Robotic Process Automation (RPA) is a suite of specialized computer programs that automate and standardize processes based on rules-based algorithms. There prevail limitless opportunities to leverage RPA coupled with other automation technologies to benefit industries like Life Sciences and Pharma.
The pharmaceutical industry is turning to technological solutions to save money and streamline the clinical trial process. This can be attributed to the rising healthcare costs, increased pressure to adhere to drug development regulations, and the greater need to process data in an unbiased, reproducible, and rapid way.
RPA bots can automate clinical tasks including patient matching and execute trial subject recruitment via initial virtual interactions that can rapidly gather potential subject information and designate qualified subjects. Clinical teams can continue the follow-up process after these automated interactions.
The clinical trial processes today, are driven by manual processes. RPA along with other advanced technologies holds the potential of impacting several touch points across processes, such as study startup, conduct, and closeout, and regulatory submissions as well.
Any clinical trial process has three phases: study planning and design phase, study startup phase, and study execution phase.
During the study planning and design phase, a significant amount of time is spent trying to gather information and in interpreting the different ways in which the critical protocol elements are defined. This often results in delays, errors, and sometimes both in the study planning and designing phase.
In the next phase, study startup, currently there is no link among the rules, transformation, and mappings between protocol parameters and e-CRF pages due to a lack of automation-based workflows between protocol authoring and electronic case-report forms (e-CRFs). This often leads to misaligned standards and metadata definitions across the main therapeutic areas.
During the study execution part, a lot of data elements are fed into the electronic clinical applications, and data from many sources is collected for the select observational studies. The amalgamation of such data sources depends on manual edit checks, often resulting in inconsistent signal detection, transcription errors, and assessment and narrative mismatches. Additionally, manual running of operations leads to spurious timing of key processes, during the study closeout phase.
These challenges provide an opportunity ripe for RPA and other intelligent automation technologies to provide practical solutions to address the clinical trial process.
With the combination of RPA, intelligent workflows, natural language processing (NLP), and cognitive agents, intelligent automation can remove inefficiencies from the manual processes. Depending on the use case, companies can leverage customized intelligent modules created using these elements separately or in combinations. RPA can add value proposition to the entire clinical trial process starting from the study design and startup phase to the study execution and completion phase.
During the study design phase, companies can use bot-based data checks and mappings with machine-readable study definition elements. They can create semantic relationships based on Bot-based ancillary standards using a graph database.
Likewise, in the study execution phase, companies can use a metadata-based transaction system with scripts and alerts to manage workflows across data collection, data management, and data submissions. The study closeout procedures, such as automatic database archival, bot-based data validation and cleanup, etc. can be performed using a bot-driven cascade and machine-readable instructions.
Companies can leverage RPA along with other automated technologies in patient matching, greatly reducing the need for manual intervention during patient screening. With an optimized clinical study process, companies can accelerate the time it takes for vital drugs to make their way from the laboratory to the pharmacy shelves.
RPA is a solid bet for pharma companies competing to add value to their clinical trials and roll our drugs at speed. If you are keen on leveraging RPA along with other automation technologies, but not sure where to start, PureSoftware can help you.
PureSoftware holds capabilities across the Drug Discovery process and has robust partnership with automation anywhere to provide an agile and customized solution to your needs. Explore PureSoftware’s service offerings in Life Sciences and RPA, and we can discuss your requirements. Reach to us now.