Cool Startup: GenoSpace

daniel meyer

Healthcare is drowning in a deluge of data. Decision-makers must somehow make sense of a heterogeneous array of information — demographic, clinical, patient-generated, treatment and outcomes data. The latest waves of information also include data from mHealth and genomic sources. It’s not hard to imagine that many in the healthcare industry suffer from information overload and struggle with a bit of ‘analysis paralysis.’ How can organizations make sense of all this big data and actually harness it to improve healthcare and outcomes?

One company helping answer this question is GenoSpace, an ambitious genomic and health data management startup based in Cambridge, Mass. Its current chairman, John Quackenbush, and CEO, Mick Correll worked together in the Center for Cancer Computational Biology at Dana Farber before co-founding the company in 2012. Contracts with notable customers like the Multiple Myeloma Research Foundation (MMRF) and PathGroup funded GenoSpace before the first round of outside funding in 2014.

It was around that time that GenoSpace hired Daniel Meyer, an entrepreneur with a background in venture capital, as Chief Operating Officer. According to him, it was GenoSpace’s ability to attract high-quality customers early on (a rarity for most early-stage companies in life sciences) that convinced him to join. Recently, we sat down with Meyer to learn more about how GenoSpace helps healthcare organizations make sense of all the big data.

Tell us about what you do at GenoSpace.

When you’re dealing with genomics and other biomedical data, there are a variety of different users and reasons for their use. So you could have an institution that has users engaged in research, clinical development, lab medicine and clinical care. They have different software application needs that cut across the same or similar data sets. One of the things we try to do is develop the tools, the interfaces and the experience that will enable all of those different people to get the most from the data.

Could you go over your major offerings?  

We have three primary categories of offerings: analysis and interpretation of a single assay result together with phenotypic and other clinical data, interactive analysis of data from many individuals as a group, such as from a large observational study (where we really excel is when a customer has integrated demographic, clinical, genomic, treatment, outcomes and other data) and enabling patients to directly report and interact with their data. We’ve created software applications and web-based sites for patients to upload their data, track their results and better understand their condition. Although we have a core competency in genomic data, we do not only deal with genomic data.  Research and clinical care rarely rely solely on a single data type.

Now that Obama has announced the Precision Medicine Initiative expanding genomic study, do you also expect your work to expand?

We think it’s a fascinating announcement and those are the types of initiatives we support. One of the interesting things is that we have customers right now solving many of the problems that the initiative will face. For example, we have been working with Inova, a healthcare system based in Northern Virginia that serves more than two million people per year in the metro DC area. They have been collecting a rich set of whole-genome sequencing data together with structured clinical data on thousands of people. Their data management and analysis needs map directly to those of precision medicine initiatives like the one announced by the White House.

I’d imagine that you’d have greater demand on the private side.  

We have spent most of our time there. Our first clinical lab customer, PathGroup, is delivering industry-leading molecular profiling across a wide geographic footprint, including to some big cities in their coverage area and also smaller cities and towns.  Our ability to help them bring academic-quality medicine to community oncology is a huge impact. Roughly 85% of oncology patients are treated in a community setting. If you’re only deploying in major cities with academic medical centers, you’re missing out.

What are your next plans? Any new projects or goals?

We are  looking to expand to different customer use cases. That can be in terms of the therapeutic indication, such as rare diseases, neurologic or cardiac disease. But it can also be integrating different kinds of data. We have a lot of experience working with demographic, diagnostic, treatment and outcomes data together with genomic results, and there are more opportunities to expand.

Are you also working on using machine learning to do predictive analytics?

We think about that a little differently. There’s supervised analysis, the user asking questions and getting answers about the data, and there’s unsupervised analysis. For many of our customers, they’re not looking for a black box. Our goal is not to replace molecular pathologists, but to work hand in hand with them to make sure their work is better, more operationally efficient and more sustainable, particularly if it’s a commercial entity.

That last piece is underappreciated by a lot of folks. We do a lot of work in genomics and in precision medicine and there’s a lot of science and advanced technology. All that work is lost in most settings if you don’t deliver it properly. You have to understand the science and the innovation, but also how to get it in the hands of people who can impact patients. That’s a big part of what we do.

Any final thoughts?

One of the fun things about being here is we have folks with a lot of different capabilities—in software engineering, interactive design, data science, etc. For a lot of the interesting problems that people are trying to solve in medicine, it takes that interdisciplinary team approach as opposed to a whole bunch of people with the same type of experience.

To learn more about GenoSpace, visit their website at genospace.com or follow them on Twitter at @GENOSPACE.

This article was originally published on MedTech Boston.

Precision Medicine: Pros & Cons

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23 chromosomes (image from Scientific American)

This past week, President Obama announced a $215 million proposed genetic research plan, called the Precision Medicine Initiative.  According to the plan,  the NIH would receive $130 million towards a project to map the DNA of 1 million people, the National Cancer Institute would receive $70 million to research the genetic causes of cancer, the FDA would receive $10 million to evaluate new diagnostic drugs and devices, and finally, $5 million would be spent on tech infrastructure to analyze and safely store this data.

Not surprisingly, this announcement sparked some online controversy.  If internet pundits are to be believed, this plan is going to prevent you from ever finding a mate, an employer, get health insurance, cause us all to become part of a giant genetic experiment to tailor human beings, and will also put us into crippling debt and line the pockets of Big Pharma.  I’m not even sure I covered it all…The complaints ranged from reasonable to ridiculous.  The most amusing are the conspiracy theorists who are certain that Obama must be plotting a genetic apocalypse.

But, in all seriousness, I have to admit I have concerns as well, despite being mostly optimistic about this news.

Here are some of the exciting positives offered by the precision medicine plan:

  • New diagnoses:  We may finally be able to identify genetic causes of diseases that were previously unknown.
  • Prevention vs. disease management:  Knowing genetic risks ahead of time can help us to focus more on preventing disease rather than reacting after-the-fact, once the disease occurs.
  • Early diagnosis:  We may be able to detect diseases earlier and at a more treatable stage.
  • Protective genes:  Some people have certain genes that protect them against diseases or prevent them from “expressing” their bad genes.  Studying these differences may help us to learn how to protect ourselves against those diseases.
  • Drug development:  Therapies can be developed in a faster and more efficient way by targeting certain genetic problems, rather than using the traditional trial-and-error method.
  • Personalized treatments:  Treatments can be tailored to a patient’s unique genetic aberration and we can avoid giving treatments to patients that we know may cause adverse reactions or that will fail to work.
  • Population health:  We can study genetic patterns in populations of patients to find out causes of diseases, develop treatments, and find ways to prevent disease.
  • Healthcare costs:  There’s a potential to reduce healthcare costs if focus changes to prevention rather than treatment of disease and also if we can streamline drug development.

But, let’s also look at the potential downsides:

  • Data storage:  We already know that gene sequencing of an individual produces MASSIVE amounts of data.  The sequencing of a million people is going to produce unimaginable amounts of data.  How will we store all this big data and analyze it to make any sense of it?
  • Privacy/Security:  Is there anything more personal and vulnerable to cyber-attack than your genetic information?  I wonder if the $5 million allotted to this effort will really be enough.
  • Data relevance:  According to Obama, the data will be collected from 1 million volunteers.  That’s not a random cross-section of people in the US and may not represent the population adequately in order to make population health recommendations.  I’d argue that only certain types of people would sign up and other types won’t.  Would we miss certain disorders? Would we see too much of another disorder in a population of volunteers for this project?
  • Culture:  How do we prevent people from abusing this information and not using it to screen potential partners, deny insurance coverage, denying jobs?  How will this affect culture?  Will we be cultivating a different kind of racism, on a genetic basis?  Are we on the path to a real-life version of the movie Gattaca?
  • Ownership:  Who will claim ownership of this data?  Will it be the government?  I’d argue that this data should be owned by the individuals from whom it comes, but the experience of the genetic sequencing (now genetic ancestry) company 23 & Me is worrisome.  For the time being, the FDA has blocked the company from allowing individuals from having access to their own genetic information.  Will this change as part of the new initiative or not?
  • Drug/device industry:  Genetic research and development of treatments has been very promising and productive in the private sector.  How will government involvement affect research?  Will our governmental agencies work cooperatively with them or competitively?  Again, if the experience of 23 & Me is any indication, this is a real concern.
  • Healthcare Costs:  Yes, there’s potential to decrease costs, but there’s also potential in greatly increasing costs.  It’s no small feat to genetically map a population, analyze the information, store it safely and securely, and develop recommendations and treatments.

Part of me is excited about the potential and I think that it probably does take a huge governmental initiative to tackle and impact population health, but another part of me is concerned about government invading a space that is so personal and private and I wonder if it could slow down progress in developing life-saving therapies in the private sector.

What do you think?  Are you excited or nervous about President Obama’s Precision Medicine Initiative?