This has been a disruptive year for the life sciences industry. While the COVID-19 pandemic impacted thousands of clinical trials across the globe, bringing many to a staggering halt. On the other hand, we saw the industry rising to the occasion, and accelerating COVID-19 vaccine trials, with vaccines being approved in less than a year. The industry transitioned from a technologically averse, inwards looking model, to working in an agile and a collaborative manner. Digital resiliency was what mattered. Innovation, driven by technology adoption, took center stage.
Accelerated Growth of Decentralized Trials
Ensuring patient safety, while driving business continuity during the pandemic were the biggest challenges. The words ‘remote’ and ‘decentralized’ became synonymous with clinical trials, with approximately three-fourths of clinical trials adopting a hybrid decentralized approach. Regulators across the globe worked hand-in-hand with the industry to rapidly revise regulations and facilitate progress. Patients became more amenable to remote healthcare solutions, further enabling the implementation of these solutions (U.S. Life Science Top 10 Market Trends for 2020, IDC #US44986020, January 2020).
This has resulted in the accelerated growth of remote patient monitoring (RPM) solutions, including the use of telehealth, the internet of medical things (IOMT), wearables and sensors, and the use of electronic clinical outcome assessments (eCOAs) (eCOAs — Driving Patient Engagement and Ensuring Data Continuity in the World of COVID-19, IDC #US47084720, December 2020), generating a flood of real-time data (RWD), providing critical insights into patient health in a real world setting.
Leveraging Real World Evidence (RWE)
Data has been sitting around for a long time, but in siloed platforms. The need to mine real world data generated from disparate sources and drive interoperability, has led to the rapid growth of secure, scalable unified cloud platforms, aiming to create a connected healthcare ecosystem. This has also propelled the growth of digital biomarkers and prescription digital therapeutics (PDTs). Synthetic control arms (SCAs) are being developed to simulate a clinical trial control arm, thus accelerating approvals, reducing clinical trial costs, and adding immense value to rare disease studies.
Optimizing the Patient Experience (Px)
As patient-focused drug development (PFDD) became the new norm, the industry transitioned from a ‘site-centric’ to a ‘patient-centric’ model. The increasing disconnect between regulatory approval and market adoption have made the industry redirect its attention to truly understanding the patient’s voice.
Various efforts are ongoing to incorporate the patient’s voice in clinical trials, including soliciting their inputs in clinical trial design through crowdsourcing. There is an increasing focus not only on reducing the patient burden index (PBI), but on enhancing the patient experience (Px) and driving patient engagement. This became especially important as the when patient is based remotely, with limited interaction with the site. The industry has been working on enhancing the Px in many ways. These enhancements include bringing the trial to the patient’s home, offering patient concierge services, providing single sign-in platforms to the multitude of technology solutions a patient may need to utilize during a trial. The continued improvement of user interfaces (UIs) so as to improve the user experience (Ux), as well as including AR/VR solutions and gamification to enhance engagement have also been a triumphant leap forward. Another big piece of the patient experience is building trust, and trust is driven by transparency. This has led to a need to share trial results with patients in the form of plain language summaries (PLS), in a language that the patient can understand.
While the focus on transparency has increased, paradoxically, the importance of data privacy and security has significantly risen, with requirements to comply with stringent regulations such as Healthcare Insurance Portability and Accountability Act (HIPAA) and the General data Privacy Regulation (GDPR), which makes remote monitoring even more challenging, as a result of diversity in regulations across states.
Move to the Cloud
For several years, life science companies have been moving data and applications to the cloud, often as Software-as-a-Service (SaaS) (Post-COVID-19 SaaS Spending in Life Science and Healthcare, IDC #US47222219, December, 2020). These moves accelerated in 2019 and 2020, fortuitously as it happened with the sudden moves to remote work and collaboration due to COVID-19. Among 14 business-critical applications for life science companies, two-thirds are already deployed in the cloud, with that proportion expected to near 90% by 2022, according to IDC’s findings. Ease of collaboration, coordination with other systems, automatic revision management and reduced IT support has made this migration an easier decision for life science IT executives as legacy systems age.
Remote Engagement in Healthcare Practice
As consumers of health services have become more comfortable with Zoom meetings to consult with their doctors, doctors have also taken advantage of remote meeting technology to gain useful information from pharmaceutical field sales representatives. This adds to a long-term trend pivoting away from personal visits to healthcare provider (HCP) offices toward digital channels such as approved email, drug company website portals, e-detailing and virtual webinars and conferences.
In-person calls will certainly increase as COVID-19 subsides, but prescribers will continue to rely on these remote digital tools at a much higher level than pre-pandemic to access critical information about medicine, devices, and disease states, as well as view approved content and conduct remote sampling requests. Such digital channels provide convenience to busy prescribers to access drug and device information where, when, and how they want it, while improving productivity and lowering costs for life science companies.
Innovation in Medical Supply Chain Management
Early in the pandemic, shortages of PPE, drugs, and medical devices such as ventilators exposed a lack of preparedness by governments and healthcare organizations. As therapies and vaccines have been developed and approved in record time (U.S. Life Science Top 10 Market Trends for 2021, IDC #US46583321, February 2021), new challenges have emerged to manufacture and distribute these lifesaving drugs at scale around the globe.
“Thinking” supply chains (Coronavirus Slams Medical Supply Chains — How Can Technology Help?, IDC #US46180220, April 2020) will employ technology such as AI, analytics, and innovative surveillance techniques to monitor potential demand and to identify supply bottlenecks and secondary sources to address shortages. By embracing collaboration, connectivity, and security using cognitive technologies, these systems will assist in identifying medical supply issues in real time and generating insights and actions to rectify them.
To conclude, the world has become ‘data-centric’, leveraging high speed networks to generate real-time data. ML and predictive analytics (IDC TechScape: Worldwide Life Science R&D Machine Learning and Cognitive Computing Landscape, IDC #US47482121, March 2021) are being increasingly used to unravel the data chaos and derive meaningful insights. One sees growth in Data as a Service (DaaS) as machine learning (ML) algorithms need to be trained on large training sets of data. Analytics are being leveraged in diverse ways, ranging from signal detection to strategic drug forecasting. While what COVID-19 triggered was an attitudinal revolution in the life sciences industry, on the long-term, one expects that the industry will see an accelerated digital evolution. To learn more about the future of Life Science, join us for the “The Digital Disruption of the Life Science Industry: 2021 Top Trends” webinar live on April 20th at 11 AM/ET.
