Tuesday 7 November 2017

Proactive pharmacovigilance through Social media data


Adverse drug events (ADEs) are a significant cause of morbidity and mortality worldwide. Clinical drug trials have limited ability to detect all ADRs due to various reasons: small sample sizes, relatively short durations, lack of diversity among participants usually excludes specific conditions: kids, elderly, pregnant women, patients with co-morbidities. Pharmacovigilance practice has evolved and grown more complex over the past 5 to 10 years due to higher data volumes, evolving regulations, increased influence of emerging markets and the emergence of social media and innovative technological advances. Social media is a promising source for new safety data and potential emergent safety signals.

Social media may be a method by which pharmacovigilance could be strengthened given that approximately 72% of internet users search for health information online. Social media have significantly expanded recently with Twitter and Facebook now registering over 300 million and1.4 billion active users, respectively. Social media have already been utilized in different domains illustrating their potential application to pharmacovigilance. A relatively new resource that can tackle the current surveillance systems is the user posts in:

Social health networks
Microblogs (e.g. Twitter)
Disease specific communities, and etc.
Millions of health-related messages can reveal important public health issues.

There may be several example user posts in social media:
Schizophrenia (indication) Risperdal did not suit me, had tremendous weight gain and my breasts were enlarged.

 Levaquin fetched me with Achilles tendon rupture. 

Reporting may have irregularities, spelling errors, misinterpretations and grammatical errors. Extraction of information could be done by various methods including medical records, user posts, blogs and health social networking sites: DailyStrength, PatientsLikeMe, MedHelp etc. Although this kind of post on social media does not resemble a traditional adverse drug reaction (ADR) report, pharmacovigilance experts are investigating whether this type of public information on Twitter, Facebook and on patient forums or blogs, might help regulators and pharmaceutical companies monitor the safety profile of medicines. It could be utilised in potential signal detection in post marketing surveillance if handled appropriately. 

Challenges:

1) Drugs may be described by their brand names, active ingredients, colloquialisms or generic drug terms (e.g. ‘antibiotic’).

2) May be referred to using creative idiomatic expressions or terms not found within existing medical lexicons. Consumers does not always use medical terms, instead they are using phrases, their own verbatim, descriptive symptom explanations and idiomatic expressions.

3) The existence of a side effect may be clear while the specific side effect experienced remains unclear.

4) Discussion of a drug could involve indications, beneficial effects or concerns of an adverse event. For example, there may be information with respect to benefits of drug or concerns associated with adverse events that might influence selection or rejection of drugs.

5) A minority of companies also utilize social media in patient engagement for marketing purposes or for recruitment and retention within clinical trials. The latter may cause significant difficulty if the subjects enrolled use social media for communication, as it may lead to the unblinding of investigational medicinal products including the product of interest, active comparators and/or placebo. 

6) Underreporting is common but there may be pattern of reporting bias observed such as patient suffering from impotence may be less likely to post this on a social media site. Rivalry among different Marketing authorization holders (MAHs) could result into notoriety bias as a result of publicity or because the drug has recently been introduced onto the market.

7) In a social media setting, patients are likely to be reporters themselves, without any confirmation of data from HCPs. Credibility and origin of these self-generated reports are key issues. These reports are reluctantly acceptable and need confirmation. Due diligence should be conducted for patients and reporters.   

8) The large amount and variety of information obtained via social media as well as its rapidly changing nature, makes it a typical big data problem.

Technical Challenges:

1. Identification of duplicate safety information with respect to data originating from digital media.
2. Multiple languages
3. Data privacy and personal data protection issues

Advantages: 

1) Mining data from social media gives us a greater chance of capturing ADRs that a patient wouldn’t necessarily complain about to their doctor or nurse. Physician could better diagnose problems and illness but patients can better relate to adverse events and reactions. For example, a psychiatrist can’t see suicidal ideation as an ADR while a patient can describe it perfectly.” 

2) Importance sampling: Patient groups such as pregnant women and children are often excluded from clinical trials due to concerns of teratogenicity and ethical issues yet they represent active social media users. So trend of events can easily be identified by using this medium. 

3) Sponsors within the industry are utilizing social media for commercial purposes to distribute information about diseases and their treatment, medicines and company like: 

The industry — e.g., costs of medicine
Their therapy — e.g., tolerance, adverse events, side effects
Their disease or condition — which is an opportunity for R&D to identify unmet needs
A particular company — e.g., its service and reputation
Competitors — so this can be a form of competitive intelligence

4) Social media sites are increasingly being adopted by healthcare professionals and patients for the discussion of adverse experiences with licenced medicinal product.

5) Social media presents new channels and methods that can enable companies to move away from traditional PV systems and safety reporting methods towards more patient-centric models for reporting, analysing and monitoring of safety data. These channels have the capability to allow swift and open communication between companies and the consumers/patients and healthcare providers using the medicinal products, thereby helping foster transparency and build public trust.

Conclusion:

To realize fully the benefit social media have to offer, requires careful combination of each of data sources or information to generate significant signals. Appropriate use of the internet and social media can prove to be a significant catalyst in the transformation of the PV practice in the not so distant future. Traditional PV methods will certainly prevail, yet social media has the potential to become an added new-age tool to monitor data in real-time, making it an early indicator of potential safety issues for further investigation. Further, this would enable companies to generate more robust product safety profiles by leveraging the additional social media information.

References: 

1. Utilizing social media data for pharmacovigilance: A review Accessed from http://www.sciencedirect.com/science/article/pii/S1532046415000362on 28-DEC-2015.

2. Searching social networks to detect adverse reactions Accessed from http://www.pharmaceutical-journal.com/news-and-analysis/features/searching-social-networks-to-detect-adverse-reactions/20067624.article on 29-DEC-2015.

3. Social media and pharmacovigilance: A review of the opportunities and challenges Accessed from 
http://www.researchgate.net/publication/279807301_Social_media_and_pharmacovigilance_A_review_of_the_opportunities_and_challenges on 01-DEC-2015.




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