Let’s Speed the Genomic Revolution, UK CMO Says

Sally Davies genomics

Whatever path various societies take to tap the power of the genome to improve human health, a recent report from England’s Chief Medical Officer, Dame Sally Davies, calls out key elements for realizing that future sooner rather than later.

England’s Chief Medical Officer wants to build on the success of Genomics England’s 100,000 Genomes Project and take her country swiftly into the age of precision medicine. The goal is to get patients optimal treatment more quickly and with fewer side effects. That means using genomics to more accurately guide prescribing—initially for cancer, infections, and rare diseases—but increasingly for all conditions and overall wellness and prevention.

Dame Sally Davies’ vision is anchored in the work that Genomics England is engaged in today and to which WuXi NextCODE and other leading genomics organizations have contributed. It’s a rallying cry that many voices are joining and underpins our work not only in England, but also similar efforts we are helping to advance in countries near and far, from Ireland to Singapore.

Her call is particularly forceful in three areas that she rightly singles out as critical to realizing the potential of precision medicine to revolutionize healthcare:

  • Industrial scale: Genomics has in many ways been treated and developed as a “cottage industry,” yielding important advances. But the need is massive scale in the era of population health (e.g., whole-genome sequencing, or WGS).
  • Privacy AND data sharing: Dame Sally wants to provide and ensure high standards of privacy protection for genomic data but is adamant that this should not come at the price of stifling the data sharing and large-scale collaboration that will transform medical care and many patients’ lives. She wants to move beyond “genetic exceptionalism,” which holds that genomic data is fundamentally different or more valuable than other data. Like other sensitive data, we can protect genomic data well and use it for public benefit.
  • Public engagement: She calls for a new “social contract” in which we, as individuals and members of society, recognize that all of us will benefit if we allow data about our genomes to be studied. That holds whether we are talking within our own countries or globally.

In England, as elsewhere, these shifts require the input of political leaders, regulators, and a range of healthcare professionals, including researchers as well as care providers. Crucially, such a transformation also requires a level of commitment on the part of patients throughout the National Health Service (NHS) and citizenry in general. If England takes this bold step forward, it could have tremendous effects. But “NHS must act fast to keep its place at the forefront of global science,” said Davies. “This technology has the potential to change medicine forever.”

To date, more than 30,000 people have had their genomes sequenced as part of the 100,000 Genomes Project. But there are 55 million people in the UK, and Dame Sally would like to see genomic testing become as normal as blood tests and biopsies for cancer patients: She wants to “democratize” genomic medicine, making it available to every patient that needs it.

We share and are, indeed, taking part in helping to realize much of Dame Sally’s vision as we work to accelerate Genomics England’s work and engage with our partners globally. As we know, different societies have different models of healthcare and different approaches to research and care delivery. But the ability for people anywhere to tap into the power of the genome to improve their health is at the very core of our own mission as an organization, and we applaud Dame Sally for calling out some of the key elements for realizing that future sooner rather than later.

Whatever path different societies choose to follow toward precision medicine, her recent report provides one enlightening view of a starting point for making the leap.


Domain Expertise: Jumpstarting Artificial Intelligence in Biomedicine

Is artificial intelligence the “single most transformative technology in modern history?” That’s the view of Tom Chittenden, who leads WuXiNextCODE’s AI program. And Tom is not alone in his enthusiasm, as numerous analysts are predicting this technology will be one of the fastest growing fields in the world.

In recent talks at Boston’s BioIT World and the EmTech conference in Hong Kong, Tom described some of the strides we’ve been making with our DeepCODE AI tools. Their power is in part thanks to a novel, causal statistical-learning method and deep-learning classification strategy. But another advantage is that they were built on—and are extending the reach of—our global platform for genomic data. That means that Tom’s team has that rare combination of both of the key ingredients to AI making an impact in biomedicine: cutting-edge algorithms AND deep domain expertise and access to the biggest datasets.

Tom—who also holds appointments at Harvard, MIT, and Boston Children’s Hospital—and his growing team have the former in spades; our platform and expertise in genomics provide a key edge in the latter. Our platform has been built over more than 20 years and today underpins the majority of the world’s largest genomics efforts and includes all major global reference databases. It stores, manages, and integrates any type of genomic data and correlates it with phenotype, ‘omics’, biology, outcome, and virtually any other type of data that may be relevant to a particular medical challenge.

That means that we can routinely train and test our AI tools on some of the most comprehensive data sets in the world, such as that in The Cancer Genome Atlas (TCGA). “Today we can take ‘omics data and clinical information and map those to curated resources such as SNOMED CT and biomedical ontologies, and then use AI to identify patterns that lead us to novel findings,” Tom says.

This is a powerful approach to tease out which of hundreds of genetic variants are really involved in a particular disease, based on which ones are actually associated with aberrant expression pathways. You may find hundreds of genetic mutations in a single type of breast cancer tumor, for example, but it is determining which ones are drivers of the disease that matters.

Put simply, AI can lead us to both better diagnoses and easier discovery of more and better drug targets, by taking a range of genomic data and marrying it to clinical information and scientific knowledge. AI is not just going to better match patients to the right drugs, it is going to help further our understanding of the relationships between genes and complex molecular signaling networks, one of the most challenging arenas in our field and the most sought-after starting point for discovering validated pathways and targets.

Valuable insights in real-world medical challenges are already emerging from this AI effort uniquely developed on and applied to the genomic and medical data that counts.

WuXi NextCODE  recently presented preliminary data from analyses using our novel AI technology to diagnose subtypes of tumors. Our DeepCODE tools were validated on six patient-derived tumor xenografts from mouse models, and then tested against approximately 8,200 human tumors from a collection of 22 cancer types in The National Cancer Institute’s TCGA collection. That study included five ‘omics data types. We achieved 98% accuracy overall, and our analyses of human breast and lung cancer subtypes were accurate in 96% and 99% of cases, respectively. This points to an improvement over current methods for matching patients to treatments for their particular cancer, and we have refined that accuracy further still. This capability is also going to be central to the development of liquid biopsies.


In another oncology study, using the same multi-omics data, DeepCODE identified a signal predictive of survival across 21 cancers, pointing to novel and holistic pathways for developing broad oncotherapies.

A recent study published in Nature, meanwhile, describes a potential new role for a well-known growth factor. That report, led by Yale University scientist Michael Simons, looked at blood vessel growth regulation—a crucial process in some very common conditions, including cardiovascular disease and cancer. Our Shanghai team provided RNA sequencing for this study. Our Cambridge AI team drove some of the key insights pointing to novel disease mechanisms.

Simons’ team studied knockout mice, whose fibroblast growth factor (FGF) receptor genes were turned off. They proved, for the first time, that FGFs have a key role in blood vessel growth, uncovering some metabolic processes that were “a complete surprise,” according to scientists on the team. Further, they mapped out pathways that could help provide new drug leads.


Our AI team is just getting started. We’re looking forward to many more intriguing findings from this group as they leverage their expertise and massive amounts of the relevant data to improve medicine and healthcare.