RPA Overview

Automating manual tasks with robotic process automation services (RPA) can hugely benefit the Pharma industry by being a game changer. RPA (or software bot) emulates transactional, administrative tasks which are repetitive, rules-based and require no decision making or strategizing.

Using robots to drive tangible business benefits is very much a reality today: The IT-enabled RPA market has been growing rapidly at a CAGR of 60.5% from 2014 and is expected to reach US$5 billion by 2020.

RPA is reshaping the Pharma industry’s value chain

The pharmaceutical industry needs to aim for a zero-tolerance methodology regarding mistakes or failure. Pharma companies can deploy RPA to thrive while eliminating tedious tasks.

Contrary to what one would expect in the R&D process of vital drugs, data handling tasks are mostly manual. This traditional approach comes with its fair share of trouble by being prone to human errors. Moreover, increasing regulatory control, the constant need for drug approval, and HR management expenses are making R&D costs shoot right through the roof. This has put the pharma industry in a tough spot and there is an urgent need to contain this rise.

RPA is of greatest value when used for rule-based, repetitive processes in drug development operations. Its use can support consistency in data entry, quality control and audit readiness in several targeted activities comprising clinical, regulatory, safety and laboratory operations.

Integra RPA can increase a biopharma’s future agility and work smarter using digital labor.

RPA’s ability to quickly integrate data to enable agility in complex environments make it a technology relevant to the middle and front office, too. Here are some of the many benefits RPA can provide in core industry processes across the Pharma value chain:

• Processing pharmacovigilance (PV) cases processing
• Managing trial master process
• Supporting regulatory submission process
• Recording sales activities and processes
• Retrieving accurate and timely sales data anytime
• Providing real-time tailored knowledge to customers
• Acting as a virtual medical companion to patients
• Entering varying data sets into statistical databases
• Rebate/Chargeback Processing
• Verifying data quality upon completion of studies
• Monitoring protocol compliance
• Clarifying data anomalies
• Designing data collection methods