What One Change Does Life Sciences Need? We Asked the Experts

The life sciences are advancing at an unprecedented pace, driven by powerful technologies, ambitious research and a growing emphasis on translation from lab to clinic. Yet despite these rapid developments, bottlenecks remain – some technical, others cultural or political – that slow the journey from discovery to impact.

What single change could most accelerate progress across the field?

We asked leading researchers, innovators and policy experts to share their perspectives. Their answers span from scientific freedom and funding, to data sharing frameworks and cultural openness, trust-building and regulatory clarity. Together, they offer a compelling roadmap for how science could move faster and more equitably in the years ahead.

Johan Junker, PhD

Technical developments within life sciences happen at a rapid rate, yielding endless options and possibilities. While some cultural and policy-related hindrances exist – i.e., restrictions on the use of certain progenitor cell populations and excessive regulatory processes within MedTech – solid research and novel therapeutics manage to find their way to clinical implementation.

In my opinion, the main obstacle to overcome is providing scientific freedom and adequate funding to pursue groundbreaking ideas. With more and more research being performed with commercial interests in mind, potentially disrupting ideas and technologies may be thwarted due to being deemed as “too high risk” or not commercially viable.

Rami Mehio

A much stronger technical and informational framework for consenting patients to make their DNA samples/data available for the research community would make a huge difference in omics-based advances. Technologies that can keep that data de-identified/anonymized and federated would be essential for the success.

Sergej Ostojic, PhD

I believe that political and cultural changes – such as stronger commitments to openness, greater support for young researchers to thrive and encouragement of truly disruptive science – would accelerate discovery in the life sciences more than any single technical breakthrough.

Michael Head, PhD

Trust. Build trusted partnerships between higher and lower-income countries and across these multi-country collaborations. This should produce equitable findings that can be trusted by policymakers in richer and poorer countries alike and then convey the usefulness of these policy changes or innovations to the general public, so they trust the evolution in healthcare delivery. In my view, trust is a hugely undervalued variable in science.

Gene Mack

The easy answer is that the greatest challenges – and opportunities – are policy and cultural, and they come down to administration. Drug development is a long and complex process. From the very beginning, we have to think about what the world will look like in 5 or 10 years, because that’s when a new therapy is likely to reach patients. That means we’re constantly making bold predictions in an environment where innovation is already difficult to forecast. Any uncertainty in policy or regulation can quickly bring progress to a halt. Even small administrative changes ripple downstream, creating delays and slowing collaboration across the industry. I don’t think policymakers always recognize the long-term consequences of these shifts. If the uncertainty continues, it risks creating a public health crisis. What’s needed is clarity and stability in the regulatory framework so that innovation can move forward with confidence.

Falk Schlaudraff, PhD

One key change would be to make advanced technologies more accessible. Currently, tools like deep visual proteomics (DVP) are primarily used in top-tier labs with substantial funding and expertise. These limits on who can contribute to discovery.

Democratizing access through better training, more affordable instruments and open data platforms would allow us to make faster progress. It's not just about geography. It's also about incorporating new perspectives from fields such as public health, nutrition and environmental science. The more diverse the research community is, the more innovative the outcomes will be.

Iain Yisu Wang, PhD

Policy change can have significant effects on progress in life sciences. A well-targeted regulatory shift can reshape both the pace and direction of innovation. For example, the US Food and Drug Administration (FDA) has already begun phasing out the requirement for mandatory animal testing and encouraging new approach methodologies (NAMs), such as artificial intelligence-driven discovery, organoids and organ-on-chip models. The most transformative step would be the formal integration and prioritization of NAMs as regulatory standards, gradually replacing traditional animal studies where validated. Such a policy not only ensures safety and efficiency, but also stimulates technological innovation, sets industry trends and shapes the future direction of the life sciences.

Denise Teber, PhD

More openness on the challenges that we face and more openness to new methods that could support us in solving these challenges. A stronger exchange across the field.

Eleonora Juarez, PhD

A cultural and technical shift towards the integration of multiomic datasets would greatly accelerate progress across the life sciences. Today, critical insights remain fragmented across genomics, transcriptomics, epigenomics and proteomics. Unlocking the full potential of these data streams requires both platforms that can handle a variety of data, policies and incentives that promote open, secure data sharing. By enabling researchers and clinicians to build richer, more connected datasets, we can dramatically accelerate discovery

Carol Houts

Regulators have already laid out a strong framework to encourage advanced manufacturing programs like the FDA’s Advanced Manufacturing Technologies designation, Center for Drug and Evaluation Research’s (CDER) Quality Management Maturity program and early-engagement efforts, such as the Emerging Technology Program and CBER’s Advanced Technologies Team, all signal a clear commitment to innovation. The next step is pairing these policies with real economic incentives, especially around application programming interfaces (APIs). APIs are inexpensive to import from India and China but building that capacity here requires covering significant fixed costs. If procurement models, particularly in the generics space, can start rewarding reliability and underwriting domestic API production, we’ll finally have the foundation to match policy with sustainable practice.

Cesar Canales, PhD

Greater investment in data accessibility, interoperability and overall easy open-access to multiomics repositories would be field-transformative. We generate huge amounts of genomic and transcriptomic data, but much of it remains siloed or inconsistently annotated. Making datasets more accessible, standardized and integrated across species and modalities would dramatically accelerate discovery, reproducibility and cross-lab collaboration.