By Pat Jenakanandhini, chief product officer, ArisGlobal
With the new year here, life science organizations have reached technology crossroads in choosing whether to embrace a digital-first mindset and adopt innovative digital technologies or hold fast to legacy processes.
Digital transformation has driven newer technologies designed to improve efficiency, patient care and workflows. Those who choose not to adopt these technologies risk developing data integrity issues, which can include data silos and faulty documentation.
Life science organizations hoping to expedite the process of bringing drugs to market — while maintaining rigorous safety standards — should leverage these technology trends.
Evolution of wearable technologies and AI in healthcare
Over the last decade, the popularity of wearable health technology like smartwatches, biosensors and fitness trackers has increased. Patients have become more engaged and connected to their healthcare, relying on these devices enable consumers to monitor vital health signs daily — and communicate that health data to their doctors.
For example, one study found 56% of Gen Zer and 46% of millennial smartwatch users talk to their doctors about the biometric data their fitness trackers collect, like heart rate and sleep habits. Of 600 nurses participating in a LinkedIn survey, over 80% said they have a “somewhat” or “very positive” view of how technology affects patient care. Tech companies including Apple and Samsung are working to design a suite of healthcare apps for smartphones and smartwatches to help people manage their health more effectively — something the nurses and other medical professionals think is a good idea.
Once those apps launch and that data becomes more widely sharable, life sciences organizations will be able to use the same biometric data in clinical trials to advise medical teams on real-time health statuses.
Like wearable tech, AI improves healthcare delivery by automating processes to free up healthcare personnel — including nurses — to focus on their patients. By managing repetitive, redundant administrative tasks, AI improves efficiency and productivity and reduces human error, enhancing healthcare pros’ daily work lives.
AI also allows life sciences organizations to take a more personable approach when engaging with patients and healthcare professionals when paired with human teams to work together.
Doing so can help draw insights from large datasets more quickly to improve the overall business by methodically processing data, automating workflows, and transforming data into actionable insights.
Transformative power of the cloud
While the life sciences industry has begun to recognize the cloud’s transformative power, it’s been slower to adopt digital transformation because its leaders lack complete understanding of its value and how to capture it.
Traditionally, life sciences firms have focused on reducing technology costs and improving IT.
Nevertheless, other aspects will propel the future of the cloud forward, including:
● Architecture transformation: Cloud platforms with an open-architecture help integrate end-to-end operations and systematize workflow management across regulatory, clinical, safety and medical affairs teams.
● Versatility: Cloud systems support nearly all key business capabilities, from early research to post-marketing pharmacovigilance. Smaller biotech organizations can also leverage the cloud to scale without drastically increasing spending.
● Automation: Automation enables pharmacovigilance teams to pivot and realign their focus on mission-critical areas such as benefit-risk assessment and signal detection in drug safety. Cloud automation reduces the risk of errors and accelerates innovation in research and development (R&D) teams by replacing manual tasks.
● Data analytics: Cloud platforms allow organizations to scale and expand analytics use cases along the whole value chain. AI and ML translate complex medical data into actionable clinical insights for healthcare leaders.
Sixty percent of global companies use data and analytics to drive process and cost-efficiency. Nearly 70% of companies use business process automation solutions to improve end-to-end visibility across different systems. These transformative features produce high cost and profitability benefits for the life sciences industry, which experiences periods of growth and contraction subject to drug approval.
Real-world data in action
Real-world data (RWD) connects research and practice within healthcare by empowering drug developers to study patient utilization and response to approved drugs. Both regulators and the life sciences industry have progressively embraced the insights and value created by RWD. The FDA uses real-world evidence (RWE) and RWD to monitor postmarket safety and adverse events (AE) to make regulatory decisions due to its increasing role in healthcare decisions.
Many sources — like product and disease registries, claims and billing activities, and electronic health records (EHRs) — generate RWD. Companies often use these sources to gain insights into how patient attributes and behaviors impact health outcomes, which can inform decisions for care.
As they approach 2023, organizations must welcome innovation and promote resiliency to attain better business outcomes and produce life-saving remedies. Those who do not will jeopardize themselves in today’s competitive market.
Pat Jenakanandhini is ArisGlobal’s chief product officer, where he oversees all product strategy and management functions.