4 Ways Medical Writers Can Benefit from NLG
By 2025, the global market for AI software in healthcare is set to exceed more than $8.1 billion. As this uptick in spending demonstrates, the use of Artificial Intelligence (AI) and Natural Language Generation (NLG) across life sciences has never been more necessary, or widespread.
As the race wages on to fast track drugs, vaccines, and cures, life sciences leaders are implementing underlying AI technologies to keep up. So, what does this mean for medical writers involved in the day-to-day analysis and interpretation of patient information?
Below are 4 ways medical writers can leverage AI and NLG technologies to streamline long-form content creation and analysis.
Faster report automation
A significant area of focus for medical writers is producing clinical study reports (CSR). A CSR is one of many types of regulatory documents that comprises an application submitted by a pharmaceutical company. Having the right data and documents to produce this CSR on time and accurately is critical.
A CSR can take weeks, and in some cases months, to complete. What the industry needs, then, is a way to reduce the time taken up by CSRs to cut costs, free up medical writers, and bring drugs to market in a much shorter time frame.
This is now available in the form of software tools powered by AI, that can automate the writing of repetitive and mundane sections of a CSR. In turn, implementing AI models augments the efforts of experienced professionals and allows them to focus on the more complex and demanding aspects of the job.
Medical writing is a high pressure and intensely skilled job, filled with mounting deadlines and real life altering scenarios. Often, writers are faced with overwhelming amounts of data and meeting targets that can lead to burnout, long hours, and time away from family.
At the end of a clinical study, clinical data must be analyzed in weeks. Often, this sheer volume of information can overwhelm the capacity for medical writers to make use of it. By leveraging NLG for medical writing, teams can leverage accurate data analysis removing the tedious and time consuming tasks out of their job. It makes writers faster, more accurate, and concise. It also leads to happier team members, able to focus on higher value initiatives that truly matter.
Streamline regulatory approval
Then there’s the job of simplifying regulatory approval. In an increasingly competitive and complex industry, life sciences firms need to provide full compliance and transparency into their data collection and analyzation processes. They need to satisfy the mandates and requirements of authorities, and AI delivers here too.
With more control comes increased accuracy all around and assists regulators in streamlining any investigations around clinical trials. When these two underlying fundamentals are in place, regulatory approval time becomes significantly faster. Medical writers simply don’t have to worry about getting flagged by the FDA due to an inadvertent mistake that could have been easily avoided in the first place.
Improve writing consistency
Another CSR issue is that with multiple medical writers working on a single report, it often results in clashing writing styles for a regulator to easily navigate. NLG facilitates a more consistent and cohesive writing style across the document.
According to Noemie Lagier, Project Manager at Yseop, “The CSR process sometimes requires decisions and information that only exists inside a medical writer’s head. By providing text customization options, NLG providers like Yseop empowers the medical writer to decide the level of analysis needed, within the same standard of writing.”
Given these benefits for medical writers and across industries, the immediate need to turn data into more powerful insights, it’s imperative for organizations to deploy AI and NLG technology to automate reports and improve clinical writing.
To learn more about how medical writers have accelerated drugs to market faster with AI, watch our webinar with Cognizant. We discuss a wide range of topics, including how to automate CSR writing with AI-based technologies. Watch here.