Generative AI and Digital Workers: Accelerating Innovation in the Pharma Industry

Satish Shenoy
Regional vice president
Global AI strategy and
technology alliances
SS&C Blue Prism

The pharmaceutical industry is among the most highly regulated in the world, where transparency, traceability and precision are paramount. Even the smallest human error can have serious consequences. Forward-thinking pharmaceutical companies have turned to digital tools, business process automation and orchestration to drive digital transformation and streamline operations. Now, with the integration of Generative AI, they have an opportunity to elevate their efficiency even further, unlocking new levels of productivity and innovation.

McKinsey & Company estimates that generative AI could create between $60 and $110 billion in value each year for the pharmaceutical industry. A lot of this value would come from speeding up the process of discovering new drug compounds, helping to develop and approve them faster, and even improving how they're marketed. It’s a game-changer for the whole drug development process.

Digging through the data

Pharmaceutical companies are facing increasing pressure from new laws and regulations. Failure to meet regulatory requirements or legislation could result in financial and reputational loss in the billions.

It takes a total of nine to 12 years for an average drug to gain regulatory approval in the med and biotech industries. This includes discovery, testing, clinical trials, government review and finally appearing on the shelf.

Throughout the drug approval process, every piece of data—such as discoveries, emails, research papers and communications—must be meticulously recorded and digitally stored. This is especially critical during clinical trials and once the drug is in use. Any adverse patient events must be promptly reported by the pharmaceutical company, healthcare provider or pharmacist to meet regulatory requirements. Managing this involves storing terabytes of unstructured data, which must remain accessible and available to regulators or government agencies at any time.

Reports can come from various sources like emails, phone calls or electronic forms, and they need timely and accurate processing. Traditionally, it would take hundreds of people to manage the data capture process and exception handling–a mechanism separating abnormal data results. But relying completely on humans opens up the process to errors.

Gen AI can efficiently sift through vast amounts of unstructured internal and external data–such as records, emails, phone calls or text messages–and garner insights. This constant communication can be effectively managed with the aid of gen AI, ensuring timely and accurate responses.

A gen AI-driven approach is not limited to the initial stages of processes like drug discovery. It can extend beyond clinical trials to the everyday use of approved drugs. For example, digital workers (DWs) can provide versatile support in highly regulated environments. They can interact seamlessly with various systems, handle data collection, provide exception handling, and ensure human oversight when necessary. This flexibility is essential for regulatory compliance and process auditability, especially when government regulations require detailed reporting.

Gen AI could be integrated seamlessly with existing systems to automate this process. It could extract relevant information from reports, interact with regulatory bodies such as the U.S. Food and Drug Administration, and log every step for compliance.

End-to-end automation could offer significant benefits: speed, accuracy, and scalability. Digital workers perform repetitive tasks without errors, ensuring that reports are processed quickly and accurately. This is particularly important in industries where delays can have serious consequences.

Gen AI also supports multimodal capabilities, handling various types of data like text, images, and even audio. Digital workers are versatile and work with screens much like humans can, but also work with Application Programming Interfaces (APIs) and human inputs so captured data is more easily tracked and reported on, which is important when it comes to instant auditability. This broadens the scope of automation, allowing for more comprehensive solutions.

Digital workers can enhance transparency and traceability, crucial for industries with stringent regulations like pharmaceuticals. They can ensure that every step of the process is logged immutably, allowing for complete end-to-end traceability. This will be vital for audits, enabling companies to provide detailed records of all actions taken during a process. Should a government or regulator say ‘prove it’ when examining a process, digital workers would be able to do that and provide regulatory compliance. Ensuring comprehensive coverage and continued understanding and evolution throughout the lifecycle of a drug is crucial, and aids in maintaining consistent quality and compliance.

Future-proofing Big Pharma

In an environment where precision, transparency and traceability are non-negotiable, gen AI and digital workers offer solutions that can enhance operational efficiency and help ensure strict adherence to regulatory standards. With the ability to accelerate drug discovery, streamline data management and enable comprehensive audit trails, these advanced technologies can reshape the way pharmaceutical companies bring life-saving treatments to market.

The potential value is immense, with the Pharma industry poised to unlock billions in new efficiencies. Organizations that embrace this digital transformation will lead the charge into next-generation innovation, setting themselves up for success in an increasingly competitive market.

Satish Shenoy is regional vice president of global AI strategy and technology alliances for SS&C Blue Prism.