Researchers at U.S.-based WuXi NextCODE and the Yale School of Medicine published two new studies in the Journal of Experimental Medicine and Nature Metabolism on novel, artificial intelligence (A.I.) approaches that breathe new life into big data for complex diseases. A deep dive into these publications demonstrates breakthrough, biologically-validated A.I. approaches with the potential to understand virtually any disease in much greater detail using cost-effective designs of therapeutics. With precision medicine poised to transform patient care, the big data revolution in healthcare and drug development has taken center stage. Yet, the promise of precision medicine hinges on the ability to reduce the complex interconnections of large, multi-omic data sets into useful biological information. One of the long-term promises of precision medicine is to understand underlying disease mechanisms to ultimately improve our ability to diagnose, treat, and prevent a diverse array of conditions.

Geneticists can use the latest AI and Big Data analytics technology to study, diagnose, and even treat cancer. Cancer is one of the most active fields in genomics, spurring mountains of research papers and clinical trials. WuXi NextCODE is committed to pushing this field forward, and so we had a special "Genomes for Breakfast" session devoted to this topic at the recent ASHG17 event. The Cancer Genome Atlas (TCGA) is one of the most useful public genomic cancer databases available. It has led to critical discoveries, including entirely new drug targets and better insights into tumor origination, development, and spread.

Yale scientists publish a study in Nature that shows how WuXi NextCODE's AI and genomic analysis technology revealed an unknown cause of cardiovascular disease. WuXi NextCODE today highlighted the contribution of its artificial intelligence (AI) and sequencing teams to the discovery of a novel mechanism regulating how blood vessels grow. The study, "FGF-dependent metabolic control of vascular development," led by Yale University's Michael Simons and including scientists from six countries, is published in the May 2017 edition of Nature. The development of blood vessels is regulated by growth factors. If this development is impaired it can lead to cardiovascular disease; conversely if it is normal or upregulated in cancer, it can contribute to a tumor's rapid growth.

Almost 15 years after scientists first sequenced the human genome, making sense of the enormous amount of data that encodes human life remains a formidable challenge. But it is also precisely the sort of problem that machine learning excels at. On Monday, Google released a tool called DeepVariant that uses the latest AI techniques to build a more accurate picture of a person's genome from sequencing data. DeepVariant helps turn high-throughput sequencing readouts into a picture of a full genome. It automatically identifies small insertion and deletion mutations and single-base-pair mutations in sequencing data. High-throughput sequencing became widely available in the 2000s and has made genome sequencing more accessible.