The Coming Shift from Biomarkers to Biological Trajectories

For most of modern medicine, we have treated disease as a static condition. A patient has cancer. A patient has rheumatoid arthritis. A patient has inflammatory bowel disease. Diagnosis has largely meant identifying the condition, assigning a label, and selecting a treatment based on the standard of care.

But disease is not static, it is a dynamic biological process that evolves over time. Biology operates through change, and what we call a disease is often just the name we assign to a single point along a continuous biological journey, shaped by interactions among cells, tissues, and the immune system, by environmental exposures, and by the selective pressures of therapy itself. The lines we draw between health and disease, response and progression, are snapshots of a process that never stops moving.

Seen this way, the most consequential questions in healthcare are not about presence but about direction. Where is the patient today? Where are they heading? Which future states remain possible, and how can we change the path? The next era of medicine will be defined not by earlier detection alone, but by the ability to measure biological trajectories and ultimately intervene to change them.

A state-transition problem

Consider the decisions that actually determine patient outcomes. Diagnosis asks what biological state a patient is in. Therapy selection asks which intervention is most likely to move them toward a better one. Treatment monitoring asks whether they are moving in the expected direction. Drug development asks how an intervention alters biological trajectories across an entire population.

These look like distinct challenges, but at their core they are the same problem: understanding how biological systems move from one state to another. Yet most of our measurement tools were never designed to answer that question. They were built to detect the presence of something—a mutation, a protein, a lesion, a biomarker. Those measurements have transformed medicine, but they are static snapshots. They tell us what is present at a given moment far better than they reveal what is changing, why, or where the biology is headed next.

The challenge facing medicine is no longer detection alone. It is understanding dynamics.

A larger transformation

The evolution of liquid biopsy mirrors this broader shift. In 1997, Dennis Lo, DM, DPhil, and colleagues showed that cell-free fetal DNA circulates in maternal plasma, establishing that biological information could be read non-invasively from blood. The first generation of tests asked a simple question: Can disease-associated DNA be detected non-invasively?

The second generation moved from detection to sequence. Circulating tumor DNA assays identified cancer-associated mutations, monitored molecular residual disease, and flagged emerging resistance. The third generation went further still, using methylation and fragmentomic patterns to infer tissue of origin—which organs or cell types had contributed DNA to circulation.

Each advance extracted more information from a single blood draw. But all three generations remained focused on what was present and where it came from. A more fundamental question is now emerging: What was happening inside the cell before that DNA entered circulation? Not which tissue released it, nor which mutations it carried, but the functional state that generated the signal in the first place. Answering that question moves liquid biopsy beyond measuring static signals and toward measuring the biological processes that produced them.

Tissue of origin to biological state

The field has already begun to move past the question of where DNA comes from. The harder question is what those tissues were doing. Disease is rarely the work of isolated cells acting alone. Cancer emerges through interactions among tumor, stromal, and immune compartments. Autoimmune disease arises from cross-talk between infiltrating immune cells and tissue-resident populations. Fibrosis develops through coordinated remodeling across multiple cell types. These processes are not defined by single genes or mutations, but by regulatory programs, cell-to-cell communication, and transitions between biological states. And traces of that functional information appear to persist in circulation: A growing body of work indicates that cell-free DNA can carry signals of immune activation, fibroblast activity, and tissue remodeling, making aspects of gene regulation and cellular state readable directly from plasma.

This shifts liquid biopsy from identifying tissue of origin toward measuring tissue and disease states. Across a range of immune-mediated diseases, circulating signals increasingly reflect the stromal and immune programs seen in tissue and single-cell studies—not isolated molecular changes, but coordinated states of matrix remodeling, immune activation, and tissue stress. Just as important, repeated measurements turn these signals from snapshots into longitudinal trajectories, letting clinicians watch how biology evolves and responds to treatment over time. The critical question is no longer only what state a patient is in today, but where that state is heading next.

The emergence of trajectory medicine

Once biological states become measurable, a different model of care becomes possible. Many diseases are still managed by observation and iteration. In rheumatoid arthritis, for example, patients often cycle through therapies until one happens to work. The problem is not a shortage of options, but limited visibility into the biology driving disease in a given patient. The same constraint runs through oncology, inflammatory bowel disease, fibrosis, neurodegeneration, and transplantation.

This is no longer purely theoretical. In a peer-reviewed study led by investigators at Princess Margaret Cancer Center,¹ a single blood-based assay simultaneously measured immune, stromal, and tumor-associated biology in leiomyosarcoma—a cancer where low tumor mutation burden limits conventional circulating tumor DNA approaches and repeat biopsies are rarely feasible. Plasma-derived promoter activity showed strong concordance with matched tumor RNA sequencing, and longitudinal sampling captured shifts in immune and stromal biology tied to immunotherapy response and resistance.

Similar observations are beginning to appear beyond oncology. In immune-

mediated diseases such as rheumatoid arthritis² plasma-derived signals have recovered distinct, tissue-anchored stromal and immune programs consistent with the biology of the affected tissue. These findings are still early—generated in relatively small cohorts and in need of validation in larger, independent studies—but together they suggest that functional biological state, across both cancer and chronic inflammatory disease, can be measured from blood and followed over time.

When biological state becomes measurable, treatment shifts from reacting to symptoms toward managing trajectories. The questions change: not where a patient is today, but which path they are on, which intervention is most likely to change course, and how early a divergence from the expected response can be caught. Answering them requires a measurement framework built to capture biological change, not just biological presence.

The next platform layer in medicine

Every major advance in medicine has been unlocked by a new layer of measurement. Clinical chemistry enabled laboratory medicine. Imaging-enabled anatomical medicine. Genomics enabled precision medicine. The next layer will come from the ability to measure functional biological states and how they change over time.

The implications reach well beyond diagnostics. Therapy selection becomes a question of which intervention is most likely to alter a patient’s course. Drug development becomes a question of mapping how interventions reshape biology across populations. Disease interception becomes a question of recognizing an unfavorable path before symptoms appear. Healthcare itself becomes organized around how biological systems evolve, respond, adapt, and recover.

The organizations that define this future will not simply identify biomarkers. They will build the technologies and analytical frameworks that make biological change measurable, predictable, and ultimately actionable. The next era of medicine will be defined not by detecting disease earlier, but by understanding where biology is headed and learning how to change its course.

Problems that will define the field

None of this will come easily, and the challenges are worth stating plainly. Reading regulatory signal from cell-free DNA demands sophisticated computational methods and large, well-annotated datasets that account for variation across individuals, disease states, and platforms. Without rigorous analytical and technical standardization, such measurements will be hard to compare, reproduce, and interpret at scale.

The challenges of clinical translation are greater still. Prospective studies must show that measuring biological state from plasma improves clinical decisions and patient outcomes, especially where treatment selection remains largely empirical. Regulatory and reimbursement frameworks, built for mutation- and burden-based tests, may be a further hurdle. Functional biomarkers will need to prove that they can reliably characterize biological state, predict clinically meaningful change, and shift management in ways that improve outcomes.

These are not reasons for doubt. They are the next set of problems that will define the field and the test any serious platform will have to pass.

Where biology is going next

Twenty-five years of liquid biopsy trace a steady expansion of what blood can tell us: from detecting DNA fragments, to identifying their tissue of origin, to understanding the functional states that produced them. The patients who stand to benefit reach far beyond oncology, into the many chronic diseases whose underlying biology is increasingly understood but still hard to measure in routine care.

The shift from detection to function is already underway. How much it ultimately changes medicine will depend on how well we translate biological insight into clinical decisions. The question is no longer whether disease can be detected from blood, but whether we can see where biology is going next and intervene before the outcome is set.

References

1. Lopes, C.D.H., Wu, HT., Dilger, K. et al. Predicting immunotherapy benefit in leiomyosarcoma through active chromatin cfDNA profiling. npj Precis. Onc. (2026). doi: 10.1038/s41698-026-01451-9.
2. Taylor P., Antonova J., Geis J. et al. Detection of Synovial Signatures in Peripheral Blood of Patients with Rheumatoid Arthritis via a Novel Blood-Based DNA Capture Assay [abstract]. Arthritis Rheumatol. 2023; 75 (suppl 9).

Diana Abdueva, PhD, is the founder and CEO of Aqtual.

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