Tag Archives: genetic variants

Domain Expertise: Jumpstarting Artificial Intelligence in Biomedicine

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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.

http://hannessmarason.com/blog/2017/04/04/a-perfect-pairing-ai-and-precision-medicine/

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.

http://hannessmarason.com/blog/2017/05/15/bringing-artificial-intelligence-cardiovascular-medicine-cancer-genomics-action/

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.

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Speeding Diagnosis of Rare Diseases

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WuXi NextCODE Claritas

Claritas Genomics combines physician experience with next-generation sequencing and WuXi NextCODE’s analytics to accelerate rare disease diagnosis.

It’s one of the most heartbreaking and frustrating things for parents and pediatricians. When a child presents with a constellation of symptoms that doesn’t point to a known disease, what do you do?

Typically, these kids undergo a battery of tests, some of which will eventually be for single genes suspected to play a role in their health problems. But what if those tests come up negative? That leaves the families and doctors wringing their hands as they wonder what to do next.

That was the case with a patient at Boston Children’s Hospital (BCH). He was a boy who, at six months, wasn’t sitting up, smiling, or doing most of the things babies his age typically do. Instead, he seemed “rigid” to his mom, and then he developed a severe respiratory virus and was hospitalized. He also had repeated seizures and eventually needed a tracheotomy—a tube placed through an incision in his throat to help him breath.

Usually, such kids then begin going through what is known as a “diagnostic odyssey”—a long and arduous journey from doctor to doctor and lab to lab.

BCH doctors are trying a new approach. In 2013, the hospital spun out Claritas Genomics, a specialized genetics diagnostics business that combines the experience of the hospital’s physicians with the power of next-generation sequencing and WuXi NextCODE’s advanced analytics. Timothy Yu, a neurologist and researcher at BCH, helped found Claritas to provide a more holistic approach to rare disease.

WuXi NextCODE’s advanced analytics play a key role in improving the speed and efficiency of such diagnostics. Reading the genome isn’t the major challenge anymore—now the issue is finding the relevant mutations in those three billion base pairs.

The data from a single genome can comprise more than 100 gigabytes, which is enough to fill the hard drive on a good laptop computer. Even the exome, which comprises the parts of the genome that encode proteins, can be 15 gigabytes. To diagnose a rare disease, doctors need to find sequence variations and then scour the research to find out what those actually do. That used to take months to years, and many of the variants were simply classified as being of “unknown significance,” without any further information or the ability to check again as the field of knowledge grew.

WuXi NextCODE’s system has begun to make this a click-and-search task. Our knowledgebase can mine all publicly available global reference datasets simultaneously and in real time to show all there is to know about any given variant and its likely biological impact. By keeping the data in a WuXi NextCODE research database, such as the one BCH is growing every day, our system can also quickly rerun the analysis and provide new information as soon as it becomes known.

Claritas is continually expanding the range of its services. Most recently, the group received conditional approval from the New York Department of Health for three new “region of interest assays” as well as one for mitochondrial DNA. That brings the number of Claritas’s approved tests in that state up to six and means more patients in New York will benefit from this new technology.

Children at BCH with ambiguous diagnoses now regularly undergo a whole exome scan early in their clinical journey. The data is then triaged. It is examined first for the most obvious mutations and then more data is progressively analyzed as necessary. With the consent of parents and security measures for privacy, that data can also become part of research datasets at BCH and other major hospitals around the world, so that the growing data pool can benefit that child and others.

This combination of expertise and technology helped Claritas Genomics find an answer for that baby boy and his family mentioned earlier. Heather Olson, the boy’s treating neurologist, had the boy’s exome scanned through Claritas Genomics, and 130 genetic variations were identified that could have caused one or more of the symptoms. WuXi NextCODE’s system helped narrow that down to only six variants that could have possibly been passed on by the boy’s parents. Olson and Yu finally focused on one, a mutation of the BRAT1 gene, which served as a diagnosis. A paper published by Yu, Olson, and colleagues, which describes this mutation and children affected by it, should help other physicians make this diagnosis more quickly in the future.

Yu presented more on Claritas’s novel platform recently at Boston’s Bio-IT World meeting. He explained how the platform helps doctors to much more quickly and accurately diagnose kids with diseases not previously described.

“Thanks to the speed of the platform, we can get a whole clinical exome completed in as little as two weeks,” he said.

The growing database of genetic variants and their effects also means more patients will get an actual diagnosis, rather than walking away still wondering what could be going on.

The ability to diagnose more cases is a start to unravelling the causes of the estimated 7,000 different rare diseases estimated to exist. And it’s a necessary first step towards developing new therapies for those conditions, too.

Diversity in Genomic Data

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genomic diversity

Incorporating information from diverse populations into reference genomic databases is key to our mission at WuXi NextCODE.

Diversity is undeniably essential to genomics. To maximize the power of our field to revolutionize healthcare and improve patient outcomes, we must continually expand our understanding of the genetic factors that influence disease. Importantly, we must recognize that those factors are not uniform across all populations. At WuXi NextCODE, we believe that incorporating information from diverse populations into reference genomic databases is key to our mission.

As a recent article in Nature clearly describes, we have made great strides in expanding the diversity of genome-wide association studies (GWAS). Between 2009 and 2016, we have seen tremendous growth both in the number of studies (from 373 to 2,511) and in the number of individual samples (from approximately 1.7 million to almost 35 million). During that same period, however, the percentage of non-European samples included in GWAS grew from just 4% to roughly 20%.

The progress that has been made in the diversity of genomic data is mostly derived from the inclusion of studies that focus on Asian populations, such as the initiatives WuXi NextCODE has launched in China. Expanded diversity in GWAS will continue as more and more population-wide studies gain traction in non-European countries. Announced studies that will contribute to diversity in genomics include H3Africa (Human Heredity & Health in Africa), the Egyptian Human Genome Sequencing Project, and the Saudi Human Genome Program. And WuXi NextCODE is proud to have partnered with Sidra Medical and Research Center to develop the Qatar Genome Programme.

In addition to these global initiatives, we will gain a better understanding of genetic diversity through targeted studies in Europe and the United States. Specifically, we will benefit from research that focuses on underrepresented populations, such as the Hispanic Community Health Study/Study of Latinos and the Strong Heart Study of American Indians. Further, we will benefit as well from continuing investigation of diversity within European populations, including the work of WuXi NextCODE allies Genomics England and Genomics Medicine Ireland.

In all of these efforts, we seek to identify actionable associations not only between genetic variants and diseases, but also between genetic variations and drug responses. Thus, as diversity expands, so will important information about disease biology. Key questions will be answered: Which associations uncovered in studies built on GWAS for European populations will be replicated, and what new associations will be discovered?

At WuXi NextCODE, we appreciate the importance of gathering and analyzing data from diverse populations.  We supply research and analytical tools to ensure that the benefits of research extend to diverse populations.  Above all, we are committed to pursuing research and discovery goals around the world, leveraging our global footprint and global vision to maximize opportunities to discover meaningful associations that lead to improved treatment and better patient outcomes.

Genomic Information and the Importance of Communication

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Communicating clinically useful results both to doctors and patients will drive success

genomics-communications-hannes-smarasonAround the world, researchers and clinicians are taking on the challenge of integrating genomic analysis into medical practice. Physicians and patients are increasingly aware of the potential utility of genomic data. As genomics continues to become a more powerful tool in healthcare, there is a clear and compelling need for a commitment to excellence in communication.

At WuXi NextCODE, we are proud to provide sequencing and analysis resources that help doctors:

  • Shorten diagnostic odysseys, as I have discussed here; and
  • Improve treatment choices, as I have discussed here.

Maximizing the opportunities afforded by the ‘big data’ of genomics necessitates collaboration and communication, which I discuss in more detail here. As part of our genomics business, we are dedicated to the highest standards of communication – indeed, we view effective communication as central to how our technologies will improve health in both the near and the long term.

The task of harnessing the vast and expanding quantity of genomic data to improve clinical care requires interpretation and discovery powered to translate the data into clinically useful information. Leveraging that information to improve patient outcomes also requires clear and accurate communication:

  • Between researchers and clinicians;
  • Between specialists in different medical fields;

And, increasingly,

  • Between doctors and patients.

As the recent CLARITY Undiagnosed competition highlighted, applying genomic data to medical practice involves interpreting the sequenced genomes and identifying molecular diagnoses – and a third step: communicating clinically useful results both to doctors and to patients.

The CLARITY challenge winners, including WuXi NextCODE, were explicitly recognized for the quality and clinical utility of their reports.

Studies and surveys have shown that many people favor greater access to genetic information. Individuals want analysis of their genomes in order to:

  • Reveal their unique risk factors for inherited diseases;
  • Pinpoint a diagnosis if they are ill; and
  • Guide their decisions if they are seeking treatment.

Genomics is helping to inform patients in all these ways.

In addition, genomics demonstrates enormous potential to empower individuals.

The hundreds of thousands of people who purchase genomic testing through direct-to-consumer businesses like 23andMe are demonstrating a robust enthusiasm for gathering genomic information. And patients enrolled in clinical trials and donors participating in population-wide genomic studies express a desire to be more informed. Patients and consumers consistently seek resources that transform their personal genomic signatures into information they can use to make better healthcare and lifestyle decisions.

And most patients and consumers are willing – often eager – to share their genomic information to aid medical research and discovery. 23andMe reports, for example, that 80% of its customers consent to share their genomes for research.

It is unmistakably clear that, in the not-too-distant future, every individual in many countries around the world will have their genome sequenced. Throughout a person’s life, medical professionals will be able to access genomic information to guide health decisions – from identifying inherited conditions to assessing risk for complex diseases to calculating appropriate treatments, drugs, and even dosages for truly personalized healthcare.

The more effectively we communicate – the more we share information within the research community and parlay that into clinically useful information for patients – the greater the benefit to all.

As much as people understandably prefer simple, definitive answers to questions about their personal health, the information that genomics provides can be complex and even ambiguous. A genetic variant might be identified, for example, that can be tied to family medical history and translated into a probability or likelihood. This was the case for Angelina Jolie Pitt, who noted in her New York Times piece that her genomic analyses “gave [her] an estimated 87 percent risk of breast cancer and a 50 percent risk of ovarian cancer.” Percentage risks are nuanced, and individual perceptions of acceptable risk vary considerably. It is therefore difficult to define precisely the circumstances under which a genetic variant becomes clinically actionable.

Or a genetic variant might be identified which gives physicians clues but does not explicitly identify a specific disease. For example, a patient seeking a diagnosis may have a genetic variant that correlates to a number of diseases involving dysregulation of lipid metabolism. Identifying the variant provides physicians and caregivers with a clear direction for further analysis and treatment, but does not yield a conclusive diagnosis or prognosis.

Or a genetic variant might be identified which has yet to be understood as causing or playing a role in disease. Such a variant may occur by chance and have no medical relevance, or its meaning may be uncovered as science in the field advances. But for the person who is having the genomic information analyzed today, it offers no actionable information.

As all of these examples illustrate, effective communication about genomic information can be a significant challenge. There is a risk that poor communication will be a barrier to the adoption of genomic medicine, but if we strive to communicate clearly with patients and the public, our successes will likely accelerate more widespread use of genomics. The role of genomics in transforming health care will grow exponentially as we all endeavor to improve communication with patients, their families, and the public at large.

Our work at WuXi NextCODE is advancing the transformation of medical practice through genomics. As part of that vision, we recognize the critical importance of facilitating effective communication among all stakeholders. We provide the resources that enable researchers and clinicians to identify disease and inform treatment decisions. And we strive to add additional value by communicating about genomic information accurately and proactively, all with the ultimate goal of meaningfully improving patient outcomes.

Genomics: Big Data Leading to Big Opportunities

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The Big Data of Genomics

WuXi NextCODE Exchange

The big data of genomics will continue to expand, and our approaches to analyzing genomic data need to continue to evolve to meet the growing demands of clinicians and researchers. Cloud-based platforms such as WuXi NextCODE’s Exchange are essential to address the fundamental big data challenge of genomics.

Beyond question, we are in the midst of an explosion of “Big Data” in many facets of human endeavors. In fact, data-storage leader IBM asserts that roughly 2.5 quintillion bytes of data are generated every day and 90% of the world’s data was created in the last two years.

An outpouring of articles in scientific journals and major newspapers has highlighted the promising potential of big data in medicine, including a special section in the current issue of Nature.  Genomics has become a major source of the growth of such big data, particularly as the cost of sequencing genomes has plummeted. The raw sequence data for just one person’s whole genome use as much as 100GB—and already hundreds of thousands of individual genomes have been sequenced.  With more than 2,500 high-throughput sequencing instruments currently used in 55 countries across the globe, more genomes are added every day. The aggregate amount of genomic data is growing explosively, and next-generation sequencing (NGS) sequencing data are estimated to have doubled in volume annually since 2007.

The accumulation of genomic data is a worldwide phenomenon.  Impressive population-wide sequencing efforts are leading the way, from 100,000 genomes in England, Saudi Arabia, and Iceland to 350,000 in Qatar to a million in both China and the U.S.

And earlier this month, the CEO of the Cleveland Clinic predicted that soon children will routinely have their whole genomes sequenced at birth, implying a near-future in which 10s of millions of new genomes are sequenced annually.

Turning Data into Resources

But sequencing genomes is not enough, and the creation of genomic big data is just the beginning.

Thanks to the analysis of big data in genomics and associated informatics, we are seeing meaningful progress in cancer care and the diagnosis of rare diseases, as I have discussed here and here. We clearly have a tremendous opportunity to use the big data of genomics to continue to drive a revolution in healthcare.

Yet there is a broad consensus that a ‘data bottleneck’ is hampering collaboration and discovery. Not all researchers and physicians confronting the current onslaught of genomic big data can readily determine how to use genetic information to prevent or treat disease. To succeed, researchers and physicians clearly need resources that:

  • Draw together useful data from disparate sources;
  • Facilitate analysis and collaboration; and
  • Improve clinical practice.

The power of genomic analysis needs to expand outward from major research centers and hospitals to the myriad clinics and community hospitals where many patients receive care. To have the greatest impact on the broadest population, clinicians throughout the world’s health systems need access to the big data generated by DNA sequencing, even—or perhaps especially—if they are not affiliated with research institutions. They also need to be able to make sense of the data they have access to.

Answers in the Cloud

Sequencing provides the raw data to uncover the genetic variants that contribute to disease. But the datasets are too big to transfer repeatedly—and too big even for smaller hospitals, labs, or clinics to store onsite. Key medical advancements require not only big data, but also tools and resources to generate, interpret, and share analysis of millions of genomes.

Cloud-based platforms—such as WuXi NextCODE’s Exchange—are essential to address the fundamental big data challenge of genomics. Collaboration in the cloud works to dismantle existing “data silos”—genomic information hosted only on local servers and analyzed on idiosyncratic, closed platforms. The NextCODE Exchange, in contrast, is a browser-based hub that affords secure, seamless collaboration with colleagues around the world. Moreover, users get access to NextCODE’s tools for making the critical links between variation in the genome and disease and other phenotypes, backed by harmonized links to the the most important public reference data.

And cloud-based computing is inherently scalable: resources for data storage and analysis expand as needed, allowing researchers and physicians to leverage massive datasets to improve patient care in the clinic. The big data of genomics will continue to expand, and our approaches to analyzing genomic data need to continue to evolve to meet the growing demands of clinicians and researchers.

At WuXi NextCODE, we have built upon our heritage of conducting the largest analysis of genomic data (deCODE’s path-breaking Icelandic analysis) by assembling an ever-growing database of human genomes. We are committed to driving the movement of sequence data into patient diagnosis and care through user-friendly, leading-edge analysis and informatics. I am confident that data analysis and collaboration in the cloud will revolutionize healthcare, and exceptionally proud that WuXi NextCODE’s Exchange is at the forefront of this exciting advancement.

FDA Approval Moves DTC Genetic Testing Forward

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DTC genetic testing, Hannes Smarason

23andMe is relaunching its direct-to-consumer genetic tests in the U.S. with the approval of the FDA to provide consumers “carrier status” information on 36 genes that can cause rare diseases. I am optimistic that DTC genetic testing will expand its impact over time, ultimately having a tremendous impact on human health globally.

Today, genomics industry maverick, 23andMe, is relaunching its direct-to-consumer (DTC) genetic testing in the U.S., with the approval of the FDA to inform consumers whether they carry a genetic variant for one of 36 rare diseases that could potentially be passed on to their children. In addition to this carrier status information that now meets FDA standards, reports from the newly launched 23andMe test will include information on wellness, traits, and ancestry.

A big positive step forward

For the genomics industry as a whole, this is a significant step forward as the FDA’s decisions have global influence. Indeed, this is a landmark FDA decision, as it is the first time ever that the FDA has allowed such a broad spectrum of medically relevant genetic information to be provided directly to consumers. Both the FDA and 23andMe deserve credit for working through the challenges that, less than two years ago, resulted in the FDA ordering 23andMe to stop marketing its genetic testing kits in the U.S. That the FDA—one of the world’s most thoughtful medical regulatory agencies—has come so far so fast is indicative of the potential it likely sees in DTC genetic testing improving the health of U.S citizens.

A larger journey ahead for direct-to-consumer genetic testing

Moving forward, there are at least two important directions that—in collaboration with the appropriate regulatory agencies, such as the FDA—I think DTC genetic testing will advance:

• DTC genetic testing will expand its reach globally; and
• DTC genetic testing will likely expand the medical impact of its reported results.

DTC genetic testing will expand its reach globally.

Catalyzed by demand for improved health, DTC genetic testing services will inevitably become accessible to much of the world’s population over the decades to come. To be successful, these services will need to be customized by geography and culture and approved by the appropriate local governmental agencies. While the genome is shared by all humans, it is naïve to think that DTC genetic testing services will be the same across all people living anywhere. It is incumbent on industry participants to align their DTC reports and services to best meet the needs of the specific customers in specific countries and geographies—and to do so in a spirit of cooperation with the appropriate governmental health regulators.

DTC genetic testing will likely expand the medical impact of its reported results.

As noted, today’s FDA approval for 23andMe to be able report on carrier status is a significant step forward, but more health data remains to be gleaned—and reported—from an individual’s genomic data. From 23andMe’s announcement, you can see the foreshadowing of what may ultimately be possible:

About [23andMe’s] Carrier Status Tests
[23andMe’s tests] can be used to determine carrier status in adults from saliva collected using an FDA-cleared collection device (Oragene DX model OGD.500.001), but cannot determine if you have two copies of the genetic variant. Each test is most relevant for people of certain ethnicities. The tests are not intended to diagnose a disease, or tell you anything about your risk for developing a disease in the future. On their own, carrier status tests are not intended to tell you anything about the health of your fetus, or your newborn child’s risk of developing a particular disease later in life.

Clearly, working with regulators such as the FDA, and others, such as thoughtful genetic counselors, there is a future potential for the right service to be able to report on people’s risk for developing specific diseases. Informed, health-conscious consumers are very likely to demand access to this information—and millions of individuals have already paid significant sums out of their own pockets to have their genomes sequenced and analyzed. Indeed, from news reports covering 23andMe, we know that when ordered by the FDA to stop providing health information such as the disease risk, their rate of new customer sign-ups dropped by more than half.

I am very optimistic that DTC genetic testing will expand its impact over time, overcoming skepticism and ultimately having a tremendous impact on human health globally. I am proud that our team at WuXi NextCODE will be a part of making this exciting future happen, and today I am especially proud that WuXi Ventures recently invested in 23andMe, making us active supporters of its current and noteworthy success.

Four Factors for Improving Genomic Data for Personalized Medicine

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advancing the use of genomic data for personalized medicine

The pace of progress has been astounding with advances in the use of genomic information to provide faster, more accurate, and more in-depth information to enable personalized patient care.

We’ve come a long way in improving the way that a patient’s genome sequence data is analyzed and interpreted to realize the full potential of personalized medicine. Here are four factors helping to overcome barriers and achieve new milestones for using genomic data to provide faster, more accurate, and more in-depth information to guide clinicians in delivering personalized care for patients.

Factor #1: Fast database query of the genome

Problem: Relational database architectures make it possible to store large quantities of sequencing data, but querying whole genome data can be time-consuming and take days to weeks.

Solution: The GOR (Genomic Ordered Relations) database is able to query whole-genome sequences in real time. The reason is that GOR understands the genome in terms of chromosomes, its natural structure, rather than as a continuous string of sequence. That’s both intuitive and innovative. When searching for a variant, tools in the GOR architecture don’t have to scan each individual’s entire sequence; they retrieve the variant straight from its location. Annotation data – information on what diseases or conditions variants have been linked to – are also stored in the same way. The GOR database was pioneered a decade ago by deCODE genetics, one of the first organizations to manage truly large genetic datasets, and is now being used by NextCODE for clinical applications of genomic data.

Factor #2: Fast, reliable identification of disease-causing variants

Problem: Many sequencing analysis pipelines are only powered to process data in a compressed format called Variant Call Format (VCF) files. These comprise only a tiny fraction of the genome, and being working only with VCF files makes it difficult to correct common alignment and allele-calling errors. That can result in both false positive and negative results, or to missing the key causative variants altogether.

Solution: The foundation for improved sensitivity and specificity is the ability to use VCF data on top of the raw sequence data from which it was derived. NextCODE’s pipeline and clinical interfaces, powered by GOR, give users the ability to go back to and visualize raw sequence data at a click. This approach enables genomic analysis and interpretation by seeking out disease-causing genetic variants, either in specific patients, or for research studies in a clinical setting.

Factor #3: Patient genomic information at the fingertips of the clinician

Problem: Many of today’s genomic interpretation tools are too complex and difficult to use by clinicians who may have minimal experience with genetic informatics tools.

Solution: All of the complex informatics required by a clinical analysis tool should disappear at the fingertips of a clinician. It starts by having a robust foundation to the informatics platform, and using the GOR database architecture enables rapid cycling between personal sequence data and broad clinical knowledge. The result is the Clinical Sequence Analyzer (CSA) in which clinicians can simply type in a patient’s symptoms, and CSA will search the patient’s whole genome for variants that may be relevant.

Factor #4: Applying the full power of whole-genome sequencing to cancer tumor analysis

Problem: Many of today’s approaches to the analysis of cancer genomes only look at the immediate next step for a course of treatment, an important capability but only part of a holistic view of a the genetic profile of a patient’s cancer and what can be done to fight it.

Solution: The Tumor Mutation Analyzer makes a more holistic approach possible, analyzing a whole exome or whole genome sequence from a patient’s own genome and from tumor cells. Comparing the two it is possible to isolate the variants likely to be cancer drivers. The distinguishing feature of TMA is the depth of the data it stores and the unprecedented level of detail it provides to more accurately identify variations. This level of detail is especially important in cancer genetics, where the chances of finding previously unknown variants are very high, and even if a mutation is successfully targeted with a course of treatment, another potential driver is often waiting in the wings.

The pace of progress has been astounding with advances in the use of genomic information for patient care. How will the path continue in the future? Stay tuned.


 

Personalized Medicine: The Future is Almost Here

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The new era of personalized medicine.

The achievement of low-cost genome sequencing and the use of genomic data to better understand diseases are advancing the exciting new era of personalized medicine.

It’s been more than a decade since the human genome was first sequenced. Since then, we have been on the journey of applying this profound new discovery to create personalized medicine and advance human health.

Two significant triumphs along this human genome journey:

  • Using genomic data to better understand diseases; and
  • Achieving low-cost genome sequencing.

Each of these accomplishments has been a stepping stone into the exciting new era that is dawning now: where genomic information is becoming integrated into medical care.

Using Genomic Data to Better Understand Diseases

Let’s take a look back at the early days of using genomic data to connect the dots between genetic mutations and disease. From 1997-2004, I was part of the leadership team at deCODE, the Icelandic genomic company. This was the period when deCODE was building the world’s most productive human genomics platform, with a database of  tens of thousands of individuals who participated in genetic studies and including the largest database of genomes to this day. deCODE’s genomic engine was able to successfully identify the genetic variations associated with human disease. This resulted in dozens of groundbreaking discoveries that were published in major, peer-reviewed journals.

The legacy of deCODE was the creation of an industrialized platform capable of massive storage and analysis capabilities. This enabled researchers to crunch genomic data to gain insights about genetic variants, or risk factors, associated with many common diseases. deCODE’s premise was that once the genetics of disease was better understood that information could be used to create new ways to diagnose, treat and prevent disease. However, when I left deCODE in 2004, there were still barriers to overcome before this genomic information could be widely applied to the level of an individual patient. Chief among them was that the cost of genome sequencing was still prohibitively high. (deCODE was subsequently acquired by Amgen).

Achieving Low-Cost Genome Sequencing

Back in 2004, the cost to sequence a single human genome was hundreds of thousands of dollars. Today that cost is a few thousand dollars (and, in fact, fast approaching $1,000) for a whole genome sequence. DNA sequencing costs continue to fall, as speed and accuracy increase.

This means we are rapidly approaching a tipping point where, as the sequencing of human genomes becomes more economical, its adoption in the medical community becomes more widespread and genomic data can become more routine in medical care. This is why personalized medicine is becoming a reality.

The Era of Genome Sequencing in Medical Care

The steep drop in the costs of sequencing, combined with the explosion of research on gene variants and disease, mean the time is fast approaching when genome sequencing will become routine in medical care. Today, pathologists perform blood cultures to decide which antibiotics will stop a patient’s bacterial infection. Soon a patient sample can be taken to perform a genome sequencing to analyze the genetic characteristics of a patient to determine ways a disease can be prevented or, if they are sick, which treatments might work best for their disease.

The body of genomic knowledge and the large databank of human genomes built by pioneers like deCODE established the key building blocks that enable genome sequencing to have predictive power for individual patients. As more human genomes are sequenced and more genetic variants are associated with disease, the predictive power of knowing about risk genes and effective treatments for each patient – a.k.a. personalized medicine – will become an essential part of medical care.

Genome Sequencing Being Implemented by Medical Centers

In preparation for the future of personalized medicine, major medical centers in the U.S., Europe and Asia are actively beginning to install DNA sequencers and supercomputers as important tools for integrating genome sequencing into medical care. These medical centers are taking initial steps toward the routine sequencing of every patient’s genome to define the ideal course of prevention and treatment based on variants found in a patient’s genes.

Evidence of this adoption of genome sequencing by medical centers appeared in an article in The New York Times in April 2013 citing that:

  • Medical centers in New York City are spending more than $1 billion on new genomic research centers;
  • Several hospitals around the U.S. are undertaking systematic genome sequencing in patients;
  • Mount Sinai Medical Center has a program in which 24,000 patients participate in a biobank to include their DNA sequence and research over their lifetimes;
  • Memorial Sloan-Kettering Cancer Center sequenced 16,000 tumors from cancer patients in 2012; and
  • Phoenix Children’s Hospital opened a new institute in December 2012 to sequence the genomes of 30 percent of their childhood cancer patients.

For now, the use of whole genome sequencing in medical practice is still in its infancy, but the pace of progress continues to accelerate. Clearly, genome sequencing will soon become part of the nucleus of medical care. This will herald a new era in personalized medicine revolutionizing healthcare as we know it and transforming our lives. When do you think genome sequencing will become a part of the medical decisions in your life?