A New Data Economy for Life Sciences – or Why Access and Trust Now Define Value

4 Nov

Across the life sciences, data has quietly become one of the most valuable strategic assets. From genomic sequencing and clinical trial results to patient-generated health data and real-world evidence, the organisations that can access, analyse, and apply high-quality data effectively are shaping the future of healthcare innovation.

But as data’s value has risen, so too has its scarcity. The days of open access and freely shared datasets are fading fast. Increasingly, data is being treated not as a by-product of science, but as a core competitive differentiator. It is now seen as an asset to be protected, licensed, and monetised with care.

For innovators and investors, this shift represents a significant change to the established rules.

Data is the new differentiator

Until relatively recently, success in biotech or digital health often hinged foremost on scientific ingenuity or novel technology. Today, another key-differentiator is data — how much you have, how good it is, and how effectively it can be harnessed to generate insights, train algorithms, or validate outcomes.

From AI-enabled drug discovery to precision diagnostics, data drives model accuracy, regulatory confidence, and commercial readiness. Yet while technology is increasingly commoditised, high-quality, well-curated datasets are not.

As a result, some of the most valuable assets in the sector are now exclusive data partnerships, characterised by long-term collaborations between biopharma, healthcare providers, or patient platforms that provide controlled access to proprietary data.

Rise of data protectionism

As the strategic and commercial value of data has become increasingly clear, data owners have become more protective. Hospitals, biobanks, and patient networks are setting tighter controls on how data is shared, used, and monetised.

The underlying reasons for this include:

Commercial opportunity: Organisations recognise that their data has value — and are less willing to give it away without tangible returns or strategic influence.
Ethical responsibility: Institutions are more conscious of patient consent and the societal implications of data use.
Privacy and regulation: Evolving data protection laws (GDPR, HIPAA, and equivalents worldwide) have raised compliance requirements and liability risks.

As a result, access to rich, real-world datasets has become a negotiated privilege, rather than an assumed right.

Access, trust & partnerships increasingly matter more than technology

For start-ups and investors alike, this trend has clear implications. Simply having cutting-edge AI or analytics capabilities is no longer enough. Without access to data, and a trusted relationship with those who hold it, those technologies are limited on what they have to operate on.

To succeed in a world of restricted data, companies need to build three key enablers:

Access: Develop genuine, mutually beneficial partnerships with data custodians such as healthcare systems, patient registries, or academic institutions. Offer shared value through research collaboration, co-development, or improved patient outcomes.
Partnerships: Recognise that no company can own all the data it needs. The future lies in ecosystems where biotech, data platforms, payers, and technology providers collaborate under shared frameworks that balance innovation with responsibility.
Trust: Demonstrate transparent governance, ethical data use, and strong data security. Trust is built not by technical claims, but by behaviour and track record. The most successful digital health partnerships are those where both sides are confident in how data will be handled and how value will be shared.

Investors should increasingly evaluate not just the usual Due-Diligence framework where they look at a start-up’s technology stack and health of their business plan, but its data access strategy. Namely. who they can work with, what data rights they control, and how sustainable those relationships are.

From ownership to stewardship

As the industry matures, a shift is increasingly apparent: from data ownership to data stewardship. Rather than attempting to hoard or lock down datasets as a strategy, the most forward-looking organisations are investing in responsible sharing models that balance protection with innovation.

Enabled by modern technologies that leverage federated data approaches, ontologies and semantic search, these include federated data models, where data stays in its original location but can be analysed securely across multiple sources; or data cooperatives, where patient communities retain ownership while enabling approved use for research or development.

This approach reflects a growing recognition that trust and transparency create more long-term value than control alone. Companies that engage openly, respect consent, and give something back, (i.e. insights, tools, or better outcomes) are more likely to gain sustainable access to high-quality data sources.