This post was originally published on this site.
As artificial intelligence converges with life sciences at an accelerating pace, the founder of NJF Holdings argues that the most consequential discoveries of the 21st century are more likely to emerge from within the human body than from beyond it — from the study of cells, genes and neural networks rather than from planetary missions or deep-space observation.
The claim is less contrarian than it might appear. For centuries, the dominant image of scientific ambition pointed outward: new continents, new atmospheres, new galaxies. The instruments of exploration were ships, then rockets, then satellites. What has changed is not the scale of the ambition but its direction. The machine-learning models now being applied to biology can predict the onset of disease years before symptoms appear, design candidate molecules in seconds and identify patterns in brain activity with a precision that earlier generations of researchers could not have approached. The telescopes of this era, Junkermann has observed, are trained not on stars but on the biological systems that determine how long and how well people live.
How Nicole Junkermann frames the shift from treatment to anticipation
The practical implications for medicine are significant. Healthcare systems across the developed world were designed around a reactive logic: a patient presents with symptoms, a diagnosis is made, treatment follows. That architecture reflects the limits of what was technically possible for most of the history of modern medicine. Those limits are changing.
Federated learning — an approach that allows hospitals and research institutions to collaborate on large datasets without transferring sensitive patient records — is creating the conditions for a genuinely decentralised health infrastructure. AI systems are already being used to model protein structures, accelerate drug discovery pipelines and flag early biological signals that human clinicians might not detect for months or years. Owkin, a company in the NJF Capital portfolio, operates precisely at this intersection: using a federated architecture to enable biomedical research across institutions while preserving the data privacy standards that the NHS and its European equivalents require.
Nicole Junkermann has described this trajectory as a structural shift rather than a cyclical one. The opportunity in life sciences is not tied to a single breakthrough or a particular product cycle. Scientific platforms, longitudinal data ecosystems and research collaborations of the kind now becoming technically feasible can compound in value across decades. The frontier, in her analysis, is not a moment but an architecture.
The ethical questions Nicole Junkermann sees in the exploration of inner data
The same convergence of AI and biology that makes predictive medicine possible also creates a new category of risk. As thought patterns become decodable and emotional states increasingly quantifiable, the concept of privacy acquires a dimension it did not previously have. Brain-computer interfaces are already restoring movement to paralysed patients and enabling communication for those who have lost speech — applications whose therapeutic value is clear. But the underlying capability raises questions that go well beyond the clinical setting.
Nicole Junkermann has argued that the central governance question of the coming decades may be who controls biological and cognitive data, and under what conditions. If the 20th century was shaped by the extraction of physical resources, the 21st may be shaped by the extraction of human data — and the distribution of the benefits from that extraction will depend on the design principles built into the systems doing the extracting. Discovery, she has warned, must not become domination.
Capital plays a decisive role in determining which design principles prevail. Investment decisions shape which technologies scale, which governance models become standard and which institutions accumulate the trust necessary to operate at the frontier of biological data. The potential to back companies that extend healthy lifespan, strengthen public health infrastructure and reinforce individual data rights is, in Junkermann’s framing, both a strategic and an ethical choice — and the two are not in tension.
Nicole Junkermann on responsibility and progress in life sciences
Nicole Junkermann has pointed to a boundary that deepening biological knowledge does not appear to dissolve. Algorithms can model perception, map neural pathways and replicate aspects of reasoning with increasing fidelity. Consciousness — the quality of awareness that underlies curiosity, empathy and the capacity to find knowledge meaningful — remains outside what computation can reproduce. The more precisely machines can describe the human body, the more clearly that boundary comes into view.
The exploration of inner space, on this reading, is not only the most ambitious scientific undertaking of the century. It is also the one most likely to clarify what distinguishes human experience from the systems built to study it. True progress in life sciences will require pairing technical capability with restraint — ensuring that the governance frameworks applied to biological data are built to protect the autonomy of individuals, not merely to facilitate the ambitions of institutions. In Junkermann’s view, the most durable companies in this space will be those that treat that distinction as foundational rather than as a constraint imposed from outside.
