The Short Version
Robotic Process Automation (RPA) deploys software bots to handle the repetitive, rule-based, error-prone work that drains your team's time. In regulated life sciences, RPA can also reduce compliance risk by limiting human interaction with regulated data, but only when it sits inside a sound validation strategy. This RPA 101 covers what RPA is, what it can and can't automate, and where it fits in GxP workflows.
You Can Probably Name a Few Work Tasks You Dread Because They Are Repetitive and Time Consuming
To make matters worse, when you check a spreadsheet or database, you inevitably find data entry errors. Surely, in this day and age, there must be a way to automate menial but necessary tasks and know that they are getting done right. Right?
Say Hello to RPA
Robotic Process Automation (RPA) is software that acts like a robot (bot) to emulate how humans interact with digital systems to execute routine or repetitive business tasks. As the concept of RPA evolves, artificial intelligence (AI) can help automate complex processes and tasks, allowing AI robots to go from “execution” to “thinking” and predict possible outcomes or understand documents, images, and processing languages.
For now, let’s stick to the basics. RPA bots follow specific rules and use standard user interfaces to capture data and manipulate applications like humans do. They can interpret results, trigger responses, and communicate with other systems to perform repetitive tasks. RPA can take the work you hate off your plate. By automating some of the most cumbersome tasks, companies and their employees are able to focus on the high-value responsibilities within their roles.
Incorporating RPA into your workflows isn’t just about saving time, improving productivity, and ensuring accuracy; it can also reduce risk and compliance issues by limiting human interaction with regulated data.
RPA can take the work you hate off your plate — freeing your people to focus on the high-value responsibilities within their roles.
What Can You Automate?
A multitude of workplace tasks can be automated, but RPA does have a few limitations. For example, it must be a rule-based process that is not dependent on human judgement, and it requires structured data. Still, the potential use cases for RPA can go a long way toward greater productivity and fewer errors; they include, but are not limited to:
- Reading and writing to databases
- Opening emails and attachments
- Copying and pasting data
- Moving files and folders
- Scraping data from the web
- Communicating with other systems
- Connecting to system APIs
- Invoking an external process
- Extracting and processing data from documents, emails, and forms
Is a Task a Good Fit for RPA?
Before you point a bot at a process, test it against three quick criteria drawn from the points above:
- Rule-based. The process follows defined logic and does not depend on human judgement.
- Structured data. The inputs are consistent and machine-readable rather than free-form.
- Repetitive and high-volume. The task runs often enough that automating it returns real time and accuracy gains.
Processes that clear all three are the strongest candidates. Where automation touches regulated systems, pair this screen with disciplined oversight — see our perspective on citizen development and automation governance risks for life sciences.
RPA for GxP-Related Tasks
Developing a flexible, mature validation strategy can help you implement controls that support regulatory compliance, product safety, and industry competitiveness as they use automation to pursue efficiency, cost-savings, and innovation opportunities.1
- Streamline product labeling in manufacturing
- Process volumes of data on product quality and distribution
- Maintain official records required by predicate rules subject to inspection under FDA requirements
- Automate training assignments in your learning management system
- Identify high-risk abnormalities in images from radiology reports
Validate Before You Automate
In a GxP environment, an unvalidated bot is a compliance liability, not a productivity win. A risk-based approach — grounded in Computer Software Assurance (CSA) and aligned to 21 CFR Part 11 requirements for electronic records and signatures — keeps automation efficient and inspection-ready. Sustaining that validated state over time is exactly what USDM Cloud Assurance is built to support.
Case Study
Learn how USDM helped a Top 5 global pharmaceutical company with an artificial intelligence pilot program using their Azure tech stack and natural language processing tools to develop chatbots for GxP content that would support clinical trials.
There's More!
See Part 2 of this blog series for insight into how we are incorporating our RPA framework into GxP related tasks and workflows.
In Part 3, we’ll share lessons we are learning on this RPA framework learning path.
For more information on the beginnings of our automation journey, read this blog about our Lessons from the USDM Cloud Assurance Box GxP Automated Testing Tool.
On-demand webinar
Here's a sneak peek of information presented by Stepheni Norton and Jim Lyle during the How to Maximize Your GxP Use of the Public Cloud webinar.
Watch the full-length on-demand webinar: How to Maximize Your GxP Use of the Public Cloud
FAQ: Robotic Process Automation Basics
What is Robotic Process Automation (RPA)?
RPA is software that acts like a bot to emulate how humans interact with digital systems, executing routine or repetitive business tasks. The bots follow specific rules and use standard user interfaces to capture data and manipulate applications the way a person would.
What kinds of tasks can RPA automate?
Common use cases include reading and writing to databases, opening emails and attachments, copying and pasting data, moving files and folders, scraping data from the web, communicating with other systems, connecting to system APIs, invoking external processes, and extracting and processing data from documents, emails, and forms.
What are the limitations of RPA?
RPA has a few key constraints: the work must be a rule-based process that does not depend on human judgement, and it requires structured data. Tasks that hinge on subjective decisions or unstructured inputs are not good candidates without additional AI capabilities layered on top.
How does RPA help with compliance in regulated environments?
Beyond saving time, improving productivity, and ensuring accuracy, RPA can reduce risk and compliance issues by limiting human interaction with regulated data. In GxP settings, a flexible, mature validation strategy helps you implement controls that support regulatory compliance, product safety, and industry competitiveness.
Where can RPA be applied to GxP-related work?
Examples include streamlining product labeling in manufacturing, processing volumes of product quality and distribution data, maintaining official records required by predicate rules subject to FDA inspection, automating training assignments in a learning management system, and identifying high-risk abnormalities in radiology images.
Ready to Put RPA to Work in a Regulated Environment?
USDM helps life sciences organizations automate the right processes and keep them validated and audit-ready. Contact us to scope your RPA opportunities and see how automation stays inspection-ready as your program matures.