Cystic Fibrosis: A Journey through Time and Hope.

Just over thirty years is the span of a generation. It is also the time that has passed since the discovery of the gene responsible for cystic fibrosis. Today, it is safe to say that this discovery has revolutionized our understanding, research perspectives, and management of this disease, which was, thirty years ago, a pediatric condition with a grim prognosis.

[The revolution of AI in drug development].

Artificial intelligence and machine learning enable the construction of predictive models, which are currently used to assist in decision-making throughout the process of drug discovery and development. These computational models can be used to represent the heterogeneity of a disease, identify therapeutic targets, design and optimize drug candidates, and evaluate the efficacy of these drugs on virtual patients or digital twins. By combining detailed patient characteristics with the prediction of potential drug-candidate properties, artificial intelligence promotes the emergence of a "computational" precision medicine, allowing for more personalized treatments, better tailored to patient specificities with the aid of such predictive models.

Correction: The genetic history of France.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The genetic history of France.

The study of the genetic structure of different countries within Europe has provided significant insights into their demographic history and population structure. Although France occupies a particular location at the western part of Europe and at the crossroads of migration routes, few population genetic studies have been conducted so far with genome-wide data. In this study, we analyzed SNP-chip genetic data from 2184 individuals born in France who were enrolled in two independent population cohorts.