Impact of robotic process automation, AI in pharma 

Digitalisation and emerging technologies have revolutionised the pharma industry. These technologies are very useful from the perspectives of quality and compliance, based upon Industry 4.0/Pharma 4.0 concepts. 

Robotic Process Automation (RPA) and Artificial Intelligence (AI) are no longer small operations as manufacturers are using these technologies to maximise quality and compliance. Many companies are already using AI to analyse huge scientific data in an effort to speed up and improve the drug discovery process. 

These technologies have new applications in diverse areas like regulatory/compliance, clinical trials, manufacturing, and supply chain. RPA automatically handles manual, repetitive, time-consuming, and highly structured tasks such as data entry, reviews and back-office functions. RPA solutions can improve regulatory compliance because bots do not deviate from programmed steps and audit trail history can be tracked. They provide comprehensive, unchangeable, and time-stamped activity logs, reducing risks and errors through the automatic execution of repetitive and routine manual activities. 

There are several applications of RPA/AI in the pharma industry from quality and compliance perspectives such as:

Data integrity compliance: Achieved through RPA audit trails review of various chromatography data generated during laboratory analysis. When reviews performed with RPA detect no anomalies, the reviews can autonomously be closed and logged by the bot. However, if the bot detects any inconsistency or discrepancy that requires human evaluation, RPA can be programmed to report the issue to one or more users before proceeding with the next steps of the process. 

Ensuring quality, predictive quality analytics (PQA): AI-enabled LIMS–QMS, automates time-consuming, error-prone, manual inspection tasks. Predicting the quality of a batch is another big advantage of newer technologies as they help to standardise quality monitoring processes. They analyse data, predict quality, deal with complaints handling process and make remedial suggestions to mitigate the risk of failure of a batch.

Clinical trials: AI and RPA are used to speed up the process of selecting the volunteers saving time from months to only a few days. AI is now being used in identifying the right candidate for clinical trials. Monitoring the pharmacovigilance activity is another area where RPA is of great advantage. It helps to monitor huge amounts of adverse event data, as well as enable necessary communications to report and accumulate such data. RPA solution utilises bots to substantially reduce data processing time, improve reliability and mitigate risk by eliminating errors and improving accuracy in trial documentation.

The regulatory documents submission process is a huge and time-consuming activity where RPA solutions can speed up certain required activities, such as document status tracking and creating a records dossier, thereby reducing process time.

Manufacturing: AI helps to reduce manual oversight in manufacturing and allows tighter control of quality and operating costs by assessing manufacturing data from multiple batches and product lines, identifying process anomalies and predicting quality issues. This can direct staff to investigate only those batches most likely to have quality issues, saving time and resources. It proactively identifies anomalies, prioritises compliance risks, and improves operational efficiency.

Sterile manufacturing: The applications in pharma manufacturing are vast, including aseptic roller bottle processing, multi-format aseptic filling, aseptic cytotoxic compounding, packaging, warehousing and distribution. Robotic production lines that can provide flexible aseptic filling and closing of ready-to-use vials, syringes, and cartridges with a single machine, resulting in overall production speed are necessary to remain competitive and cost-effective. Several benefits in sterile manufacturing like minimising human errors (like foreign matter, hair etc. contaminations), maintaining air velocity, and sterile conditions in core areas, RPA enables closed systems to eliminate all sources of contaminations.

Predictive maintenance: Maintenance is simpler due to fewer parts, and if done properly, can result in significantly longer lifespans. Robots facilitate ongoing maintenance by self-monitoring and using programmed alarm scenarios to alert operators of issues. AI is being used to predict the failure of equipment in the near future. As soon as an alarm is known, preventive actions start, thus ensuring zero downtime.

Packaging operations: Robotic automation is being used in packaging operations to minimise defects by way of in-line checks along with several cameras for separating defective tablets, capsules, empty strips pockets, defective blisters etc.

AI is being used in R&D drug discovery, clinical trials, manufacturing, quality control laboratory and supply chain. Automation is already transforming the pharma industry in areas like product development and real-time monitoring. Many companies are increasingly turning to robotic process automation as a solution allowing them to enhance productivity, quality, operational efficiency, and customer satisfaction. Overall, AI and robotics operations are a boon to the pharma industry in ensuring speed of product availability, quality, safety and efficacy of the products in the interest of patients. Pharma operations will be completely AI-enabled, AR + VR towards paperless plants in near future.