A partnership to accelerate antibiotic research

Accelerating the selection of potential sources of antibiotics using artificial intelligence is one of the goals of ABRoad. This project is the result of a partnership between InflamAlps, a pharmaceutical R&D company, and Idiap. Supported by The Ark Foundation, this innovative project aims to develop a digital platform enabling the selection of potential sources of antibiotics.

Supporting drug discovery, determination of bioequivalent substances and identification of new antibiotics are the objectives of the ABRoad project. This project is the result of a collaboration between the InflamAlps company based in Monthey (VS), and Idiap. The aim is to design a natural language processing (NLP) software infrastructure. This infrastructure will help biomedical data discovery by easing the analysis of large scientific textual databases, such as articles and patents, as well as the development of a model allowing to compare chemical formulas within their textual context. The project is expected to start this fall.

A more cost effective pharmaceutical research

The identification and selection of potential sources of antibiotic substances, which can then be validated experimentally, requires the interpretation of scientific literature on a large scale. Considering the size of the related scientific corpus, this task is daunting! "How can we know that what we are looking for does not already exist?," Vincent Mutel, InflamAlps' CEO, asks. Thanks to recent advances in natural language processing, it is now possible to automate important parts of this sources of antibiotics selection process. "Stakes are very high. It's about avoiding unnecessary research and therefore accelerating the discovery of new antibiotics," Mutel explains.

A transposable technology

By using cutting-edge methods developed by Idiap specifically in Natural Language Inference (NLI) the project aims to develop an advanced textual interpretation platform. To effectively support biomedical discovery the project needs to take into account inferences in the contents it will analyze. “In the past few years, these methods have dramatically evolved to support the interpretation of textual evidence at scale. With ABRoad, we will demonstrate their value in augmenting the antibiotic discovery process,” André Freitas, Head of the Reasoning & Explainable AI research group at the Idiap, explains. The software infrastructure developed for the ABRoad project is a real proof of concept of the application of contemporary NLP methods and will give a strategic boost to biomedical companies in Valais, and beyond. The project also confirms the positioning of the canton of Valais as a national focal point in the area of Natural Language Processing.

Written in collaboration with Frédérique Brunner, The Ark.


More information

- Reasoning & Explainable AI research group

- InflamAlps

- TheArk Foundation