{"id":48507,"date":"2022-08-30T19:57:12","date_gmt":"2022-08-30T19:57:12","guid":{"rendered":"https:\/\/www.arisglobal.com\/?p=48507"},"modified":"2022-08-30T19:57:12","modified_gmt":"2022-08-30T19:57:12","slug":"approachable-automation-for-drug-safety-platforms","status":"publish","type":"post","link":"https:\/\/www.arisglobal.com\/blogs\/approachable-automation-for-drug-safety-platforms\/","title":{"rendered":"What Does Approachable Automation Mean for Drug Safety Platforms?"},"content":{"rendered":"

There\u2019s no doubt that the pharmaceutical industry is well into its \u2018age of automation\u2019. A 2021 Industry report<\/a> found that 83% of life science organizations use some form of automation across their R&D processes\u2014whether that be rule-based automation or technologies enabled by machine learning (ML), natural language processing (NLP), or artificial intelligence (AI). Now that automation is becoming an expected function of successful R&D strategies, organizations are tasked with finding the right method and level of automation to support their pharmacovigilance needs.<\/p>\n

To implement a successful automation strategy, organizations should not only consider the intended benefits, but also the time and resources required to implement and maintain the system. Failing to do so can drive up your total cost of ownership or lead to issues such as incomplete data, lack of visibility to data, complex or inflexible workflows. When the right tools and automation workflows are in place, however, the burden of implementation is lowered, and automation becomes an approachable tool to empower the next generation of pharmacovigilance.<\/p>\n

This article will define the concept of \u2018approachable automation\u2019 for drug safety platforms<\/a> and share how they can transform pharmacovigilance into a strategic business function.<\/p>\n

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Understanding the Spectrum of Automation<\/h2>\n

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Safety automation capabilities have expanded in recent decades with the introduction of smarter, more agile technology. When considering what capabilities would best benefit your pharmacovigilance efforts, it\u2019s best to think of automation as a spectrum.<\/p>\n

On one end of the spectrum are the structured, more repetitive tasks that rely on rule-based automation<\/strong>, such as automating duplicate data checks or establishing bulk case intake workflows. These often come pre-built in a safety system<\/a> and can be configured to minimize the impact of human error on data entry and increase staff efficiency. Rule-based automation optimizes common workflows, leading to a reduced cost of case processing as well as improved data quality. It also frees up staff resources to focus on more high-value tasks like risk mitigation or maintaining global compliance.<\/p>\n

Knowledge-assisted tasks<\/strong> \u2013 such as literature database screenings or causality assessments \u2013 require more mature forms of automation such as machine translation or natural language processing, that possess contextual intelligence. Organizations that need to process higher case volumes across larger global footprints benefit from knowledge-assisted automation because it scales to address increases in case volumes and can better handle structured or unstructured case sources.<\/p>\n

Finally, knowledge-based automation<\/strong> refers to mature cognitive systems such as AI, machine learning, or natural language generation. These automation tools are powerful for digesting large data sets and delineating them down into meaningful safety trends. Knowledge-based automation contains sophisticated algorithms that can perform tasks that typically require visual perception, cognitive reasoning, speech recognition, and decision-making. This intelligent automation is the most complex to implement in safety workflows<\/a>, but it can unlock insights into data sets related to patient safety or compliance that would otherwise take a significant investment of time and manpower.<\/p>\n

Knowing what level of automation best matches your safety needs can be challenging. This is where the concept of approachable automation becomes critical.<\/p>\n

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What is \u2018Approachable Automation\u2019?<\/h2>\n

With an ever-growing scope of automation workflows available across a multitude of drug safety platforms, how can organizations determine the level of automation and correct platform for them?<\/p>\n

The key is to focus on what makes automation approachable. Safety strategies are fluid and need to respond in real-time to changes in data volumes or new compliance regulations. Safety automation<\/a> needs to mimic this fluidness and therefore requires a level of flexibility, functionality, and approachableness to support teams in all situations.<\/p>\n

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What are the signs of approachable automation?<\/h2>\n