3. Please note: I am an employee of Pfizer. The statements or opinions expressed during this presentation are my own and do not necessarily represent those of Pfizer.
4. Michael A. Ibara mibara@mibara.com http://www.linkedin.com/in/ibara http://gplus.to/MikeIbara
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8. AGENDA History Issues Fundamental Causes Implications Solutions (long term / short term)
9. “Social Media” Web sites Social networking (e.g., Facebook, MySpace, LinkedIn, Google+) Wikis (Wikipedia) Blogs (web logs) Customer forums Micro Blogs (e.g., Twitter) Social bookmarking (e.g., digg) Location-based services (e.g., Foursquare) Virtual Worlds (e.g., Second Life) Patient Networking (e.g., PatientsLikeMe) by example…
17. Fallacy… Adverse event reports are not lilies in the field… there is not necessarily a finite number AE reports are the product of awareness and having a framework to observe them One of the determinants of the number of AE reports is how much news coverage the particular AE is getting So, the rate of AEs found by Nielson is not a rate set by nature, but a rate set by social interaction and awareness, and therefore subject to radical swings in frequency
18. A Rush to Judgment… Blindly applying the ‘four criteria’ points out a conceptual problem in the way social media is approached for safety What does it mean to have “an identifiable reporter”? In the ASTER Study, we identified reports by institution only, not individual reporter Another difficulty with the Nielson interpretation is understanding ‘triggers’ Triggers could be explicit (designed into a system) or implicit (occurrence of a news report) Triggers can greatly modify the reporting rate A third problem is assuming the workload is proportional to the final output, vs the raw output Nielson counted only “serious, unexpected, unlabeled’ AEs, but that’s not what companies will have to look at
22. Extrapolating Comparision Data of Forum Posts Forum Posts Reviewed: Randomly selected 500 posts from over 360,000 Identified 35 times the number found by Nielsen Online with identifiable patient, drug, reaction and reporter. Extrapolating for our current number of Forum Posts we calculate: 1,080,000 X .07 = 75,000 potential AE Patient Drug Reaction Reporter
23. Drug Safety Platform: Free-text data (excluding Forum) Free-text assessed for current clients: 9977 entries of free-text data For all drugs in our database 1500 entries contained an identifiable patient, drug, reaction and reporter Extrapolating to our current content: There are currently over 200,000 free-text entries (Bios, Comments, Advice/Tips) 200,000 x 0.15 = 30,000 potential AE Patient Drug Reaction Reporter
24. Total AERS Data Number of reports in FDA AERS by reporter since 2000
25. Potential AE Numbers from Forum Posts at 1 Million Members March 2009 June 2010 Number of Forum Posts
26. Proceedings of the 2010 Workshop on Biomedical Natural Language Processing ACL 2010, pages 117-125, Uppsala Sweden, 15 July 2010
27. “…we propose and evaluate automatically extracting relationships between drugs and adverse reactions in user posts to health-related social network websites.” Used DailyStrength health-related social network Automated web-crawler (‘scraped the data from the raw HTML) Lexicon created from four resources (UMLS, COSTART, SIDER, MedEffect) Annotated comments Used NLP techniques
28. Measuring the Coastline… “…the length of the coastline depends on the method used to measure it ‘Measuring’ adverse events in social media might be like measuring the coastline – the finer the instrument used, the greater the measurement… From Wikipedia: “Coastline paradox”
30. Issues Uncertainty… Who is responsible? What are they responsible for? What gets monitored? What is done with the findings? Workload More means more! Quality Is it any good? Improving public health Will this help us, provide any value?
33. There are established and evolving standards for exchanging safety informationOnce transaction costs drop, new business models will be possible The Hypothesis
34. ADE Spontaneous Triggered Electronic Reports David Westfall Bates, MD, M.Sc. Chief of the Division of General Internal Medicine at the Brigham and Women's Hospital; Professor of Medicine at Harvard Medical School and Professor of Health Policy and Management at the Harvard School of Public Health (Co-Director of the Program in Clinical Effectiveness) Jeffrey A. Linder, MD, MPH, FACP - PI of *ASTER Assistant Professor of Medicine, Harvard Medical School Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston MA
39. "Overall ASTER was well-accepted by the participating physicians, who felt it was unobtrusive and who saw the public health potential. “The clinicians, most of whom submitted no reports in the prior year - submitted over 200 reports in 3 months." Jeffrey A. Linder, MD, MPH, FACP Brigham and Women’s Hospital / Partners Healthcare PI on ASTER Study
40. Traditional ASTER Paper or separate site 36 minutes Several days or more 0 reports per physician 1 page of information At point of care 60 seconds 20 minutes (triaged) 5 reports per physician 7 pages of information
41. The underlying problem is that we’re using rules and regulations and concepts which were developed when data was hard to find… …but we’re trying to use them in a world that no longer matches the one in which they were developed
42. "A design representation suitable to a world in which the scarce factor is information may be exactly the wrong one for a world in which the scarce factor is attention.” Herbert Simon The Sciences of the Artificial p.144
43. We’ve got a safety (and regulatory) system built on sparse, hard to get safety data.But we’re entering a world of abundant, easy to get safety data.
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45. [further in…] “…the current pharmacovigilance legislative framework is unsuitable for today’s digital era…”
49. “Print newspapers like The New York Times have struggled with this whole internet thing, in which online users have come to expect free and immediate access to all kinds of information…”
51. “It was decided that an interpretation of copyright law enabling the music industry to sue for more money than they’ve made in the history of recorded music was necessarily wrong, and accordingly the damages were reduced to “a single statutory damage award from Defendants per work infringed, regardless of how many individual users directly infringed that particular work.”…”
55. …reconstruction of the field from new fundamentals… “The transition from a paradigm in crisis to a new one from which a new tradition of normal science can emerge is far from a cumulative process, one achieved by an articulation or extension of the old paradigm. Rather it is a reconstruction of the field from new fundamentals, a reconstruction that changes some of the field's most elementary theoretical generalizations as well as many of its paradigm methods and applications. During the transition period there will be a large but never complete overlap between the problems that can be solved by the old and by the new paradigm. But there will also be a decisive difference in the modes of solution. When the transition is complete, the profession will have changed its view of the field, its methods, and its goals.” Thomas Kuhn The Structure of Scientific Revolutions (1962), 84-5.
56. 4 elements vs 4 questions Identifiable Patient Identifiable Drug Identifiable Reaction Identifiable Reporter
57. What is safety data? Where does it come from? How do we get it? What can we do with it? Follow the data…
58. Cameron Neylon from the UK Science and Technology Facilities Council is quoted in the Nature article as saying that it makes much more sense to publish everything and filter after the fact. We are moving from a world of “filter then publish” to a world of “publish then filter.” [Italics mine]
59. We need to really educate ourselves on this if we hope to understand the implications What is it? Who uses it? How do they use it? What does it mean for safety?
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61. So what do we do? What we don’t do is take each case as a unique ‘one-off’ situation… Should we monitor/collect from web sites? Should we monitor/collect from Facebook? Should we monitor/collect from Twitter? O, that way madness lies…
62. I’m not saying we shouldn’t collect AEs in social media… I’m saying we need to call them something different than ‘serious’ or ‘nonserious’ AEs Maybe call them ‘Potential AE Lead Reports’ … This data clearly could be very valuable… …but this is where our old concepts clash with the new world
63. Even better.. Designate the information from social media as a ‘public good’ … Allow searching and matching of potential adverse event ‘pointers’ by pharma, academics, others, with no attempt to apply today’s regulations on reporting Reserve those regulations for specific programs a manufacturer runs on it’s drug … This could address not only collection issues, but data privacy issues as well
73. 1. Social Media is a symptom, not a cause, of what is wrong with safety 2. SM is both a new source of old data and a potential new source value 3. We are naturally predisposed to resist thinking this way - as is any established industry when it is threatened by a sudden shift in it's business model brought on by the digitization of its core business 4. We are now entering the era of abundant data in safety and it is bringing new business models 5. Solutions to this problem will require a paradigm shift which leads to a reconstruction of the field of pharmacovigilance from new fundamentals 6. This is creating a divide between those who see the world as it was and those who see the world as it could be 7. It is possible to begin working, however haltingly in this new paradigm for safety
74. Maynard Keynes (economist) said that … …“It is difficult to get a man to understand something when his salary depends on him not understanding it.”
