Abstract

The COVID-19 pandemia has brought into focus the need to be prepared for emerging threats. Arguably one of the most significant concerns in the area is antibiotics resistance. There is a vast amount of data in the Antibiotic field that has been collected over the years and can be used as the springboard to new Drug Discovery projects. Literature data is noisy and need to be curated and trusted to be useful. In addition, successful projects such as the COVID Moonshot with a worldwide approach to crowd sourcing science ideas has shown that collaborative efforts are key to accelerate the delivery of new therapies1. We present an application of the CDD Vault research data management platform combining the benefits of using curated antibacterial (Gram-negative) research data in combination with machine learning methods in a collaborative platform to tackle resistance. We use CDD Vault®, a hosted platform designed to archive, mine, and securely share research data across multiple sites and verticals, to accelerate the discovery process by sharing knowledge and build models together based on the past and collective know-how.