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WuXi NextCODE Partners with Google Cloud

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We’re delighted to announce an alliance between WuXi NextCODE and Google Cloud. This partnership will provide our customers and partners yet another world-class option for accessing a growing genomic data analysis toolset capable of fueling real breakthroughs in research and clinical care.

WuXi NextCODE is building the global standard platform for using genomic data at scale and over the internet. Our offerings already include our pioneering GOR database management system; our own secondary analysis pipeline; the Sequence Miner case-control research application; and the Clinical Sequence Analyzer interpretation system.  Google, meanwhile, has one of the world’s leading cloud platforms as well as its own outstanding genomics tools, such as BigQuery the DeepVariant secondary analysis pipeline, as well as full integration with other open-source tools that many are eager to leverage in tandem with ours.

As pioneers of using the genome online, working with Google in genomics is clearly exciting. Through this partnership, Google Cloud will host the entire suite of WuXi NextCODE’s core offerings and make these available on the Google Cloud Launcher Marketplace. This will provide users our combined IT horsepower and a full range of tools to perform at the leading edge of genomic research and clinical interpretation.  We expect to launch our tools on Google Cloud in May, at the BioIT World Conference & Expo in Boston.

As we build the global standard platform for genomic data, WuXi NextCODE has been making crucial partnerships to ensure our clients have the most options for accessing the full range of tools they need, however they prefer to do so.

Read more about this remarkable partnership at the WuXi NextCODE Genomics Insights blog or in our press release.  It is an important step towards realizing our vision to provide people and organizations with the best tools for using genomic data – wherever they are and at internet speed.

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Why We Need Big Infrastructure For Tackling Rare Disease

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Hannes Smarason big data rare diseases

Having bigger databases, and having a mechanism that flags genomic variants, is key to optimizing patient care for entire families

Uncovering the genetics of schizophrenia is vital but challenging. As I wrote in my last post, mutations in more than 100 spots in the genome have been linked to the condition. But which ones actually play a role in the disease, and which ones are just there for the ride—innocent bystanders that just happen to occur alongside the real culprits? That’s the crucial question for scientists seeking new treatments for this condition, among them leading researchers and clinicians at our close partner, Boston Children’s Hospital (BCH).

One thing we’ve learned recently is that even a small amount of knowledge about genetic underpinnings of disease can have a big potential benefit for patients. For example, the 16p13.11 region deletion I described in that last post ended up being very important for several patients later, particularly one father and his son, recently described by our colleagues at BCH. This case highlights the importance of expanding the scope and scale of such research, and of updating and alerting patients as more is discovered—not just in schizophrenia, but across rare disease.

In their previous work, the BCH team used chromosomal microarray analysis to determine that a young boy with symptoms of schizophrenia, including psychosis, was missing an entire chunk of DNA—one copy of the chromosomal region 16p13.11, which spans several genes.

Schizophrenia in children is rare, and some researchers believe it could be an extreme variation of the disease, and so might hold important clues for the treatment of this condition in both young and old. A search of our and BCH’s databases showed that several other young patients also showed variations in that region. Just as important, it was confirmed that a parent of one of those patients also carried that deletion, and it seemed likely that another parent (not available for testing, but with reported symptoms of schizophrenia) also likely carried the deletion.

Clearly 16p13.11 seemed to be emerging as a “hotspot” for variations linked to psychosis. But the scientists were only finding this because they could go back and search the databases, and they were working their way backwards from pediatric cases to learn information that might have been medically relevant to the parents as well. All this suggests that having bigger databases, and having a mechanism that flags such variants, is key to optimizing patient care for entire families.

One case uncovered by the BCH scientists, regarding a young man who we will call Jack, brought this into sharp focus. As a teenager, Jack had undergone detailed genetic screening at BCH because of symptoms that included learning disabilities and recurrent seizures. It was determined that he had a 16p13.11 deletion, but at the time of his screening, that mutation hadn’t yet been linked to psychosis. So it became just one more detail in Jack’s medical record.

Separately, a few years later, Jack’s father was diagnosed with ADHD and treated with a high dose of mixed amphetamine salts. Within a few weeks Jack’s father experienced a manic-psychotic episode. He was prescribed an anti-psychotic and eventually recovered. Unfortunately, his son was deeply affected by his father’s breakdown and became withdrawn and depressed. Eventually, Jack also developed psychotic symptoms, which were so serious he was hospitalized.

Jack’s symptoms, thankfully, responded to anti-psychotic medication, but his doctors wondered if there was any connection between the breakdowns suffered by the father and son.

A check of Jack’s medical record revealed the 16p13.11 deletion. And seeing that detail after the link had been made between 16p13.11 and psychosis, his doctors immediately speculated that it might be a cause of Jack’s symptoms. Further, they suspected that mutation could be the “linchpin” causing psychosis in the father and the son. Jack’s father was tested, and he also carries a 16p13.11 deletion.

So here’s the lesson: if Jack’s doctors had known about the link between 16p13.11 and psychosis as soon as it emerged, they might have also suggested testing Jack’s father. If they had, the BCH doctors “believe that the psychosis could have been averted in both father and son.”

In light of this case, the BCH researchers write that they see a keen need for broad, integrated, and sophisticated infrastructure to support genomics-driven precision medicine. They have several recommendations, including that physicians need to receive regularly updated risk information about specific mutations; genetic reports on parents who are “carriers” but seem unaffected should note that problems could arise later, and families that include carriers of variations that increase risk should be monitored and given counseling.

Such activities will be well supported by tools such as WuXi NextCODE’s Genomically Ordered Relational (GOR) database and global platform for diagnosing rare disease and building a global knowledgebase. This can act as one of the key spokes in the “wheel” of genomic diagnostic process. But we also need to build in others, such as means to automatically alert doctors to important knowledge updates, monitor patient records, and connect doctors to specialists who can help refine a diagnosis as new discoveries are made. We and our partners at BCH are committed to helping create these tools.

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Headed to ASHG? If you are attending ASHG this month, join us to hear more about how rare disease studies can inform our understand of common diseases at two of our “Genomes for Breakfast” events: “Using Population Genomics to Understand Common and Rare Disease” (Oct. 18), and “Using NGS to Diagnose Rare Disease—Experiences from Three Continents” (Oct. 19).

Marking Progress in Genomics: Reflections and Prospects

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Progress in Genomics WuXi NextCODEAs leaders of our field gather in Vancouver for the annual American Society of Human Genetics Meeting (ASHG 2016), it is an excellent time to take stock of the past and clarify our perspectives for the future. For the field of genomics, this is an opportunity both to reflect on our accomplishments over the last few years and to consider what we can achieve in the years ahead.

Indeed, our accomplishments have been numerous and our goals are ambitious, yet achievable. Here, I would like to summarize five significant ways in which our work in genomics has been revolutionizing medicine and improving patient outcomes.  In addition, I would like to share my thoughts about five areas in which I believe our field can drive meaningful change over the next few years.

What We Have Achieved
1. Improvements in Sequencing Technology and Analytical Tools
The ever-increasing volume of genomic data is testimony to the dramatic increases in sequencing speed and efficiency over recent years.  At the same time, novel methods of analysis, like the powerful genomics platform employed here at WuXi NextCODE, have considerably advanced our understanding of genetic variations and their clinical significance.

2. Transformations in Cancer Treatment
As I have discussed here, the expanding use of genomic data to guide treatment decisions in oncology is transforming the way clinicians approach cancer treatment.  In addition, our growing understanding of genetic predispositions for certain cancers is helping high-risk individuals make informed choices about preventive care.

3. Progress in Rare Diseases
Genomic data has brought new hope to families struggling with rare diseases by shortening diagnostic odysseys, guiding treatment, and building communities.  I provide examples of the game-changing power of genomics in the diagnosis of rare diseases here.

4. Empowerment of Patients and Consumers
Patients and consumers are increasingly informed about the innovative and meaningful ways in which genomic data can guide healthcare decisions.  The successes in our field are empowering individuals to pursue personalized medicine and generating interest in direct-to-consumer testing.  I offer my thoughts about DTC genetic testing here.

5. Innovations in Cloud-Based Analysis
The vast and ever-growing quantity of genomic data and related information necessitates new approaches to storage and analysis.  As I have previously discussed, cloud-based computing is essential to continued success in genomics.  WuXi NextCODE’s Exchange is at the forefront of the accelerated research made possible by real-time collaboration and analysis in the cloud.

What We Can Achieve in the Years Ahead

1. Effective Communication and Collaboration
Realizing the full potential of big data and cloud-based computing will require new efforts to dismantle “data silos.”  I am encouraged by recent initiatives to facilitate collaboration in cancer research, and – as I have recently discussed – call upon researchers and clinicians throughout the field of genomics to improve communication among all stakeholders.

2. Policies for Research with Patient Data
Our field derives its greatest power from careful analysis of genomic data, and access to data is critical to effecting meaningful change in healthcare.  In order to gather this game-changing data – from patients, from consumers, and from population-wide studies – we need to develop and embrace policies that lead to consider the ‘biorights’ of patients.  Individuals who wish to contribute information for research should have the opportunity to do so, and all parties should clearly communicate the purposes and extent of data-sharing.

3. Integration for Clinical Trials
I perceive significant movement toward the development of clinical trials that test the efficacy of treatments tailored to specific genetic anomalies – and use genetic information to screen participants.  This is an area in which genomics will dramatically accelerate the development of personalized therapies that will surely improve patient outcomes.

4. Actionable Information from Population-Wide Genomic Studies
I believe that in the near future we will reap significant rewards from projects that gather population-wide genomic information.  Analysis of the data we are collecting around the world, which I describe here, is an essential step to reshaping healthcare practices worldwide.

5. Globalization of Genomic Products: ‘Think Globally, Act Locally’
The power of genomic information is now known throughout the globe, and can be applied in a multitude of positive ways.  With such widespread potential, individual countries and cultures will choose to advance and roll-out genomics in their own distinct ways for the benefit of their citizens.  Companies that develop genomic products will need to adapt and design their products for use in specific markets.  At WuXi NextCODE, the first focus of our product portfolio for individual patients and families is in China, where we are delivering three offerings: population-optimized diagnostics, carrier screening, and whole-genomic wellness scans.

Together these initiatives build upon our recent accomplishments and further the creation of data and analysis necessary for meaningful change in healthcare.

The genomic revolution in medicine that we envisage will be achieved through applied use of research and development that is:

  • Fueled by big data, including data provided by informed consumers and patients and data derived from population-wide studies;
  • Supported by clinical trials crafted to assess the safety and efficacy of treatments tailored to individual characteristics; and
  • Enabled by collaborative work and effective communication.

At WuXi NextCODE, we are energized by the prospects for genomics in the years to come. We are proud to be at the cutting edge, providing the tools and resources that researchers and clinicians need to harness the transformative power of genomic data. And—importantly—we are confident that our field will continue to drive meaningful changes in healthcare that improve 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.

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.


 

The Technologies That are Key to Unlocking Genome Analysis

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Lower-cost genome sequencing, genomic analysis tools support personalized medicine

Lower-cost genome sequencing, genomic analysis tools, and reference databases for human genomes are the “3-legged stool” that will help the world reach personalized medicine.

Genome sequencing technology available today can accurately sequence a whole genome from an individual’s test sample for a surprisingly low cost—a few thousand dollars (and dropping fast). As a result, the adoption of this technology is rapidly expanding as medical centers around the world embrace its utility in informing healthcare decisions—an emerging reality of personalized medicine.

Three important areas of technology progress have enabled the medical community to reach this point:

  1. Lower-Cost Genome Sequencing: Major technological advances have reduced the cost of sequencing to nearly $1,000 or less, a critical milestone to enable the use of sequencing as a mass-market product for medical care.
  2. Genomic Analysis Tools: Since the human genome was first sequenced more than a decade ago, an increasingly robust body of research has showcased the links between mutations identified in the genome and disease risk. Informatics tools have been developed by medical centers and genomics companies to apply to whole-genome samples. Increasingly, these genome analysis tools will need to adapt to the steady pace of new genomic linkages to disease and to operate at a level approaching “big data.”
  3. Reference Databases for Human Genomes: There are a growing number of robust databases of human genomes, including data for healthy people or those with certain diseases.  When properly analyzed, these databases offer the potential to provide the medical community with a reference library against which to compare genetic data. Large-scale, high-quality databases are an essential element to cross-reference a patient genome to guide more informed medical decisions.

These three technology domains represent the “3-legged stool” that will help the world reach personalized medicine. The technology is in place, and the corresponding insights and uses are expanding every day. Yet there are challenges to be resolved before implementing these tools on a universal basis.

For example, logistically, how will new DNA and supercomputing equipment be accessed by medical centers, and how will the data be stored? And more importantly, what is the most efficient way to compare an individual’s genome to the massive body of genomic information available to help inform medical decisions for that patient?

One important part of the solution: we must turn to “big data” solutions to manage and make use of the enormous amounts of data produced through sequencing. The whole-genome sequence of a single human is roughly 100GB—that’s the entire storage capacity of a single Macbook Air®.

The progress to date has been amazing. Yet the opportunities ahead are even more extraordinary to improve the speed, accuracy, and accessibility of genomic information to improve human health.