OpenTox Virtual Conference 2021 Session 13
Sustainable Predictive Toxicology with Open Science approaches
Sustainability is defined as using a resource so that the resource is not depleted or permanently damaged. The resources that can be depleted are the components essential to the ability to reproduce a predictive toxicology model. These include the data from which the model is created, the tools to create the model, and the model itself. All are at risk of getting lost in history. The journal article is a demonstrable medium that permanently damages the resource. Open Science, on the other hand, has all the characteristics to establish undepletable and undamageable predictive toxicology. This talk will discuss open science solutions developed in the past 20 years, including FAIR and Open data, open-source cheminformatics, open standards for toxicology, the solution to remove the risk of damage, and the peer-review process. Many of these are not routinely used yet and the presentation will end with the upcoming challenges we face. Here, FAIR metrics guide us towards a more open, more sustainable predictive toxicology. Examples will come from both small compounds and nanoparticle toxicology.