{"id":24062,"date":"2019-07-15T05:26:37","date_gmt":"2019-07-15T05:26:37","guid":{"rendered":"https:\/\/arisglobal.com\/bkp-site\/?p=24062"},"modified":"2019-07-15T05:26:37","modified_gmt":"2019-07-15T05:26:37","slug":"automation-in-pharmacovigilance-a-closer-look-at-use-cases","status":"publish","type":"post","link":"https:\/\/www.arisglobal.com\/blogs\/automation-in-pharmacovigilance-a-closer-look-at-use-cases\/","title":{"rendered":"Automation in Pharmacovigilance: A Closer Look at Use Cases"},"content":{"rendered":"

On June 5th, 2019, ArisGlobal held a webinar focused on the \u201cKey Use Cases of Automation in Pharmacovigilance<\/strong><\/a>.\u201d During that event, 84% of attendees indicated a significant increase in their case volumes over the last five years. Although the stage of planned or currently adopted levels of automation varied, attendees had some thoughts to share about where automation should be prioritized once adopted.<\/em><\/p>\n

In our June 2019 webinar \u201cKey Use Cases of Automation in Pharmacovigilance\u201d, Dr. Tims Thimmanna and Dr. Swati Nayak presented how automation addresses specific areas of PV-related changes \u2013 case intake, data entry, dictionary coding, duplicate check, follow up, narrative generation, causality assessment and submission. During the webinar, we asked respondents where their automation priorities were across the case processing workflow. The results were highly distributed, which reaffirmed our belief that automation can have a positive effect in many different places, as we\u2019ve seen from working on automation use cases directly with some of the industry\u2019s largest organizations.<\/p>\n

Indeed, robotic process automation (RPA) can be leveraged to automate manual, repetitive steps and is best used in cases where human intervention and decision-making is not typically required, whereas artificial Intelligence (AI) and its sub-categories can mimic human decision-making to read, interpret, and analyze source documents and determine the appropriate actions required. For example, natural language processing systems can be used in literature surveillance and review of medical literature. Image recognition systems can be useful in medical review and assessment of laboratory reports. Machine learning can be used in performing logical steps of case processing.<\/p>\n

Overall, these cognitive computing tools can augment the performance of a company\u2019s pharmacovigilance staff, reduce the volume of manual and repetitive tasks and allow a PV team to focus on more value-add activities.<\/p>\n

Which areas of PV are you most likely to automate?<\/h3>\n

DUPLICATE CHECKCASE INTAKENARRATIVE GENERATIONQUALITY CHECKFOLLOW-UP PROCESSINGEND-TO-END CASE PROCESSING<\/p>\n

(This is Blog Three in a Series of Three Blogs from the Key Use Cases of Automation in Pharmacovigilance Webinar.)<\/p>\n

To learn more about the insights shared and questions asked and answered, view the on-demand Key Use Cases of Automation in Pharmacovigilance<\/strong><\/a> webinar and read our white paper \u201cCognitive Computing in Pharmacovigilance: Revamping Drug Safety Using an Advanced Computing System<\/em><\/a>.\u201d<\/p>\n

We also invite you to register to attend a complimentary lunch-and-learn workshop on July 18th<\/sup> in Cambridge, MA. \u201cBuilding an Automation-Centric Approach to Drug Safety<\/strong>.\u201d During the two-hour workshop, Edwin Raj, Senior Director and Head of Safety Operations, AMAG Pharmaceuticals will share how they have replaced their legacy Argus system and are moving away from repetitive manual tasks by automating patient data collection from any source, which reduces errors and increases cost savings. Space is limited, so register soon if you are available to attend.<\/p>\n

Request a Demo<\/h2>\n","protected":false},"excerpt":{"rendered":"

Automation can have positive effects in many different areas, such as case intake, duplicate check, follow up, narrative generation, quality check or end-to-end processing. But which one are you most likely to automate? <\/p>\n","protected":false},"author":27,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[67],"tags":[],"class_list":["post-24062","post","type-post","status-publish","format-standard","hentry","category-blogs"],"acf":[],"yoast_head":"\nAutomation in Pharmacovigilance: A Closer Look at Use Cases | ArisGlobal<\/title>\n<meta name=\"description\" content=\"Automation can have positive effects in many different areas, such as case intake, duplicate check, follow up, narrative generation, quality check or end-to-end processing. 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