Leading After the Pandemic: Strategies to Guide the Future of Clinical Research

A COVID-19 vaccine in one year is no small feat! What made it possible was the industry coming together in unprecedented ways and operating with a sense of urgency, spurring global cooperation for vaccine research, innovation, and distribution. All that while continuing trials for other life-saving drugs and therapies. The life sciences industry has undergone a radical transformation making significant strides and closing the once-widening chasm between science, technology, and regulatory bodies. As an industry, we need to maintain this momentum at this critical junction, strengthen partnerships, and apply our learnings and knowledge to optimize clinical trials and accelerate the drug development process.

In the last decade, we have made revolutionary discoveries and advancements in science and technology, but only in their realms. Owing to impediments with business models, obsolete processes, and regulatory challenges, we are yet to make consistent progress in leveraging technology-enabled innovations to deliver valuable drugs and therapies to patients faster. As a technologist in the life sciences industry, I believe the way forward is to create and repeat sustainable processes from those adopted through the pandemic. We need to enable science through the leverage of technology, take a data-first approach to implement patient-centric and decentralized trials, and personalized medicine. Adapting and upskilling across the board will be critical to moving the industry forward. We now have primed and proven techniques and approaches to realize the digital future of clinical research. There is no going back.

A few strategies to consider that can guide us through the new data and post-pandemic era:

• Collaboration and Partnerships 

  Big pharma collaboration and strategies to combine resources to increase trial efficiencies, improve speed, safety, and efficacy, like the Oxford University and AstraZeneca, and Pfizer and BioNTech partnerships were instrumental in developing the COVID-19 vaccines in record time and securing regulatory approvals. With the common goal of accelerating timelines to develop a vaccine quickly, government agencies, pharmaceutical companies, and clinical researchers came together throughout the last year in extraordinary ways. The single vision in the industry created opportunities to cooperate and collaborate—this mindset should prevail.In the U.S., the leading causes of death are heart disease and cancer. Yet, clinical development to treat these—and many rare diseases—remains under-researched and lacks trial participation. We should maintain the momentum we gained with the COVID-19 pandemic, scale our learnings, strengthen partnerships and operate with a sense of urgency. Data and knowledge sharing should be at the core of any life sciences organization. Tighter collaboration between governments, healthcare, and the biopharmaceutical and medical device industries will result in significant developments for other drugs and therapies. We will be better prepared for the eventuality of another pandemic and also be able to expedite the development of treatments and medicines.

• Modern Infrastructures and Data Strategy 

  The pandemic has accelerated life sciences companies’ digital transformations and has forced the shift to modernize clinical trials. These trends are here to stay and will require suitable investments to drive value and outcomes. Now consider the data proliferation as we shift to implement decentralized clinical trials that rely on wearable technology and real-time data streams, leverage vast genomic and ‘omic data crucial to drug development for personalized medicine, and mine real-world data needed for clinical research and development. Now imagine the transactions and exchange of massive amounts of data throughout the clinical trial process. Without the modern infrastructure, AI and machine learning, and platform-centric approaches to scale, automate, and manage data, it will be next to impossible to transform that stream of data into actionable results.Over the last three years, the increase in data has contributed to a 40% increase in Last Patient Last Visit (LPLV) to database lock. Adopting a modern data management strategy will provide greater visibility into new sources and increased data collection. It will also help automate processes, reducing the manual labor needed to standardize diverse data sources. A robust strategy will ensure data quality, minimize risks, and prepare data for advanced analytics and quicker approval processes.

• Technology Upskilling 

  Finally, life sciences leaders need to foster new skills on their teams to navigate this new environment. With technology and digital transformation becoming a priority, clinical leaders need to support a deep understanding of how these new solutions work and how to maximize their usage to achieve the best results. So it is crucial to transform the workforce to help optimize these new digital tools, drive adoption, and consistently improve teams’ overall efficiency. Leaving repeatable, time-consuming processes to technology can allow clinicians and data managers to use their skills effectively for other critical functions.To increase speed and accuracy in clinical trials, we need to expand and acquire new skill sets vital to augment and maintain the techno-functional balance. An example, traditionally, is data managers’ and statisticians’ role to collect, clean, and analyze data. But the increase in data sources and types is forcing clinical trial leaders to rethink this process. Data Science is a skill set that companies will need to develop to evolve and enhance data intelligence to drive data and analytics capabilities to predict outcomes, increase accuracy, and accelerate timelines.

The Future of Clinical Trials 

In the post-pandemic world, we are on the brink of a technology and science revolution in clinical research. We proved that it’s possible to accelerate clinical trial timelines without compromising quality or neglecting regulatory guidelines. Maintaining collaborative efforts, modernizing technology infrastructures, and enabling modern clinical trials by supporting decentralized trial models will all serve to build on the momentum we’ve seen across the industry this past year. Achieving more groundbreaking outcomes is possible, but only if we can implement these strategies, put patients first, and establish a sustainable, data-driven standard for clinical studies.