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

Among the many promises of big data, one of the most exciting could be the potential to unlock the detection of cancer before advanced malignancy ensures, which means opening up a whole new understanding of the disease.

Big Data may revolutionize social science—and also amplify our deepest cultural biases.

Large-scale multi-modal information on patients’ health is ever increasing, providing an opportunity to use big data for taking individualized medicine to a global scale.

Healthcare is an imperfect practice, with disparities in care reflecting those in society. While algorithms may be misued to amplify biases, they may also be used to identify and correct disparities.

Although examples of algorithms designed to improve healthcare delivery abound, for many, clinical integration will not be achieved. The deployment cost of machine learning models is an underappreciated barrier to success. Experts propose three criteria that, assessed early, could help estimate the deployment cost.

The recent report of an antisense oligonucleotide therapy designed for only one patient spotlights regulatory, economic and ethical issues that must be grappled with in an era of accelerated development of ‘ultra-personalized’ drugs.

To promote effective translational medicine, academia must take the lead in creating a conducive environment for the first steps into translation, urge Roch Ogier and colleagues.