Precision Medicine Transformed Oncology —It’s Time to Do the Same for Sepsis

Sepsis can happen to anyone. Clinicians know it and patients fear it. But too few researchers target it.

We’ve seen an upwell of news articles and social media posts about the deadly disease in the weeks since NASCAR driver Kyle Busch’s tragic death. Each piece earnestly describes sepsis symptoms and outlines what people should do if symptoms appear. It’s a good conversation, because increasing awareness is deeply important and can save lives. But awareness alone won’t help patients who will still be relegated to supportive care when they arrive at the hospital.

When it comes to making progress toward better treatment options for patients who develop sepsis and other acute conditions, progress has been stalled for decades. Sepsis is the “graveyard for pharmaceutical companies” because drugs stall after unsuccessful clinical trials. The result? No truly new therapeutics in more than 20 years.

While sepsis may be the most recognizable example, the same challenge extends across acute immune-driven diseases, like severe pneumonia, acute respiratory distress syndrome (ARDS), acute kidney injury, and acute organ failure. Together, these conditions affect millions of patients each year and remain among the most costly and lethal challenges in medicine.

The conventional wisdom has held that sepsis is simply too complex. When we look at the progress happening across healthcare – and the real potential for dramatic innovations fueled by AI-enabled discovery – it’s time to rethink what “too complex” actually means so we can reignite innovation in this area of deep unmet need.

Simple labels obscure complex biology

In oncology, we don’t treat “cancer” or even “breast cancer” —  we treat HER2-positive breast cancer. Precise biological profiles have defined disease sub-types that are ever smaller and more similar, enabling the development of treatments matched not to “cancer” but to very specific biology.

We can do the same with “sepsis.”

Syndromes such as sepsis or ARDS often group together patients with fundamentally different underlying biology. Two patients can arrive at the hospital with the same diagnosis, similar symptoms, and similar vital signs but entirely different biological processes are driving their deterioration beneath the surface. Yet historically, those patients have often been grouped together in clinical trials and treated as though they represent a single population.

Oncology faced a similar challenge decades ago. Fueled by the expansion of genomic sequencing technology, researchers harnessed an ever-growing world of data and insights on how tumors operate on a biological level, not as monolithic “cancers” but as unique ecosystems.

The result has been one of the most important transformations in modern medicine.

Conditions like sepsis that emerge in acute care have historically lacked the ability to do the same. The challenges are real. The biology driving these syndromes moves quickly, over hours or days rather than months and years. Patients deteriorate before they can enroll in studies, biological samples are hard to come by and lack of progress breeds lack of interest. 

Or consider pneumonia. Studies evaluating corticosteroids have produced conflicting results for years. Some patients appear to benefit. Others do not. Some may even be harmed. We don’t know how to predict which patients are which.

But the good news is that change is on the horizon.

The convergence of real-time clinical data, rapid biomarker measurement, and AI is making the fast-moving immune responses driving these conditions visible in ways that were previously impossible. Now more than ever, researchers are identifying biologically distinct patient populations, enabling studies of which therapies may work best for specific types of patients. 

Researchers across academia, government and industry increasingly apply this precision medicine approach to acute care. BARDA, for example, supports research to better define which patients with pneumonia respond to corticosteroids, and which don’t. Researchers are also exploring how biological differences between patients can sharpen the way they develop and evaluate therapies across acute illness.

The implications extend well beyond corticosteroids. If researchers can identify which patients are most likely to respond to a therapy before a trial begins, treatments that failed in broad patient populations may prove effective in the patients they were designed to help.

So why isn’t biopharma jumping in? Largely because researchers haven’t had the tools to identify the right patients before a trial begins. As those tools become available for use in acute care, researchers have an opportunity to rethink how acute care therapies are developed and tested.

Harnessing the data to reignite innovation

It’s time we reignite treatment development for sepsis and other immune-mediated conditions that strike when patients are most vulnerable. 

The path forward requires two things moving in tandem. First, treating acute care settings not just as places we deliver care, but as places to research and understand the biology driving these fast-moving diseases, capturing the data that makes them more intelligible. Second, biotech companies willing to re-engage with disease areas they’ve long avoided, armed with the patient stratification data that has historically been missing. 

The graveyard metaphor has held for too long. The science has changed. The data has changed. The technology is now capable. 

The missing pieces are interest and investment.

Photo: drogatnev, Getty Images

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