Why biopharma needs to invest massively in data strategy, and why the next 10 years will be pivotal

Medical research is accelerating at an unprecedented pace. Targeted therapies, immuno-oncology, generative AI, decentralized trials, real-world studies… Each of these innovations shares a common foundation: data. But this foundation, while essential, remains fragile. 

According to WHO, 85% of health data is currently not standardized. And even worse, 97% of data produced in hospitals is never reused, when it could inform research, improve our understanding of diseases, and accelerate access to treatment.

Against this background, investing in a robust data strategy is no longer an option, it’s a necessity for laboratories, biotechs, CROs, medtechs and any Life Science actors that want to survive.

Without exploitable, continuous data, therapeutic innovation will grind to a halt

As pathologies become increasingly complex, traditional drug discovery pipeline models (step-by-step, slow, and siloed) simply cannot keep up. Today, Life Science actors must handle massive volumes of data coming from dispersed sources: clinical trials, national registries, imaging, genomics, EHRs, behavioral data, etc.

The shift they are currently facing is the constant intertwining of research, clinical practice and real-world data. A molecule no longer reaches Phase III without being enriched by real-world evidence, and undergoing the kind of iterative analysis needed to adjust cohorts, target sub-populations, and detect unexpected effects.

Yet in practice, R&D and HEOR teams still spend too much of their time on manual tasks: reformatting data, harmonizing heterogeneous databases, waiting for access authorizations, reconstituting dispersed cohorts…  All leading to months of delays, exponential costs, and missed opportunities.

As global competition intensifies, organizations with the capacity to exploit data faster and more cleanly will gain a decisive scientific advantage.

Personalized medicine and the need for richer, more detailed, and more granular data

The surge in personalized treatments—immunotherapies, gene therapies, cell therapies, medications targeting specific mutations, smart combinations—is one of the stand-out transformations of the last decade. 

In many cases, these treatments will only help a few hundred or thousand patients per country.  To develop them, it is not enough to observe global trends. An extremely granular approach is required. This means combining:

• Clinical data,
• Genomic data,
• Imaging data,
• Care pathway data,
• And sometimes even behavioral data.
  

But this granularity comes with a catch: the different data sources are rarely unified, aligned, or easily shared. They are stuck in technological, regulatory and organizational silos. The biopharma industry must therefore invest in:

• Secure collaborative environments,
• Interoperability standards,
• Analytical capacities that don’t require data transfer,
• Infrastructures that let algorithms move instead of the data.

Without this technological leap, personalized medicine remains a pipe dream that is impossible to scale.

A new European framework: taking data from a scientific regulatory issue to a strategic one

As the European Health Data Space (EHDS) gains ground and the expectations of regulatory authorities evolve, market access cycles are being reshaped. For laboratories, it’s no longer a question of simply demonstrating that their drugs work. They must also show:

• The origin and quality of their data,
• The traceability of their analyses,
• The conformity of their technical environments,
• The reproducibility of their models,
• The robustness of the IA models they use.
  

The message is clear: data is no longer a simple research tool. It is also the subject of regulatory oversight, under greater scrutiny than ever before.

With this in mind, actors who shape their data strategy early on will have a clear advantage: less regulatory friction, stronger submissions, faster approvals, and better visibility in market negotiations.

The industry is entering a new era. Data is becoming a regulatory asset, just as valuable as clinical expertise.

Accessing EU5 data: a major strategic challenge in a highly contrasted global landscape

The importance of Europe is often overlooked when it comes to data. Yet the EU5 (France, Germany, Italy, Spain, and the UK) in particular represents one of the richest, most complex environments for health data.

This richness is strategic for Life Science actors, as decisions on pricing, reimbursement, and commercial roll-out are all highly dependent on the analysis of local data.

An OECD survey reveals a striking paradox. According to Health Working Paper No. 127 by Jillian Oderkirk (OECD, 2021):

• The USA is among the countries with the most well-structured governance of health data, thanks in particular to a strong push to make data available for research.
  
• Yet it only has 54% of the datasets recommended by the OECD, behind Korea and France with more than 90%.
  
• And despite this relative fragmentation, the USA counts the highest number of health data start-ups and unicorns.
  

It’s a fascinating observation: the USA doesn’t necessarily offer the best data access, but it has built the most dynamic innovation ecosystem. Europe, by contrast, has a colossal wealth of data (particularly in France, where data structure is recognized as among the best in the OECD), but still struggles to mobilize it.

For Life Science actors, the opportunity is enormous: harnessing, harmonizing, and exploiting EU5 data represents a decisive competitive advantage. Securing an accurate view of healthcare practice, patient pathways, sub-populations, and therapeutic performance in Europe can:

• Ensure the success of a launch,
• Guide HEOR strategy,
• Strengthen payer negotiations,
• Instruct priority country selection,
• Cement clinical investment decisions.
  

Over the next ten years, laboratories with the capacity to leverage European data will gain a considerable lead, both scientifically and commercially.

Innovation no longer relies on science alone: it depends on the capacity to mobilize, protect, connect, and exploit data without friction. Life Science actors who invest in their data strategy today are not only securing their success for tomorrow, they are positioning themselves as those who will set the benchmark for the industry as a whole.

Sources: EHDS (COM/2022/197), EMA (RWE 2022; AI 2023), EUnetHTA 21, OECD Health Working Paper 127, NIS2 Directive (2022/2555), GDPR (2016/679).