Predicting success of food allergy oral immunotherapy

AllerGenis is a US company aiming to use data-driven diagnostics to help healthcare providers more accurately and safely diagnose, assess and monitor people with food allergies. The company has developed an algorithm that can help to predict, with 87 per cent accuracy, someone’s likelihood of success with cow’s milk oral immunotherapy treatment before they start the program.

Milk oral immunotherapy treatment, where small amounts of milk protein are given to people with milk-allergy over a sustained period of time, can lead to desensitisation in some people. However for many, the allergen desensitisation is not sustained once the therapy is completed, and the treatment itself carries significant risks, including anaphylaxis.

The ability to accurately predict those who are likely to respond well to the oral immunotherapy versus those who won’t will allow clinicians to make informed decisions about the best and safest treatments for their patients.

In developing their latest diagnostic tool, the AllerGenis team has used a next-generation peptide-based immunoassay to split allergenic milk proteins into smaller peptide fragments — called epitopes — and created a distinct antibody-epitope reactivity profile for each patient. They have then produced antibody-epitope reactivity signatures for each patient sample and, using those data and machine learning, built a predictive algorithm.

Global immunological expert Dr Hugh Sampson, who has led this research says AllerGenis is keen to get this technology into the hands of clinicians. The company’s peanut allergy assay, launching in late 2019, will be the first product released using this technology platform.

For more information, visit https://www.allergenis.com