At present, FDA tracks those adverse events through a hybrid voluntary/mandatory reporting model which feeds data into its FDA Adverse Event Reporting System (FAERS). While pharmaceutical and biopharmaceutical companies are required to report all adverse events they are made aware of to FDA, doctors and patients only do so on a voluntary basis. The result of this system, FDA officials note, is that many side effects are under-reported, especially from patients who may not know how to report to FDA.
But even while FAERS sometimes falls short, it also has certain benefits. Each FAERS report contains extensive details about the adverse event, including an identified individual patient, the drug s/he took, his/her condition, whether they had any comorbid illness or were taking other medications, and a description of the event. But over the last few years, FDA has expressed interest in moving past individual reports about patient experiences and moving toward “big data” approaches. Last year, FDA proposed a new surveillance program within its Office of Clinical Pharmacology (OCP) known as the Pharmacological Mechanism-Based Drug Safety Prediction (PMDSP) program.
The program, according to FDA, was to mine data and recognize patterns through the use of technology in order to find as-yet unrecognized safety signals. As reported in Focus, the program has experienced several setbacks and does not appear to have launched yet. But while the PMDSP program was set to mine databases like the National Library of Medicine’s MEDLINE database of medical articles and launch as many as a dozen pilot projects, until now FDA has said little about data it might obtain from search giants like Google and Yahoo, even as it has expressed interest in leveraging “big data” approaches and used its 160-million patient “Mini-Sentinel” database to probe for adverse events.
Can Regulators Use Search Engine Data?
According to the authors of the research letter—Sirarat Sarntivijai and Darrell Abernethy, both fellows at FDA—the point of using a search engine is to generate hypotheses about drug safety. In other words, to raise questions about drug safety, not to answer those questions. “When a disproportionately strong association between an adverse event and a drug exposure is noted during ongoing analysis of FAERS data, it can be viewed as generation of a hypothesis,” the duo wrote in their article, Use of Internet Search Logs to Evaluate Potential Drug Adverse Events. Similarly, “hypotheses generated by use of Internet search logs could be viewed as yet another data source,” they said.
But Sarntivijai and Abernethy both conceded that search engine data is not quite as rigorous as existing approaches utilized by FDA, even if it does have its advantages. For starters, FDA just doesn’t have the same amount of experience dealing with internet search data as it does with its FAERS system. But more importantly, Sarntivijai and Abernethy noted that it can be extremely difficult to determine the true size and cause of an adverse event signal. For example, could a spike in people using Google to search for influenza vaccine side effects be the result of a new side effect, or might it be caused by the publication of an alarming news article containing decades-old information?
It’s hard to say, and the example isn’t hypothetical, either. The articles cites previous research in the field that found that Google’s previous “Flu Trends” product, which sought to determine the scope of a flu outbreak by measuring searches for flu-related terms, had “over-reported the transmission” of the virus by being unable to distinguish between actual reports and other information. Therefore, FDA—if it is to use search engine data—will have to figure out, paradoxically, how to use less data from its searches. Instead of treating every search query equally, it will have to determine which sources are worth listening to, and which to treat with more skepticism.
The Known Unknowns
And then there are simply the unknowns, the authors explain. “It is not at all clear how Internet search behavior would differ between instances of well-known drug–event pairs and potential pairs that have not been described in the news media and are not mentioned in available drug information sources,” they wrote. “That analysis is essential and will require prospective study.” And perhaps the biggest problem of all may well be validating the data. The authors note that FDA would have to track down individual patients to establish if “what was inferred using the Internet search log methodology is what actually happened.”
While that’s routine practice for FDA, it also means that so-called “big data” approaches won’t be a panacea for regulators, but simply a new starting point—a generator of drug safety hypotheses. So will we one day see FDA using these types of data to track down adverse events? The authors say such a move would seem to be “a step in the right direction,” even if some problems will need to be worked out prior to its use. For now, though, if you’re “feeling lucky,” you’re better off just communicating an adverse event to FDA the old fashioned way—through FAERS.
REFERENCE: RAPS Regulatory Focus; 29 JUL 2014; Alexander Gaffney, RAC
Kwa sasa, FDA inafuatilia matukio hayo mabaya kupitia mtindo wa ripoti ya hiari ya lazima ambayo inatoa data katika Mfumo wake wa Ripoti ya Matukio mabaya ya FDA (FAERS). Kampuni za dawa na biofarmacy zinapaswa kuripoti matukio yote mabaya ambayo yanajulikana kwa FDA, lakini madaktari na wagonjwa hufanya hivyo kwa hiari. "Mafunzo ya mfumo huu, maafisa wa FDA wanasema, ni kwamba athari nyingi za upande hazijarifiwa, hasa kutoka kwa wagonjwa ambao wanaweza kuwa hawajui jinsi ya kuripoti kwa FDA. """ Hata hivyo, wakati FAIRS inaonekana kuwa na faida kubwa, ni muhimu kuzingatia faida zake. Kila ripoti ya FAIRS ina maelezo ya kina kuhusu tukio lisilofaa, ikiwa ni pamoja na mgonjwa mmoja aliyetambuliwa, dawa aliyochukua, hali yake, ikiwa alikuwa na ugonjwa wowote wa comorbid au alikuwa akichukua dawa nyingine, na maelezo ya tukio hilo. Lakini katika miaka michache iliyopita, FDA imeonyesha nia ya kuhamia ripoti za kibinafsi za zamani kuhusu uzoefu wa mgonjwa na kusonga kuelekea mbinu za "data kubwa". Mwaka jana, FDA ilipendekeza mpango mpya wa ufuatiliaji ndani ya Ofisi yake ya Farmakolojia ya Kliniki (OCP) inayojulikana kama Programu ya Utabiri wa Usalama wa Dawa ya Farmakolojia (PMDSP). Programu hiyo, kulingana na FDA, ilikuwa kuchimba data na kutambua mifumo kupitia matumizi ya teknolojia ili kupata ishara za usalama ambazo bado hazijatambuliwa. Kama ilivyoripotiwa katika Focus, programu hiyo imepitia mapungufu kadhaa na haionekani kuwa imeanzishwa bado. "Lakini wakati programu ya PMDSP iliwekwa kwa madini ya database kama vile ""Medline"" ya National Library of Medicine ya makala za matibabu na kuzindua kama wengi kama miongo kadhaa ya miradi ya majaribio, hadi sasa FDA imeelezea kidogo kuhusu data ambayo inaweza kupata kutoka kwa wakubwa wa utafutaji kama Google na Yahoo, hata kama imeonyesha nia ya kutumia ""data kubwa"" mbinu na kutumika ""Mini-Sentinel"" yake ya mgonjwa milioni 160 kuchunguza matukio mabaya." Je, Watawala Wanaweza Kutumia Takwimu za Injini za Utafutaji? Kulingana na waandishi wa barua ya utafiti - Sirat Sarntivijai na Darrell Abernethy, wote wawili wenzake katika FDA - lengo la kutumia injini ya utafutaji ni kuzalisha nadharia kuhusu usalama wa dawa. Kwa maneno mengine, kuanzisha maswali kuhusu usalama wa dawa, si kujibu maswali hayo. "Wakati ushirika mkubwa sana kati ya tukio lisilofaa na mfiduo wa dawa unathibitishwa wakati wa uchambuzi unaoendelea wa data ya FAERS, inaweza kuonekana kama kizazi cha nadharia, ""wawili hao waliandika katika makala yao, Matumizi ya Rekodi za Utafutaji wa Mtandao ili Kutathmini Matukio ya Baadaye ya Dawa." Vivyo hivyo, "dhana zinazozalishwa na matumizi ya kumbukumbu za utafutaji wa mtandao zinaweza kuonekana kama chanzo kingine cha data", walisema. Lakini Sargentviji na Abernethy wote walikubali kwamba data ya injini ya utafutaji sio ngumu kama mbinu zilizopo zinazotumiwa na FDA, hata kama ina faida zake. Kwa ajili ya kuanza, FDA tu haina kiasi sawa cha uzoefu wa kushughulika na data ya utafutaji wa mtandao kama inavyofanya na mfumo wake wa FAERS. Lakini muhimu zaidi, Sarnevici na Abernethy waligundua kuwa inaweza kuwa ngumu sana kuamua ukubwa wa kweli na sababu ya ishara ya tukio lisilofaa. Kwa mfano, je, ongezeko la watu wanaotumia Google kutafuta athari za chanjo ya mafua inaweza kuwa matokeo ya athari mpya, au inaweza kusababishwa na kuchapishwa kwa makala ya habari ya kutisha yenye habari ya miongo kadhaa? Ni vigumu kusema, na mfano si nadharia, ama. "Kama ilivyoelezwa katika makala ya hivi karibuni, ""Mfano wa Flu Trends wa Google, ambayo ilitafuta kuamua wigo wa mlipuko wa homa kwa kupima utafutaji wa maneno yanayohusiana na homa, ilikuwa imeripoti zaidi ya maambukizi ya virusi kwa kutoweza kutofautisha kati ya ripoti halisi na habari nyingine.""" Kwa hiyo, FDA <unk>kama ni kutumia data injini ya utafutaji<unk>itakuwa na kufikiri nje, paradoxically, jinsi ya kutumia data kidogo kutoka utafutaji wake. Badala ya kutibu kila swali la utafutaji sawa, itabidi iamuke ni vyanzo gani vinavyostahili kusikilizwa, na ni vipi vya kutibiwa kwa kutilia shaka zaidi. The Known Unknowns Na kisha kuna tu unknowns, waandishi kueleza. "Haijulikani kabisa jinsi tabia ya utafutaji wa mtandao itatofautiana kati ya visa vya jozi za madawa ya kulevya zinazojulikana na jozi zinazowezekana ambazo hazijaelezwa katika vyombo vya habari na hazitajwi katika vyanzo vya habari vya dawa za kulevya, "waliandika. <unk>Uchambuzi huo ni muhimu na utahitaji utafiti wa baadaye.<unk> Na labda tatizo kubwa zaidi la wote linaweza kuwa kuthibitisha data. "Wanahabari wanasema kwamba FDA inapaswa kufuatilia wagonjwa mmoja-mmoja ili kuanzisha ikiwa ""kile kilichohamishwa kwa kutumia mbinu ya kumbukumbu ya utafutaji wa mtandao ni kile kilichotokea kweli"" wakati huo huo ni mazoezi ya kawaida kwa FDA, pia inamaanisha kwamba ""data kubwa"" haitaweza kuwa panacea kwa wasimamizi, lakini ni hatua mpya ya kuanza ""mzalishaji wa nadharia za usalama wa dawa." Je, siku moja tutaona FDA ikitumia aina hizi za data kufuatilia matukio mabaya? Waandishi wanasema hatua kama hiyo itaonekana kuwa "hatua katika mwelekeo sahihi", hata kama baadhi ya matatizo itahitaji kufanywa kabla ya matumizi yake. Kwa sasa, ingawa, kama wewe ni kuhisi bahati, wewe ni bora mbali tu kuwasiliana tukio hasi kwa FDA njia ya zamani njia kupitia FAERS. "Kama ilivyoelezwa katika ""Mtazamo wa Usimamizi wa RAPS"" (RAPS Regulatory Focus) 29 Julai 2014 na Alexander Gaffney, RAC"