The life sciences industry has been notoriously slow to adapt to digital transformation, historically only tending to do so out of unavoidable necessity. In part, this is due to the industry’s cautious approach to regulation, which has inadvertently served to suffocate innovation. However, as the COVID-19 pandemic has made digital technologies an operational imperative rather than an optional add-on, this is no longer the case, and the reluctance or resistance of the past has given way to a new need to innovate for life sciences.
Technology will be the driving force behind transforming the life sciences industry of the future. In fact, recent research by Cognizant showed that technologies such as IoT, AI, automation and data analytics will blend with human capabilities to unlock innovation opportunities for intelligent decision making. As technology continues to augment human capabilities, we can expect to see big changes to the skills that the industry requires from future candidates, tilted towards those that demonstrate the ability to work alongside machines.
Global life science supply chains in a post-pandemic world
Digital transformation or bust? A new path for life sciences
There is no doubt that the pandemic has accelerated life sciences businesses and growth, as digital transformation is proving to be a key lifeline for finding solutions, vaccines and treatments for COVID-19. In a world where digital momentum has been at the core of everything from vaccine testing to supply chain, it is crucial that digital technologies are implemented at every touch point of the life sciences industry in order to keep up.
A year ago, scientists rushed to understand the massive question mark that was the coronavirus. In this instance, the sector was challenged with the ultimate ask: developing the most efficient solutions to help clinical researchers discover safe, effective treatments and to successfully manufacture and deliver them. This led researchers to unexplored territory, such as using AI to discover treatments; manufacturers collaborating with scientists and researchers to develop tests; and in some cases, partnerships were rapidly established to expand manufacturing capacity for necessary COVID-19 equipment.
Despite these superhuman leaps in scientific innovation, the life sciences sector was not exempt from social distancing, with remote research, “virtual” clinical trials, and virtual consultations setting the standard as the new norm. In fact, the Cognizant research reveals that 53% of life sciences respondents said the pandemic would further accelerate digital ways of working and doing business. Currently, life sciences companies generate just 4% of their revenue from digital channels, but predict this figure to double (8%) by 2023. This indicates positive outcomes for the future, as the industry is showing no intention of leaving these new digital ways of working as a relic of the pandemic.
The increasing amounts of diagnostic data flowing into and around processes will undoubtedly increase digital revenue – resulting in better workflows across R&D, manufacturing and supply chain processes – not to mention successive waves of innovative services targeted at patients. Indeed, the industry has not yet seen an explosion in revenue from digital channels due to regulatory constraints, yet the pandemic has overwhelmingly shown both the need and capacity for transformation.
The life sciences industry has managed to accelerate through time, accomplishing what has historically taken years in a matter of 12 months. This has been achieved through years’ worth of research, novel uses of AI, and a collaborative regulatory and funding environment. What was once thought of as a stiff and sterile industry is now exploding with opportunities in the digital sphere.
Ensuring that tech investments pay off
From IoT to automation – a new wave of machine augmented processes
Significant digital transformation is expected in the industry by 2023, despite life sciences companies just starting to operationalise digital technologies into their business processes. More specifically, the top three processes slated for augmentation are on the rise: clinical research progress will jump from 11% to 54%; clinical development from 7% to 44%; and R&D innovation from 12% to 33%. Furthermore, life sciences respondents state that intelligent machines will complete data-oriented tasks and complex decision-making from about 15% of this work today to 23% by 2023.
IoT, AI, analytics and automation are just some of the technologies driving digital transformation in the life sciences industry – with 80% of respondents to the aforementioned research already implementing IoT within their processes to some degree. The technology is most commonly used in two specific areas of life sciences: manufacturing and the supply chain. IoT helps improve visibility and connectivity across the supply chain, and medical device companies in improving control of product inventories, reducing loss and waste. For the consumer, IoT devices come in various forms such as sensors, devices and wearables to monitor things like health and activity.
It is precisely this coalescence of IoT devices that makes it possible to collect and analyse all manner of information within and outside of clinical settings, enabling automatic and hassle-free monitoring. Overall, this can help reduce costs, keep workers safe and improve health outcomes.
Participants also noted that they have improved their adoption and use of AI and analytics. For instance, AI is being used to enable more fluid patient care, increase the accuracy of risk predictions, enable pivotal decisions for the most effective treatment for individual patients, and underpin compliance via real-time insights. As many as 73% of respondents believe analytics will create value from data. With real-time decision making and insights, businesses can filter out production and supply chain inefficiencies, and remove human intervention in repetitive tasks – ultimately delivering new performance indicators.
Process automation is more attractive than ever, with 47% of participants at pilot or implementation stages. It can create huge financial savings when applied to specific processes, including clinical data science, compliance management, regulatory compliance, customer interaction, invoice processing, narrative writing and customer setup. The amalgamation of data analytics, automation and cognitive techniques will forever alter clinical development by enabling decentralised clinical trials, which will transform the way researchers engage with patients and manage processes.
Striking the perfect balance between human + machine
We can look forward to better decision-making and innovation as a direct result of this digital transformation. There is no doubt that as technology blends with life sciences processes, it will alter the required labour skillset dramatically. However, this should not lead to moral panic about human jobs being replaced with robots, as Cognizant’s research found that traditional soft skills such as innovation, decision making, leadership, and learning will continue to validate the need for human-machine collaboration. In fact, respondents believe intelligent machines will take on more data-oriented tasks and complex decision-making in the next two years, from about 15% of this work today to 23% by 2023.
Ultimately, it is essential that we give the life sciences industry the space to flex its muscles. The necessity of implementing technologies throughout the sector cannot be understated. Technology serves as the adhesive to bind people and machines at every touchpoint. The role of the human now requires a new focus on decision making, leadership and strategic thinking for managing these data-driven insights. As we move into this new highly automated future, it is important that we adopt a patient-centred approach throughout to not lose sight of who these transformations are really for.
