There has never been a more exciting time in immunology. From high-throughput sequencing to single-cell analysis, researchers now have tools capable of generating vast amounts of data. But what happens after the discovery? How do we ensure that the knowledge generated informs clinical and public health decision-making?
That’s the question driving Professor Miles Davenport, a former clinician turned immunological data scientist and co-author of a recent Nature Immunology comment titled “Towards Evidence-Based Immunology.” In the piece, Davenport and colleagues highlight a challenge facing the field: while discovery is flourishing, validation has lagged behind.
Evidence-based immunology
“We’ve become somewhat addicted to novelty – valuing new discoveries over attempts to test the validity or generalizability of our previous findings,” Davenport told AAI News & Views. “Immunology research makes great discoveries, and many of these discoveries have turned into important treatments and vaccines. But as the pace of research has accelerated over the last decade, a bottleneck to translation has become our ability to analyze and synthesize this data to inform clinical or policy activity.”
Davenport speaks from extensive experience. His early career began in medicine and molecular immunology. But his passion soon shifted toward statistics and modeling. Over two decades, he built a team of mathematicians to analyze immunological data and collaborate with scientists and clinicians. That foundation proved crucial during the COVID-19 pandemic, when his group’s synthesis of immunological studies helped identify neutralizing antibodies as a key correlate of protection—insights that shaped vaccine and treatment strategies.
Still, Davenport says this work initially highlighted an issue: “It made me realize that although immunological studies were generating a lot of interesting data, it’s quite difficult to apply this to timely decision-making, as is needed in a crisis.”
A shift in emphasis
The Nature Immunology comment lays out a path forward. Davenport and co-authors aren’t calling for less discovery, but for greater balance between exploratory and confirmatory research. In the comment, the team suggests that studies need to be clearer about where they sit on the research spectrum—from hypothesis-generating to hypothesis-testing—and adopt methods accordingly.
“In my view, what is needed is not a broadscale culture change, but a shift of emphasis within the immunology research community to increase the focus on providing evidence that can be used to inform decision making,” said Davenport.
Davenport made it clear that “we don’t want to stifle the progress that discovery research has provided and continues to make, but there is a lot that can be gained by establishing a parallel culture of evidence-based assessment of immunological data that can accelerate these immunological discoveries from ideas into actionable evidence.” Education will be key. “We need to train immunologists on study design, statistical analysis, and evidence assessment,” he said.
Adopting approaches
Davenport believes immunology could benefit from adopting approaches already common in clinical medicine. “This means that – for work we hope will impact policy – we need to develop and follow best practice and research reporting standards that allow others to readily compare, combine and draw conclusions from our work,” he said. “Individual scientists can also help by articulating how their research responds to the needs of decision makers, and how it fits into the bigger picture of the research area.”
So what would success look like for Davenport?
“Future decision makers will have a higher level of confidence interpreting and using immunological data. This will be because immunologists themselves have established best-practice guidelines, strategies for reporting, validating, integrating and communicating all the available results to give a ‘big picture’ to decision makers.”
As the pace of immunological discovery continues to accelerate, Davenport’s message is clear: with the right tools and mindset, the field of immunology can make an even bigger real-world impact.
