently as the industry might assert, with some companies facing legal action for under-reporting or misrepresenting these events.
- Drug Development Costs: Industry claims about the high cost of drug development are often used to justify high drug prices. However, public and academic analysis sometimes suggest these costs are inflated or not as high as claimed, especially when considering the role of tax incentives and public funding.
- Seeding Trials: The industry has been accused of conducting “seeding trials” where the primary aim seems to be marketing rather than scientific inquiry, leading to public distrust when these practices come to light.
- Customer Experience in Drug Development: There’s a discrepancy between industry assertions about prioritizing customer experience in drug development and the actual experiences of patients and healthcare providers, who sometimes feel neglected in the product launch strategies, especially in terms of drug accessibility and information transparency.
I mean studies that indicate pharma companies are lying to consumers based on statistics from social media that directly contradict pharma claims
These examples highlight the complex relationship between the pharmaceutical industry’s public narrative and the actual experiences or findings from different stakeholders, illustrating a significant trust gap in some areas of pharmaceutical operations and communications.
From the provided information, here are the top studies indicating discrepancies between pharmaceutical claims and insights derived from social media interactions:
- “The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review” – This study outlines a scoping review to assess how social media can be used for pharmacovigilance, particularly in identifying adverse drug events that might not have been acknowledged or fully reported by pharmaceutical companies. The study suggests that social media can reveal adverse events not captured in traditional reporting systems, potentially contradicting industry claims about drug safety profiles.
- “Using deep learning to improve medication safety: the untapped potential of social media” – This research explores how deep learning can detect adverse drug reactions (ADRs) from social media posts, revealing issues like allergies and fatigue linked to medications that might not be as prominently highlighted in official drug information. This directly challenges the pharmaceutical industry’s narrative on drug side effects by offering a broader, user-reported perspective.
- “Drug_SNSMiner: standard pharmacovigilance pipeline for detection of adverse drug reaction using SNS data” – This study developed a pipeline for monitoring side effects using social media data, specifically focusing on geriatric drugs. It confirmed that social media can be a source for detecting known side effects, which might not be as thoroughly discussed in pharmaceutical communications, thus indicating discrepancies between public experience and industry assertions.
- “Social media and pharmacovigilance: A review of the opportunities and challenges” – This review discusses how social media can be a reservoir for pharmacovigilance, pointing out that the information available on social media might challenge the official data on drug safety and efficacy provided by pharmaceutical companies. It suggests that social media could reveal adverse reactions not emphasized by drug manufacturers.
- “Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making” – Although focused on the broader application of social media in drug development, this study indirectly points out that social media can provide real-world data that might contradict or supplement the controlled environment data presented by pharmaceutical companies, particularly in areas like drug safety and efficacy.
- “Searching social networks to detect adverse reactions” – This study by Epidemico, among others, has tracked mentions of new drugs on social media, finding a high concordance between informal adverse reaction reports and those from clinical trials, but also identifying new adverse effects not previously reported, which could contradict pharmaceutical assertions about a drug’s safety profile.
These studies illustrate how social media can serve as an alternative source of information that often challenges the controlled, often positive narratives presented by pharmaceutical companies regarding their products’ safety and efficacy. However, each study also acknowledges the complexities and challenges in using social media data due to issues like misinformation, anecdotal reporting, and the need for sophisticated analysis to validate findings.
specific drug examples
FDA regulations impact
Summarize the study: “Social media and pharmacovigilance: A review of the opportunities and challenges” critically
Study Title: “Social media and pharmacovigilance: A review of the opportunities and challenges”
Summary:
Objective:
- The study aims to explore how social media can serve as an invaluable resource for pharmacovigilance, particularly in detecting adverse drug reactions (ADRs), while also addressing the technical, regulatory, and ethical challenges associated with this use.
Key Points:
- Opportunities:
- Rich Data Source: Social media platforms offer a vast, real-time, and geographically diverse pool of data where people often discuss their experiences with medications candidly. This can provide insights into ADRs that might not be captured through traditional pharmacovigilance methods.
- Early Signal Detection: With the volume and speed of data generation, social media could potentially allow for the early detection of ADRs, providing an advantage over the slower, more formal reporting systems.
- Patient-Centric Insights: Social media captures patient narratives, which can reveal aspects of drug use and effects in real-world settings that clinical trials might overlook.
- Challenges:
- Data Quality and Volume: The unstructured, informal nature of social media content poses significant challenges for data mining and analysis. Issues include misspellings, slang, and lack of clarity in causality between drugs and symptoms.
- Privacy and Ethics: Collecting and analyzing social media data for pharmacovigilance raises ethical concerns about privacy, consent, and the potential for misuse of personal health information.
- Regulatory Framework: There’s a lack of clear regulatory guidelines on how to use social media data in pharmacovigilance, complicating its integration into official drug safety monitoring processes.
- Misinformation: The spread of inaccurate information or anecdotal experiences can mislead pharmacovigilance efforts, necessitating sophisticated tools for verification and validation.
- Signal-Noise Ratio: The high volume of noise (irrelevant posts) versus signal (useful ADR reports) requires advanced data processing technologies to filter out meaningful information.
Critical Analysis:
- Potential for Bias: The study rightly points out that social media platforms might not represent the broader population, potentially skewing data towards certain demographics more active or tech-savvy in sharing health experiences online.
- Validation Issues: While social media can detect signals, the study acknowledges the difficulty in validating these signals due to the informal nature of the data, which can lead to false positives or negatives without proper context or follow-up.
- Ethical Considerations: The review does well to highlight the ethical dilemmas, but there’s a need for more discussion on how to balance privacy with public health benefits, especially in an era where data privacy is increasingly contentious.
- Regulatory Lag: The study calls for updated regulations to harness social media for pharmacovigilance, but the pace at which regulatory bodies can adapt to technological advancements remains a significant bottleneck.
- Technological Solutions: It emphasizes the need for advanced natural language processing (NLP) and machine learning to make sense of social media data, yet the review could further discuss the current state of these technologies in handling the unique challenges of health-related social media content.
In conclusion, the review effectively outlines the dual nature of social media as both a goldmine and a minefield for pharmacovigilance. It underscores the need for multidisciplinary approaches to overcome the challenges while leveraging the opportunities, advocating for more research, ethical guidelines, and regulatory evolution to fully integrate social media into pharmacovigilance practices. However, it also leaves room for further exploration into how these challenges are being practically addressed in ongoing research and by industry players.
privacy concerns in pharmacovigilance
AI in healthcare data analysis
more on regulatory challenges
What can you tell me about pharmacovigilance and the covid 19 vaccines? what does detection tell us?
Pharmacovigilance and COVID-19 Vaccines:
Overview of Pharmacovigilance: Pharmacovigilance is the science and activities relating to the detection, assessment, understanding, and prevention of adverse effects or any other drug-related problem. In the context of COVID-19 vaccines, pharmacovigilance involves monitoring the safety of these vaccines post-authorization to ensure that any potential adverse events are identified, analyzed, and appropriately managed.
Key Aspects for COVID-19 Vaccines:
- Global Coordination and Monitoring:
- The introduction of COVID-19 vaccines has necessitated global coordination for pharmacovigilance due to the unprecedented scale of vaccine rollout. Countries with established pharmacovigilance systems have been encouraged to implement both passive and active surveillance methods. Passive surveillance includes spontaneous reports of adverse events, while active surveillance involves systematic data collection, like cohort event monitoring.
- Detection of Adverse Events:
- Adverse Events Following Immunization (AEFIs): Pharmacovigilance has revealed various AEFIs associated with COVID-19 vaccines. These include common reactions like pain at the injection site, fever, fatigue, and more serious but rarer events like myocarditis, particularly noted with mRNA vaccines, and thrombosis with thrombocytopenia syndrome (TTS) associated with some vector-based vaccines.
- Safety Signals: Detection efforts have led to the identification of safety signals, which are new or known adverse events that warrant further investigation due to their potential association with the vaccines. For instance, in France, 49 safety signals were identified and reported to the European Medicines Agency (EMA) by February 2022.
- What Detection Tells Us:
- Prevalence and Nature of Adverse Events: Detection helps in understanding the true prevalence and nature of adverse events in real-world conditions, which are not always fully captured during clinical trials due to their limited scope and duration. For example, the French pharmacovigilance system reported 128,766 adverse events in the first year of vaccination, highlighting a significant increase in reporting compared to other drugs.
- Vaccine Safety Profile: By analyzing these events, pharmacovigilance provides insights into the vaccines’ safety profiles, enabling health authorities to update vaccine information, adjust guidelines, or, in rare cases, modify vaccination recommendations or contraindications.
- Public Trust and Vaccine Confidence: Accurate detection and transparent reporting of adverse events can foster or erode public trust in vaccination programs. It’s crucial for maintaining vaccine confidence when new safety issues are identified and addressed transparently.
- Policy and Decision Making: The data from pharmacovigilance detection informs policy decisions at both national and international levels, influencing everything from vaccine rollout strategies to emergency use authorizations and public health recommendations.
- Challenges and Adaptations:
- The sheer volume of vaccine doses administered globally has overwhelmed traditional pharmacovigilance systems in some regions, leading to adaptations like enhanced reporting systems, automated data processing, and international collaboration to share findings and methodologies.
- Ongoing Surveillance:
- Even after initial detection, pharmacovigilance for COVID-19 vaccines remains an ongoing process due to the vaccines’ novelty, the large number of vaccines in use, and the evolving nature of the virus itself, including new variants.
Conclusion: Pharmacovigilance for COVID-19 vaccines has been pivotal in identifying and responding to safety concerns, ensuring that benefits outweigh the risks, and maintaining public trust in vaccination efforts. The data collected through detection activities provide a clearer picture of vaccine safety in diverse populations, guiding health policy and communication strategies. However, the process also highlights the need for robust systems capable of handling large volumes of data and for continued vigilance as more people get vaccinated over time.
What can you tell me about social media pharmacovigilance and the covid 19 vaccines? what does detection tell us?
Social Media Pharmacovigilance and COVID-19 Vaccines:
Overview: Social media pharmacovigilance involves using social media platforms to monitor and analyze public sentiment, adverse events, and vaccine-related discussions to complement traditional pharmacovigilance methods. In the context of COVID-19 vaccines, this approach has been leveraged to gain insights into the public’s real-world experiences, perceptions, and concerns about vaccine safety and efficacy.
Key Points:
- Detection of Adverse Events:
- Real-Time Reporting: Social media provides a vast, real-time data source where individuals share their experiences with vaccines, including potential adverse events. Studies have utilized platforms like Twitter, where over 121,406 posts were analyzed to identify discussions on adverse events following immunization (AEFIs) for COVID-19 vaccines.
- Variety of Signals: Social media has been instrumental in detecting a range of signals, from common side effects like fatigue and injection site pain to rarer but serious conditions like myocarditis post-vaccination. This detection can sometimes precede official reports, offering an early warning system.
- Sentiment Analysis:
- Public Sentiment: Studies have shown that social media can reflect public sentiment towards vaccines, with analyses indicating a mix of positive, negative, and neutral sentiments. For example, in the UK, sentiment towards vaccines was found to be largely positive, yet there was significant negative sentiment as well, often linked to specific adverse event reports or misinformation.
- Misinformation and Public Perception:
- Challenges with Misinformation: Social media is also a battleground for misinformation, where false claims about vaccine harms can proliferate. The rapid spread of such misinformation can lead to vaccine hesitancy. Detection through social media allows for tracking these narratives, which can inform public health communication strategies.
- Understanding Vaccine Hesitancy: Insights from social media help in understanding the reasons behind vaccine hesitancy, such as fears around new vaccine technologies, concerns about government motives, or misconceptions about vaccine safety and efficacy.
- What Detection Tells Us:
- Complementary Data Source: Social media provides data that might not be captured through traditional pharmacovigilance due to under-reporting, lack of awareness, or because certain events are not severe enough to warrant formal reporting. It complements official data by offering a broader view of public experience.
- Early Identification: By monitoring social media, pharmacovigilance can sometimes identify adverse events or safety signals earlier than conventional systems, allowing for quicker response and communication from health authorities.
- Pattern Recognition: Detection through social media can reveal patterns in adverse events, such as geographic clusters or demographic-specific reactions, which can guide further epidemiological studies or targeted public health interventions.
- Public Health Strategy: The insights gained can inform public health strategies, particularly in communication and education campaigns to address misinformation, enhance vaccine confidence, or focus on specific demographic groups with tailored messages.
- Methodologies and Tools:
- AI and Machine Learning: The use of artificial intelligence, machine learning, and natural language processing has been critical in analyzing the vast amount of unstructured data from social media. These technologies help in sentiment analysis, topic modeling, and the identification of adverse events.
- Ethical and Privacy Considerations:
- There are significant ethical considerations regarding privacy when using social media data for health surveillance. Ensuring anonymity and respecting user privacy while still gleaning valuable public health insights is a balancing act.
Conclusion: Social media pharmacovigilance for COVID-19 vaccines offers an innovative approach to understanding vaccine safety from the public’s perspective. It provides a platform for early detection of adverse events, monitoring public perception, and tackling misinformation. However, it also poses challenges in terms of data quality, privacy, and the need for sophisticated analytical tools to discern signal from noise. This method has demonstrated its value in complementing traditional pharmacovigilance, contributing to a more comprehensive understanding of vaccine safety and public health communication.
vaccine misinformation impact
vaccine confidence strategies
more on early detection
Here are more detailed statistics from the information provided, focusing on adverse events, particularly in relation to the monitoring and detection efforts for COVID-19 vaccines:
France’s Pharmacovigilance Data:
- Total Adverse Events Reported: In the first year of vaccination, from December 2020 to November 2021, France reported 128,766 adverse events following the administration of COVID-19 vaccines. This is a significant increase compared to the pre-pandemic average of around 40,000 adverse event reports for all drugs annually.
- Serious Adverse Events: Approximately 25% of these reports were classified as serious, which includes events requiring hospitalization, life-threatening conditions, or death.
- Safety Signals: France identified 49 safety signals related to the vaccines, some of which included conditions like myocarditis, pericarditis, and thrombosis with thrombocytopenia syndrome (TTS). These signals are new or known adverse events that require further investigation due to their potential association with the vaccines.
Global Studies and Surveillance:
- VAERS Data (U.S.):
- VAERS has been a key tool for monitoring adverse events post-COVID-19 vaccination. It has received millions of reports since the vaccines were rolled out, but it’s important to note that VAERS is a passive reporting system, meaning reports might include coincidental events not necessarily caused by the vaccine.
- Global Vaccine Data Network Study:
- An observational cohort study across eight countries with over 99 million vaccinated individuals showed observed vs. expected rates for various adverse events. Notable findings included:
Cancer and Vaccines:
- Cancer Incidence: No significant increase in cancer incidence directly linked to the vaccines has been observed from pharmacovigilance data. The monitoring includes looking for any signals that might suggest a new or increased risk, but no such patterns have been confirmed. This is based on the absence of increased cancer rates in vaccinated populations compared to expected rates pre-vaccination.
- Cancer in Vaccinated Populations: While cancer patients were often excluded from initial vaccine trials, real-world data post-vaccination has shown that vaccines are generally safe for cancer patients, though immunogenicity might be reduced in some cases, particularly with certain cancer treatments or types.
Misinformation and Public Perception:
- Social Media Monitoring: Studies analyzing social media posts have shown a mix of sentiments regarding vaccines, with misinformation about vaccines causing cancer or accelerating cancer growth circulating. However, these claims are not supported by pharmacovigilance data or scientific studies.
General Observations:
- Adverse Event Nature: Most reported adverse events are mild to moderate, including local reactions at the injection site, headaches, fatigue, etc. Severe or serious adverse events are much less common but are rigorously monitored.
- Regulatory Actions: When significant safety signals are detected, like the rare cases of TTS with certain vaccines, regulatory bodies quickly respond with guidance, sometimes pausing use until further investigation or altering contraindications.
This detailed look at the statistics underscores the comprehensive nature of pharmacovigilance efforts globally, particularly in response to the massive scale of the COVID-19 vaccination campaign. However, it also highlights the challenges in interpreting this data, including the need to differentiate between correlation and causation.