Social Media, Literature Search, Sponsor Websites – A Safety Source Data Integration Approach

I haven been part of my fair share of discussions on Drug Safety and Social Media. In fact, I have even written a blog post about how these two are being forced into an “arranged marriage”, which could be a good thing :-). While processing data from social media is very complex and often unreliable, there is increased push to process it anyway. Understandably, Marketing teams are the first to adopt social media channels in pharmaceutical organizations, now the drug safety teams are being forced to act as these channels could end up generating adverse events and they are obligated to register, review and report.

As mentioned, processing of data from social media could be complex and may yield very few cases (0.2% according to a Nielsen’s Online survey of health-related social media content) the high level process is very similar to Literature Scanning. The later is something that is already being handled by organizations. I think that the Social Media content search and analysis can becoming an extension to this process. Now lets look at both the processes.

Literature Search:

Literature Search is used by BioPharmaceutical organizations to identify Adverse Events related to their medicinal products in medical and scientific journals published worldwide. This process was adopted as a result of multiple serious adverse events and the ensuing regulations and increased safety concerns. Many sponsor organizations have successfully built automated systems to speed up the overall process. These systems typically scan sources (Journals, Abstract Libraries and Reference Libraries) based on certain keywords, product names, Boolean expressions etc. and capture the mentions into a local database. These entries are then screened by trained professionals to either accept or reject them based on the required data elements to qualify as an adverse event. If additional details are required, the journals are purchased and reviewed to qualify the “hit” as an adverse event. Once identified, this becomes a case that will then be transferred manually or electronically (e.g. E2B) to an Adverse Event Management System and will follow the life cycle till it is reported as an expedited or periodic report to regulatory authorities.

Social Media:

This process can be very similar to Literature Search except that the source of data is much more diverse and also the data is far less structured. Depending on the source system, a manual or automated process can be adopted to monitor and record the “hits”. If the source system is a “blog” or “Twitter” or “Facebook”, a tool can be build to continuously poll certain blogs, tweets or Facebook pages to scan for keywords, products/brands etc. The resulting “hits” can be processed to filter and aggregate the “trends”. These trends can then be reviewed by trained professionals to make a decision on whether they qualify as “Safety Cases” that will then be processed per the AE case management process.

Enterprise Websites, Response Centers etc.:

The third variety that may be considered as source systems for safety cases are Brand Websites and other portals setup to increase the brand awareness or assist the patients to receive medicine faster or address any questions and concerns. This may even include response centers setup for patients, pharmacists and physicians to reach the sponsors for information and advice. Depending on the nature of inquiries, these could be potential sources of Adverse Events. This data, once screened and qualified, can also be fed into the AE Management System for subsequent review and reporting purposes.

Source Data Integration:

From a technology standpoint the architecture and design for aggregation and analysis of data may differ for each of the datasets. However, an integrated approach to collecting, aggregating, analyzing and reporting of Adverse Event data needs to adopted by the sponsor IT organizations. The diagram below depicts:

  1. Multiple Source Categories and Systems (Literature, Social Media, Enterprise Websites)
  2. Multiple Interfaces  (Manual, XML, Text, API, RSS, Web Services etc.)
  3. Simple, High Level process to screen, record, review and report the case
Literature Scanning, Social Media & Enterprise Websites  - Safety Source Data Integration

Social Media Safety Source Data Integration

(To Be Continued…)

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About Venu Mallarapu

I am currently working as Associate Director at Cognizant Technology Services in their Life Sciences division. I have over 15 years of experience in developing IT Solutions and Services, specifically for Life Sciences industry for about 9 years. I have worked with small to large pharma customers to address various business requirements in R&D, Sales and Marketing areas. IT Service Management is one of my other passions. I blog and write about technology frequently and have also presented at various conferences and workshops on wide variety of topics in technology.

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  1. Does Clinical Data qualify as “Big Data”? « Venu Sez - March 26, 2012

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