A division within the U.S. Food and Drug Administration (FDA), the Center for Drug Evaluation and Research (CDER) has currently seven RPA (Robotic Process Automation) projects in development as it works to free up staff for its core science mission. The center has used RPA for a year with plans to implement bots to Machine Learning and Natural Language Processing (NLP) for applications in regulatory review. CDER ensures safe and effective drugs on the market to improve the health of the people throughout their lifecycle.
While the FDA is recognized in the RPA space for automating drug intake forms and work within its chief financial officer’s office, CDER has quietly put several RPA use cases into production enterprise-wide. It regulates over-the-counter and prescription drugs, including biological therapeutics and generic drugs. The center has nearly 1,300 employees in review teams to assess and approve new drugs. Many of its employees have pharmaceutical science or medical degrees but find themselves in difficulties while performing tedious, manual administrative tasks.
CDER Informatics program management lead, Ranjit Thomas says, pharma sponsors must submit their plans to CDER – which receives thousands of applications a week – in order to market drugs in the U.S. or make changes to that strategy.
For this process, CDER’s bots ensure applications are complete before transcribing the information from PDFs to CDER’s system. Then the bots determine where to route new drug, investigation, and master file submissions among hundreds of workflows so reviewers and project managers have their assignments. And when a pharma company wants a unique identifier, bots assign those numbers.
CDER’s RPA to Save 24,000 Work Hours Annually
CDER envisages that its seven new RPA projects, which are in developing phase, will save 24,000 work hours annually, including those where bots schedule meetings and assign letters. For a year, the center has used RPA with plans to deploy bots to Machine Learning and Natural Language Processing (NLP) for applications in regulatory review. And in crucial situations, that bots would run the first triage of analytics on applications, according to Thomas.
However, RPA has some challenges as bots need authorities to operate (ATOs) within agency networks, wherein some agencies have gotten around by credentialing them like humans. But it does not sit well with every official.
CDER is selective here with its RPA projects to dodge such situations. According to Thomas, there are certain use cases the center come across where they have looked at bots but decided against using bots. For instance, archiving documents is a manual task, but CDER tracks who archives what in every instance. So, bots would not precisely represent the person archiving a document. It means, a bot couldn’t be held accountable, so the process wasn’t automated.
The Center for Drug Evaluation and Research (CDER) makes a vital public health task by ensuring that safe and effective drugs are available to improve the health of people in the United States. Its main objective is to make sure that all prescription and over-the-counter medications are safe and efficient when used as directed.