The use of precision medicine is beginning to play a larger role in the prevention, diagnosis, and management of food allergies. Several studies from the recent 2026 AAAAI Annual Meeting presented new data on biomarker and component testing for food allergies.

Following these presentations, featured expert Brian P. Vickery, MD, was interviewed by Conference Reporter Associate Editor-in-Chief Mona Shah, PharmD. Clinical perspectives from Dr Vickery on these findings are presented here.

I think that we are starting to make some inroads in precision medicine and food allergies, but we still have a lot of work to do. There is a general understanding that not all patients with food allergies are the same and that there are different phenotypes describing the different ways in which patients may present with, and the differing trajectories of, their disease. For example, a more severe phenotype is likely to persist vs a mild phenotype, which a patient may outgrow. While we understand that, in general, different phenotypes exist, it is hard to identify them at an individual level.

Another gap in our understanding is related to food allergy endotypes (ie, the biological differences in the condition that ultimately drive different clinical parameters). Asthma, for example, is a heterogeneous disease with different identifiable biological pathways that are active in different patients, which can help us choose the right treatment for an individual patient. This may also eventually be the case in food allergies, but we still have a long way to go before we will be actively engaged in that type of precision medicine.

Along with multiple colleagues, I presented a course at the 2026 AAAAI Annual Meeting on precision medicine approaches to early life interventions in the prevention and management of food allergies. The course focused on early life being an important phenotype to target for intervention, because the likelihood of remission is higher when treating young children with immunotherapy vs waiting to treat until they are older. This is an area that is really penetrating daily practice, especially because there are multiple options for immunotherapy that are widely available.

At AAAAI 2026, there was a lot of interest in identifying predictive biomarkers that could help us understand differences in natural history and reactivity, as discussed in a study presented by Layla Mokhtar (abstract 407). And there is a lot of interest in biomarkers that involve IgE. However, IgE alone does not tell the whole story, as IgE is necessary—but not sufficient—for the expression of allergies. So, there is a lot of diagnostic and prognostic information that is not captured by measuring quantitative IgE alone.

Component tests are now routinely available commercially, and they are somewhat helpful because you are looking at IgE response to a specific protein within an allergen such as the peanut, but they are also subject to some of the same concerns as a whole peanut IgE test. Epitope-specific profiling zooms in even further to look at the amino acid residues on a particular protein. Therefore, we are looking at the antibody response with more and more granularity. There were a couple of studies presented at this year’s AAAAI meeting looking at the utility and potential role of this type of epitope-specific testing as predictive biomarkers in food allergies: abstract 379 by Julie Wang, MD, and colleagues and abstract 403 by Kyung Won Lee, PhD, et al.

Biomarkers are still considered research tools with respect to food allergies, although they are likely to penetrate this clinical space over the next few years. As demonstrated in the study presented by Dr Lee, the use of artificial intelligence in conjunction with epitope-specific testing may help bring us closer to the goal of better predicting who is likely to respond to treatment by combining high-resolution antibody analyses with algorithms that incorporate machine learning. Right now, however, many of these analytes are still not well validated and are for research use only. At a high level, it was interesting to see at the 2026 AAAAI Annual Meeting the convergence of newer biomarker studies and computational tools that are becoming increasingly available. However, we still have a way to go to bridge the gap between proof of concept and everyday clinical use.