{"id":8663,"date":"2017-05-16T02:52:09","date_gmt":"2017-05-16T02:52:09","guid":{"rendered":"https:\/\/arisglobal.com\/bkp-site\/?p=8663"},"modified":"2017-05-16T02:52:09","modified_gmt":"2017-05-16T02:52:09","slug":"automation-pharmacovigilance-data-processing-trust-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/","title":{"rendered":"Automation in Pharmacovigilance Data Processing \u2013 Do You Trust Artificial Intelligence?"},"content":{"rendered":"

Artificial intelligence (AI), machine learning, deep learning, natural language processing \u2013 in short, cognitive computing, is changing the pharmacovigilance world as we know it. While there\u2019s a lot of talk about how AI will affect jobs, where it will have the most powerful impact is on the quality of work and the speed at which manual tasks can be accomplished.<\/span><\/p>\n

This promises to be a game-changer for pharmacovigilance, decreasing the cost of case reporting and improving data quality to allow area experts to focus on where they truly add value, including signal detection in drug safety, pharmacovigilance analytics, and benefit-risk assessment.<\/p>\n

Repetitive and routine manual tasks such as adverse event case reporting<\/strong> can be automated and tackled by AI in a very sophisticated and seamless way. These tasks, for which we have coined the term \u2018pharmacodiligence<\/strong>‘ — in other words, the due diligence of collecting and processing data — are not strategic in the same way\u00a0as activities such as benefit-risk assessment.<\/p>\n

By building AI into the adverse event case processing<\/strong> and allowing pharmacovigilance resources to focus on strategic activities, life sciences companies will realize better outcomes. That\u2019s because safety departments can work smarter and faster with reliable data at their fingertips.<\/p>\n

That, in turn, means more time can be freed up for important activities such as benefit-risk assessment<\/strong> and more resources can be committed to higher human intelligence activities that are vital for the scientific interpretation of patient data.<\/p>\n

Building Trust in Pharmacovigilance<\/strong><\/h2>\n

One of the barriers to adopting AI and automation has been the \u2018trust factor.\u2019 Life sciences companies like the idea of AI, but they are concerned that automation won\u2019t produce the same outcomes as manual case processing.<\/p>\n

In reality, however, automation has come a very long way and is well entrenched in our lives in ways we may not realize. Think about flying. Auto landing systems were introduced to the aviation industry about 30 years ago and today all planes use automated landing systems. Let\u2019s face it, if you can trust your own life with automation in aviation, trusting your pharmacovigilance data to advanced automation should be less of a leap.<\/p>\n

Join ArisGlobal<\/a> at the UK Pharmacovigilance Day in London on June 6, 2017, where Vivek Ahuja<\/a>, Vice President, Global Pharmacovigilance will present on the topic of \u201cAutomation in Pharmacovigilance Data Processing \u2013 do you trust\u00a0Artificial Intelligence?<\/em><\/strong>\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

Artificial intelligence (AI), machine learning, deep learning, natural language processing \u2013 in short, cognitive computing, is changing the pharmacovigilance world as we know it. While there\u2019s a lot of talk about how AI will affect jobs, where it will have the most powerful impact is on the quality of work and the speed at which manual tasks can be accomplished.<\/p>\n","protected":false},"author":27,"featured_media":8664,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[67],"tags":[83,93],"class_list":["post-8663","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blogs","tag-arisglobal-blogs","tag-pharmacovigilance"],"acf":[],"yoast_head":"\nAutomation in Pharmacovigilance Data Processing \u2013 Do You Trust Artificial Intelligence? | ArisGlobal<\/title>\n<meta name=\"description\" content=\"By building automation into the adverse event case processing\/ reporting and allowing pharmacovigilance resources to focus on strategic activities, life sciences companies will realize better outcomes with reliable data at their fingertips\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Automation in Pharmacovigilance Data Processing \u2013 Do You Trust Artificial Intelligence?\" \/>\n<meta property=\"og:description\" content=\"By building automation into the adverse event case processing\/ reporting and allowing pharmacovigilance resources to focus on strategic activities, life sciences companies will realize better outcomes with reliable data at their fingertips\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/\" \/>\n<meta property=\"og:site_name\" content=\"ArisGlobal\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/LifeSphereAG\/\" \/>\n<meta property=\"article:published_time\" content=\"2017-05-16T02:52:09+00:00\" \/>\n<meta name=\"author\" content=\"Mladen Prenc\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Mladen Prenc\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/\"},\"author\":{\"name\":\"Mladen Prenc\",\"@id\":\"https:\/\/www.arisglobal.com\/#\/schema\/person\/bb2c7aafe44a090bcd667448651eb974\"},\"headline\":\"Automation in Pharmacovigilance Data Processing \u2013 Do You Trust Artificial Intelligence?\",\"datePublished\":\"2017-05-16T02:52:09+00:00\",\"dateModified\":\"2017-05-16T02:52:09+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/\"},\"wordCount\":401,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.arisglobal.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/#primaryimage\"},\"thumbnailUrl\":\"\",\"keywords\":[\"ArisGlobal Blogs\",\"Pharmacovigilance\"],\"articleSection\":[\"Blog\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/\",\"url\":\"https:\/\/www.arisglobal.com\/blogs\/automation-pharmacovigilance-data-processing-trust-artificial-intelligence\/\",\"name\":\"Automation in Pharmacovigilance Data Processing \u2013 Do You Trust Artificial Intelligence? 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