In the coming year, efficiency and automation will take center stage to maximize constrained resources but balancing sensible financial management with strategic investments will be vital.

The breakneck pace of digital transformation spurred by COVID-19 continued to reshape the life sciences landscape in 2023. Rather than a single watershed moment, this year marked an inflection point as companies begin to move from reactionary adoption to the deliberate integration of advanced technologies across the value chain.

Over the year, the focus for life science companies once again remained on advancing R&D and process efficiency—as well as improving data quality in an effort to become more data-driven—all whilst fighting to keep heads above water amidst increasingly diverse regulatory requirements and the need to drive greater productivity from fewer resources. Now at the crest of foundational disruption and optimization, the overnight digital transformation sparked by the pandemic has cleared the path for life sciences leaders to reach the next level in 2024, where data and technology amplifies human potential rather than displaces it.

Let’s reflect on the key events that defined this transitional year and glimpse the future digital strategies that will separate the thriving from the surviving.

Dallying with Data and Digital Transformation

Throughout 2023, the life sciences industry has been heavily focused on leveraging advanced technologies such as artificial intelligence, machine learning, and automation to drive innovation and accelerate research and development. Though digital technologies present considerable opportunities for life sciences companies, most have yet to fully embrace and integrate these innovations in an ongoing, committed way that capitalizes on their transformative potential.

A number of organizations have been applying these tools and technologies to challenges such as R&D, drug discovery, personalized medicine, and enhancing clinical trials. However, the industry is grappling with low quality, outdated, and incomplete data, hindering progress toward newer systems that rely on these data.

In response to a greater understanding of data’s critical role in innovation and reduced time to market for new products, a wave of data-centricity in life science R&D processes opened many new challenges for organizations, particularly in master data management, data governance, and data interoperability. The challenge manifested in understanding who owns what data, how the data items link together, how to track and trace these data, and how to perform impact analysis on changes to the data.

Some life science companies have made strides this year in tapping into data’s potential to accelerate discoveries and outcomes. Organizations are becoming more aligned with common definitions (defining single consistent dose strength in your organization that are ready for IDMP, for example), and there has been an increase in adoption of cloud-based systems and platforms to consolidate, analyze, and share data. But these organizations are battling with data lacunae, cross-business data ownership, and a standard of data quality that is, in some cases, terrifyingly inconsistent. Is there the will—or the financial backing—to address this?

Part of the challenge is that large pharma companies have a significant amount of legacy data, and the clean-up or rationalization of that data is far more tasking, or perhaps impossible, and may not bring a large return on investment for older products. Small to medium pharma companies on the other hand look to stand a better chance at getting their data organized and aligned going forward.

Similarly, regulatory requirements and initiatives such as SPOR, IDMP, FHIR, and ePI, may drive companies to make changes in their master data in ways that meet the scope of those initiatives and regulations, but this does not give them time to step back and look at the bigger picture, which could give rise to different and more efficient long-term solutions and master data design.

Pressures for decreased time-to-market

The pandemic accelerated drug development timelines and heightened expectations for faster access to new therapies, and this urgency has certainly persisted post-pandemic. Intense competition and the high costs of drug development have motivated companies to try to recoup investments faster through quicker product launches. But, startups and smaller biotechs with leaner organizations and more agile processes are disrupting the market and setting new speed norms that large pharma is struggling to keep pace with; however, patient safety remains paramount.

While the pressures for speed have intensified, quality must be maintained. Striking this balance has been a key focus across the industry in 2023. One of the ways we’ve seen this come to fruition is through a greater focus on collaboration with industry partners.

Many companies have moved from the art of the possible in collaboration with other companies to kicking off those initiatives and actually making the investment. The increased squeeze of competition is making time-to-market an even bigger deal, and some of the “great firewalls” of larger life sciences companies are beginning to modernize to allow more rapid collaboration with new partners (suppliers, manufacturers, CROs, CMOs, co-development partners, auditors).

While the level of collaboration looks to have increased, the traditional ways of doing this—through tools such as SharePoint, Box, and email—are continuing to add to the pain of data and document duplication, lack of security, auditing, and versioning. In the coming years, life science organizations will need to begin the move to purpose-built, cloud-native collaboration solutions to connect partners in a unified ecosystem; breaking down silos, while increasing security and compliance, and reducing duplicative work. Ultimately, this will be essential to compressing development timelines and accelerating speed-to-market in today’s competitive climate.

The impact of budget constraints on efficiency and innovation

So, have budget constraints in key areas of the business slowed progress and innovation in 2023? Or, have they instead forced decision-makers’ hands into investing in more strategic and efficient domains? Humanity’s collective short-term memory means we’re eternally and irrationally skeptical of the repeating patterns of both war and recession, especially following major global upheavals like the pandemic.

But they’re almost as sure as the sun rising. The smart money would be investing in automation and efficient structures/processes to weather the continuing storm, and that’s exactly what a number of organizations have been doing in 2023.

The most forward-looking companies paired fiscal restraint with targeted investments to reshape operations for lasting efficiency. They automated repetitive tasks to boost productivity beyond headcount, while cloud initiatives and digitization reduced IT infrastructure and security burdens.

There has certainly been some progress and advancements in innovation, yet our technical team have witnessed first-hand that the post-pandemic technological boom is being focused down to only strategic projects with the greatest ROI, which might not always be the most efficient long-term. This prioritization risks neglecting foundational enhancements that, while less glamorous, better position organizations for the future. Investments such as automations, data management, and governance may not directly drive revenue in the short-term but are crucial to compete in the coming years.

As we enter 2024, life science companies will need to find the right balance between fiscal prudence and continued investment in growth. The impacts will linger even as the economy recovers.

Looking to 2024

With the waters tested, 2024 is the time for life sciences leaders to dive fully into digital transformation, not just dip their toes. Life science companies have laid the groundwork needed to thrive in 2024 and beyond, with momentum building toward a foundation of high-quality data that enable and amplify human-driven processes. In the coming year, efficiency and automation will take center stage to maximize constrained resources but balancing sensible financial management with strategic investments will remain important—long-term thinking must not be sacrificed for short-term savings.

Partnership ecosystems will continue expanding, and quality, reusable data will be the essential thread that differentiates the organizations that can drive progress and innovation. The industry is sure to see rapid expansion in terms of data-driven automations. There is a general buzz in the air that structured data are the future, rather than document-driven workflows, which means there are a lot of exciting opportunities on the horizon to revolutionize business processes at every step from trials to safety monitoring.

However, existing data are currently “trapped” in documents at most organizations, so there is a pressing need for tools that can extract that trapped data and move it to a structured model. Once such a model is in place, there are many clear gains, from the ability to automate the generation of submissions to health authorities, to huge increases in pattern-tracking for areas such as pharmacovigilance and regulatory intelligence.

For life sciences leaders, 2024 is time to move beyond tentative implementation of new processes and technologies, confidently reshaping operations for the next normal. Companies that strategically harness data-driven, digital capabilities will propel the industry into a more innovative, resilient, and patient-centric future, ensuring they not only serve patient health more effectively but keep their costs under control.

About the Author

Max Kelleher is chief operating officer at Generis. He is passionate about providing a viable, pragmatic path for modernizing enterprise information management in regulated industries. His close work with both pharma companies and specialist solution partners has afforded him deep insight into the critical modern-day challenges that traditional approaches to business processes and information use in complex industries like life sciences do not fulfill.