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.

Accurate identification of tumor-derived somatic variants in plasma circulating cell-free DNA (cfDNA) requires understanding of the various biological compartments contributing to the cfDNA pool. We sought to define the technical feasibility of a high-intensity sequencing assay of cfDNA and matched white blood cell DNA covering a large genomic region (508 genes; 2 megabases; >60,000× raw depth) in a prospective study of 124 patients with metastatic cancer, with contemporaneous matched tumor tissue biopsies, and 47 controls without cancer. The assay displayed high sensitivity and specificity, allowing for de novo detection of tumor-derived mutations and inference of tumor mutational burden, microsatellite instability, mutational signatures and sources of somatic mutations identified in cfDNA. The vast majority of cfDNA mutations (81.6% in controls and 53.2% in patients with cancer) had features consistent with clonal hematopoiesis. This cfDNA sequencing approach revealed that clonal hematopoiesis constitutes a pervasive biological phenomenon, emphasizing the importance of matched cfDNA–white blood cell sequencing for accurate variant interpretation.

Ultra-deep sequencing of paired plasma-circulating free DNA and white blood cells allows the identification of tumor-derived somatic mutations with high accuracy by filtering out variants consistent with clonal hematopoiesis.

With the growing number of efficient gene therapies on the market, now is the time to take actions to ensure reasonable pricing of gene therapy products. Among these, we propose to incentivize gene therapy companies to adopt a status that translates their corporate social responsibility into concrete commitments.