Earlier this year, the U.K. government announced £82.6 million ($102.2 million) in research funding for artificial intelligence (AI) companies engaged in developing solutions that accelerate drug development. The country is among the top five contributors to the global digital transformation in healthcare market, which is expected to grow from $86.03 billion in 2025 to more than $351 billion by 2035. Advanced technologies, including artificial intelligence and cloud computing, are transforming healthcare in the U.K., impacting every area, from research and drug discovery to diagnostics and patient management, to streamline operations, foster collaboration, improve disease detection, and enhance quality of care.
Companies, such as Astra Zeneca, are leading digitalisation. Its Evinova initiative, a separate health-tech business, aims to bring established digital solutions to market to optimise clinical trial design and delivery, reducing the time and cost of developing new medicines. This makes care more accessible and lessens the burden on the country’s healthcare system. However, big pharma is only one part of the U.K. digital health ecosystem – ranked Europe’s largest – which also includes specialist digital health companies and the National Health Service (NHS). Together, they connect research and patient through seamless data exchange, remote monitoring, and patient-centric innovation.
Despite this progress, the life sciences sector has been slow to adopt technological advancements. Hurdles include stringent regulatory regime and difficulties in accessing high-quality data. And while pharma companies are leveraging AI, even they need to ramp up adoption of digital technologies to improve productivity and competitiveness. Here are some options to consider:
Enhance drug development and clinical trials
Data processing is a major contributor to the cost and lead time of new drug development. Drug discovery and clinical trials can take over a decade, and only five out of ten thousand new drug candidates tested qualifying for clinical trial. Digital technologies like cloud, advanced analytics, and AI are revolutionising this process.
By leveraging cloud’s scalability and flexibility, U.K.’s pharmaceutical companies can provision computing and storage requirements on demand. Researchers can use machine learning and advanced analytics to analyse cloud-based datasets in real-time, slashing both cost and development time. For instance, they can run simulations to identify likely drug candidates faster, or study molecular structures, clinical trial data, and genomic information to predict drug-target interactions. Cloud-based analytics can process clinical trial data to discover trends and improve trial design. Real-time insights into clinical trials enable important decisions, such as how best to adapt protocols. Importantly, cloud provides a secure environment where these highly regulated companies can store, process, and exchange information while complying with applicable regulations.
AI amplifies the benefits of cloud and analytics and delivers new outcomes. Drug manufacturers can use AI to enhance drug safety and efficacy by predicting the properties of drug molecules. They can also leverage AI to recruit the right patients for clinical trials, optimise trial design, compose cohorts, retain patients, and monitor and close trials. Generative AI is introducing new use cases, such as extracting scientific knowledge and creating or summarising medical literature.
Streamline supply chain activities
U.K pharma manufacturers can also use cloud, digital analytics, and AI to transform supply chain operations. Cloud platforms enable data sharing with partners for better collaboration and allow infrastructure to scale on demand, enhancing supply chain agility and resilience. AI provides real-time visibility across the supply chain and can predict future events for proactive management. From forecasting demand and automating compliance checks to optimising warehouse processes and monitoring the cold chain, AI can enhance improve pharmaceutical supply chains in many ways.
Personalise treatments
A few years ago, GSK rolled out digital twins to improve the speed and cost efficiency of vaccine development and production.
Pharma manufacturers can also create digital twins of individual patients to simulate their response to new treatments in a virtual environment before testing the therapies on human subjects. Besides improving drug safety and efficacy by allowing early detection of adverse reactions, digital twins help personalise treatment plans for each patient.
Companies can also leverage other AI tools to analyse medical datasets, including patient records, lab test results, and medical images to identify patients at risk for certain diseases, and personalise treatment based on their health condition and response to previous interventions.
Going forward
Digitalisation presents immense possibilities for the U.K. pharmaceutical and life sciences industry. However, adoption is not without its challenges. Enterprises face hurdles like legacy infrastructure, data security, privacy concerns, and cultural resistance. The support of a trusted transformation partner is invaluable for navigating these issues and unlocking the full value of technology.
By Subhro Mallik, EVP and Global Head Life Sciences, Infosys
