Precision medicine has been an aspiration for decades. Yet for many in Biotech and the Life Sciences, precision medicine has felt more like perpetual promise than a reality. However, that appears to be changing.

The convergence of AI, multi-omics (genomics, transcriptomics, proteomics, and metabolomics) technologies, and unprecedented data integration is finally transforming precision medicine from concept to clinical reality.

The AI health app market will continue growing rapidly. However, success is anything but  granted.

In a crowded market, what distinguishes the winners?

For investors evaluating AI health apps, the decision framework is straightforward:

• Does the app solve a workflow problem, a clinical need and/or costs institutions real money?

• Is the business model based on recurring, defensible value?

• Is the regulatory strategy proactive or evasive?

• Is there a commitment to data improvement and governance?

The current wave of investment in artificial intelligence (AI) infrastructure is unprecedented in both scale and speed. Trillions of dollars are being committed to build global computing capacity intended to power next-generation AI models. While the technological potential is transformative, the economic fundamentals remain uncertain in the near term. The gap between investment expectations and projected revenues suggests growing systemic risk — with multiple indicators resembling past speculative bubbles. Although there is no doubt about the vast transformative potential of AI and long-term sustained business success, some form of correction appears to be inevitable. Such a correction may actually lead to more sustainable AI solutions in the future and the long-term economic promise remains exciting.

Although life sciences are characterised by bold ideas and brilliant science, even the most promising biotech start-ups face daunting odds. Industry data suggest that fewer than one in ten biotech ventures reach sustainable success or an exit event.

The underlying reasons are rarely bad luck or weak science. More often, failure stems from strategic blind spots that emerge between discovery and delivery, where business discipline, market understanding, and executional excellence matter just as much as innovation itself.

In this blog we discuss the top five reasons biotech start-ups fail, and what founders, teams, and investors can do differently to mitigate, or even better outmanoeuvre these risks.

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.

For years, investors in Life Science support services had a clear formula for success: buy, integrate, scale, exit. And there were some very notable successes — at first.

But today, that strategy is no longer delivering the same outcomes.

AI will not replace regulatory professionals, but it will change the nature of their work and enable them to cope with the steadily rising flood of information.
By 2030, we can expect regulatory affairs to look markedly different: data-driven, predictive, and integrated across the product lifecycle, saving cost and meeting the demands of a rapidly evolving healthcare system.

Getting there will require smart capital, thoughtful governance, and sustained change management. But for those willing to navigate the barriers, the potential to transform one of the industry’s most important and complex functions is real — and well worth pursuing.

In recent years, biotech investors have gravitated toward safer, later-stage opportunities, reflecting a natural response to volatile capital markets, rising development costs, and investor fatigue following the post-pandemic correction. While understandable, this narrowing of focus comes at a cost: the underfunding of early-stage innovation that historically has been the source of the sector’s most transformative growth.

Our analysis suggests that investors who re-evaluate opportunities at the convergence of artificial intelligence (AI), digital health, and biotechnology can position themselves for significant long-term returns while supporting the development of technologies poised to reshape global healthcare delivery.

As we head towards the close of 2025, the investment landscape across biotech, digital health, and AI-enabled life sciences is entering a new phase — one necessarily defined not by recovery from a downturn per se, but by redefinition of opportunity.

The next investment cycle will reward clarity of vision and courage of conviction. Capital is returning, but it will concentrate around the companies and technologies that redefine how therapies are discovered, developed, and delivered.

For investors willing to look forward — beyond consolidation and incremental improvements — the opportunity is clear: this is the moment to back the innovators building the infrastructure of tomorrow’s life sciences industry.

“Too big to fail” has outlived its usefulness. The future winners in Life Science Services won’t just be bigger — they’ll be smarter. For investors, that means moving beyond the comfort of the “buy-and-build” model and embracing a more nuanced, innovation-led approach to value creation. 

The safer path is not always the more rewarding one. Investors who bring rigor, vision, and a willingness to embrace innovation will be those best positioned to unlock the next wave of biotech and digital health breakthroughs. And gaps in subject matter expertise or innovation can be bridged with a trusted partner …

Drug development has historically been famously slow, expensive, and complex. On average, it can take over a decade and billions of dollars to bring a new therapy to market. For patients with urgent needs (especially in rare or life-threatening diseases) and in the light of “personalised medicine” becoming reality — that requires acceleration. This is where digital tools, particularly digital biomarkers and digital endpoints, are beginning to change the game.

5 Key take-aways …

Game-Changer: Across domains, segments & technologies the expectation on the impact of digital health is very high to game-changer

Sweet-spot: Recent inflation of break-throughs is paving the way for ground-breaking & inevitable change, with themes like “taking the middle-man out” and “direct to … e.g. consumer” being often quoted

Play smart: Sustainable new opportunities arising from the proliferation of possibilities - if being played smart

Diagnostics before therapeutics: Indication that Lab- and diagnostics-business will be affected fast and strong with no option to swing back

Commitment & focus: Continued commitment, focus and getting strategy & benefits right is crucial to success given the change ahead …

When you scroll through LinkedIn or attend an industry event, you’ll notice that terms like digital health and digital healthcare often get used interchangeably. At first glance, they sound similar — and many people use them as synonyms. But if you dig a little deeper, the distinction is important, especially for life sciences and healthcare leaders who are deciding where to invest and innovate.

So what is the difference, and why does it matter?

New employees are eager to contribute and develop themselves. As a leader, meeting these expectations is essential to fostering long-term success

Improving team communications

Certainly there is now one magic bullet to build and run high performing teams, However, respecting and following some basic ground-rules can help to improve team-performance significantly. One of those ground-rules touches team communications.

5 Key take-aways …

Game-Changer: Across domains, segments & technologies the expectation on the impact of digital health is very high to game-changer

Sweet-spot: Recent inflation of break-throughs is paving the way for ground-breaking & inevitable change, with themes like “taking the middle-man out” and “direct to … e.g. consumer” being often quoted

Play smart: Sustainable new opportunities arising from the proliferation of possibilities - if being played smart

Diagnostics before therapeutics: Indication that Lab- and diagnostics-business will be affected fast and strong with no option to swing back

Commitment & focus: Continued commitment, focus and getting strategy & benefits right is crucial to success given the change ahead …