Many of the largest pharmaceutical companies have increasingly turned to business process automation and orchestration in recent years to support their digital transformation efforts and enhance operations.
The COVID-19 pandemic highlighted the importance of automation, showcasing the potential for rapid and accurate delivery.
A solid foundation has already been established with robotic process automation (RPA) integrating traditional AI capabilities into processes to boost intelligence and maximise return on investment (ROI). However, the emergence of generative AI (Gen AI) presents even greater opportunities.
We are collaborating with top pharmaceutical firms to pinpoint processes primed for innovation through Gen AI.
An area ripe for innovation is the drug approval process, which is just one use case that offers a glimpse into how Gen AI can drive further innovation across the industry.
The road ahead
Pivotal in the life-saving prevention of cardiovascular disease, aspirin is the most commonly used drug globally, seeing some 100 billion tablets sold worldwide. But have you ever considered what goes into researching wonder drugs that help manage everything from cancers to COVID-19?
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.
At each stage of the process, every single discovery, note, email, research paper and communication must be recorded and digitally stored.
This process is even more important during clinical trials and when the drug is in everyday use. Any adverse patient event must be recorded and reported in a timely manner by the pharmaceutical company, healthcare provider or pharmacist in compliance with regulatory requirements, with high severity events mandating government authority notification. Forever.
That’s terabytes of unstructured source data that must be easily accessible and available to regulators or government at a moment’s notice if required.
Brand damage and operational mistakes
The pharmaceutical industry is one of the most highly regulated industries in the world, where transparency and traceability is vital, and human error the biggest enemy.
For global brands producing well-known products and devices worldwide, and employing thousands, failure to meet regulatory requirements or legislation will result in financial and reputational loss in the billions.
But isn’t AI and machine learning only as good as the data it trains on? And isn’t it a massive risk to leave huge decision-making up to technology in its infancy.
Traditionally, you need 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.
Managing this on a 24-hour basis is challenging, especially since supplier queries are often unpredictable and ad-hoc.
Here, the combination of Gen AI can be an invaluable tool as it has the ability to quickly sift through unstructured internal and external data – such as emails, phone calls, fax, chat, or text messages – from suppliers and vendors and garner insights. This constant communication can be effectively managed with the aid of AI, ensuring timely and accurate responses.
Governmental reporting
This 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. Ensuring comprehensive coverage and continued understanding and evolution throughout the lifecycle of a drug is crucial, and aids in maintaining consistent quality and compliance.
When deciding where Gen AI will have the most impact, it’s important to be aware that it isn’t limited to just one stage of a process. 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.
In the pharmaceutical industry, adverse event reporting is a critical and highly regulated process. Reports can come from various sources like emails, phone calls, or electronic forms. These reports need timely and accurate processing to ensure patient safety. We’re looking at Gen AI to integrate 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.
This automated approach 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.
Physicians persona in Gen AI
COVID-19 demonstrated that with pandemics, pharmaceutical companies don’t have decades of time to spot anomalies – exception handling – within terabytes of data.
In scenarios like this, the value of Gen IA and Intelligent Automation (IA) is in its power to rapidly source and provide data, so the industry is better able to manage and respond faster to supply control issues and governance.
Additionally, by using Gen AI and DWs, firms could also reduce time-to-market for pharma products and improve transparency in their research, by searching and sourcing unstructured text, paper and voice data that come through various channels. This will not only safeguard patients but also protect the reputational and financial standing of organisations in a highly competitive and regulated market.
The use of Gen AI and digital workers can provide robust solutions for managing complex and regulated processes to enhance efficiency, accuracy, and compliance, revolutionising its research and development capabilities.
By leveraging a “physician persona” within the Gen AI platform, the pharma industry could also accurately classify adverse events more quickly, provide control and governance, and create personalised responses to patients or healthcare providers at scale.
Ensuring future stability
Advanced technologies such as Gen AI will mark a significant evolution in transforming how regulatory compliance and operational efficiencies are managed, if implemented correctly into the pharmaceutical industry.
In various industries, including healthcare; finance, and retail, integrating Gen AI solutions can enhance efficiency and scalability whilst ensuring adherence to strict regulatory standards.
By modernising data management and compliance practices, organisations can minimise human error and eliminate outdated procedures, paving the way for next generation innovations.
Satish Shenoy
Satish Shenoy is Regional Vice President of Technology Partnerships, Americas at SS&C Blue Prism. Known as the ‘Scaling Guy’, Satish is focused on supporting expansion and growth through partner ecosystems. He is a thought leader and expert on leveraging all things AI, automation, and customer experience to drive meaningful business outcomes.
