Bio+Tech was started as a monthly gathering to bring together the best and the brightest entrepreneurial minds in biomedicine and combine them with leaders in the SF tech start-up world.  The idea was that we have an amazing collection of biomedical entrepreneurial minds in SF and with the advent of bio-incubators and tech breakthroughs, the barriers to starting a bio start-up continue to drop.  There’s also a curiosity about biomedicine in the tech realm.  Who better to infuse biomedical and informatics start-ups with entrepreneurial energy and push biomedicine start-ups over the entrepreneurial hump than folks from this bastion of entrepreneurial energy? Plus, the biomedical start-up world doesn’t network nearly to the same degree as does the tech start-up world – that’s critical to the tech start-up world’s success in the SF Bay Area.  Thus Bio [plus] Tech – not just the same old biotech complete with high barriers, lack of networking and support.  Six months in to the Bio+Tech experiment I’d say that so far it’s been a success.

As a note: When I talk about biomedical entrepreneurship I mean that broadly – whether informatics, biotech, pharma, bio-energy, etc – it’s all welcomed and encouraged at Bio+Tech. And, I can’t emphasize enough that not only are we looking to bring together biomedical folks, we’re also looking to bring tech folks – developers, co-founders, start-up managers, etc – in to the mix.  You absolutely do not need a PhD in biophysics to join the group.  Just a healthy interest in bio or medicine – trust me, you’ll blend right in to the group!

Bio+Tech has grown from a group of 10 in January to an average of about 30 people at each monthly gathering.  To boot, that growth has been achieved solely through word of mouth.  I’ve been to a lot of meet-ups and gatherings where there’s lots of noise and very little signal – Bio+Tech has been purposefully kept small to keep the quality of the level of interaction high.  This set up was inspired, in part, by the SF meet-up Founder Dating, which requires an actual application and recommendations from other start-up folks.  Jess Alter and her crew do an amazing job!  Go check it out if you’re looking for a tech start-up or a techie person to help you build your start-up.  I also want to give a shout out to Vinnie Lauria and his Silicon Valley NewTech Meetup as the founding source of inspiration behind Bio+Tech.

Bio+Tech isn’t quite as complicated as Founder Dating and not as large as the SV NewTech Meetup, but to join the invite list you do need to demonstrate a basic interest in biomedical, tech or bio-energy entrepreneurship.  All too often a lot of biotech meet-ups are crowded with sales people and other vendors who are more interested in selling than sharing ideas, tips, contacts or starting businesses.  That’s not to say that we don’t accept sales people in to the group – you just need a genuine interest in creating a company or joining a start-up.

Michael Shuster speaks on the changing IP landscape and how that affects biomedical entrepreneurship.

Want to join us? Each month, the time and date of Bio+Tech will be posted on its webpage, with the location in SF to be announced. If you’re not already on the invite list, feel free to contact me at windmiller@gmail[dot]com and let me know why you’d like to attend.  Just a little paragraph with your interests and what type of company you’re looking to start or join, and a link to your LinkedIn profile – nothing too complicated.  In return, I promise to do my best to connect like-minded people at the meet-up.

We’ve had a couple bio start-ups find co-founders or developers – heck, there’s even been cross-pollination of neuroscience-principles back in to a tech start-up’s social media algorithms!  Yes, it’s a bit nerdy, but I can honestly say that out of the 6 gatherings so far, everyone who has attended has been someone I’ve really enjoyed talking with and sharing ideas.

Each Bio+Tech starts with a good bit of mixing and conversation.  It’s kept that way to maximize interaction and to warm things up.  We then get together to introduce each other to the group – with 30 people I’m always amazed at how efficiently we get through the group.  This is an opportunity to introduce yourself to the group and also spot others with like minded interests.  And, of course, we welcome solicitations for co-founders or technical help or any other start-up needs to the group.  This is a chance to network and find those you’d be interested in working with.

Starting in August we’re going to try to have monthly speakers as well.  It’s a highly informal 10-20 minute talk from people in the biomedical start-up or in the tech start-up world designed to bring ideas and prime the conversation.  We’ve had Michael Shuster, partner at Fenwick & West, speak on the changing landscape of Intellectual Property (IP) and how that’s affecting start-up strategy and execution.  A lot of biomedical start-ups are realizing that execution is just as important as securing IP to start-up success.  This isn’t news to tech start-ups, but this shift in perspective is somewhat groundbreaking in biomedicine start-ups.  We’ve got John Wilbanks, VP of science at Science Commons speaking at our August gathering on the open sourcing of biomedical data sets and tools and how that is altering and encouraging opportunities in the biomedical start-up scene.

And, Bio+Tech is purposefully kept free.  Whether you’re an undergrad or grad student, or on your 5^th start-up, everyone is welcome and encouraged to come.  I believe firmly that cost should not be a barrier to attendance.  And, please pass this along to people you think would be interested in Bio+Tech – that’s how we keep new, fresh ideas coming in to the group!

I haven’t posted on genomics in a while, so it’s about time. Two weekends ago I attended the Sage Bionetworks and Science Commons 1^st annual Sage Congress here in San Francisco. The main aim of the conference was to begin to gather science folks from across the country and begin thinking about making scientific research and data sets more open. While that may seem like an easy task in the era of open source, it’s tricky from many perspectives and the effort still has a lot of skeptics. But, more on that soon – personally, I think Science Commons and Sage Bionetworks are brilliant ideas.

At the conference Anne Wojcicki, co-founder and president of 23andme gave the keynote on the last day of the conference (video at right). To be fair, in the past I’ve been skeptical of 23andme – particularly from a clinical perspective. And, the MD side of me remains skeptical of genetic testing in general – at this point we know too little to apply genomic information to clinical care. There are a few exceptions, like breast cancer and a few other diagnostics, but otherwise in my humble medical opinion tests like 23andme should be used with a skeptical eye from a clinical and medical perspective. Again, there are a few case examples of where genetic testing has helped, but those remain too few and far between.

All that said, something about Anne’s keynote struck a chord with me – the amount of phenotypic data that the company is gathering in conjunction with their tests holds tremendous promise. Consumers purchase the test, and once their results are delivered, 23andme asks the consumer to participate in a series of surveys about their health and physical traits. To date, as was mentioned time and time again at the Sage Congress, research efforts to link patient, clinical and genomic data have proven to be arduous, time consuming and expensive. But, 23andme is capturing it right out of the box.

It’s hard to really convey how valuable this data truly is. A lot of the genomic data and research the scientific community has done to date has been on a couple cells in a petri dish or in mice, etc. Less has been done in humans, but that’s changing. With the collection of millions of genetic data points per consumer plus their trait/phenotypic data via 23andme, that will all begin to change much more rapidly. Being able to directly correlate genes to their traits will be a powerful tool for researchers to help push our genetic understanding and medical knowledge forward.

How we think about DNA and our genetic information as consumers is changing. Here, a DNA gel is aligned as art.

What makes 23andme special is that they’re utilizing social media and other consumer internet approaches to engage consumers and get them to provide their data essentially for free. While this might sound intuitive to most internet junkies, it hasn’t been for much of the scientific community. Indeed, from my perspective at the Sage Congress, 23andme’s approach seemed to me met with a bit of skepticism from the community – and this was an even more open and broad thinking group of people. But, it’s working. Consumers are readily contributing information, but it’s because of 23andme’s social media and internet approach. Not only will it change consumer genetics, but I bet that 23andme’s approach will alter how we collect research data, which will in turn, accelerate breakthroughs.

This shift in thinking will be critical as genetic research and genetic testing moves forward. Genes are far from being directly causal – i.e. very rarely does one gene lead to one distinct feature. And to uncover the patterns of the chaotic interaction of genes and their environment, gathering the type of rich data that 23andme does with their surveys will be absolutely critical as we move forward. Part of the next movement in genetic testing and genetic discovery will also require new tools to deal with massive data sets and help us find those needle-in-the-haystack discoveries that shed new light on human health and disease.

Again, more DNA as art - we're beginning to re-think our relationship to our genetic information.

And, to boot, one large win for society with companies like 23andme is that they are making consumers more and more comfortable with the concept of genomic testing. That in and of itself is a tremendous value to the market and for research. In the future I predict that we’ll look back on efforts like 23andme as landmark and critical to helping us reach the next plateau of genetic discovery and understanding. And, because of that and 23andme’s awareness of that fact, I think they’ll be successful in the long run.

Biology and technology have much to learn from each other - concepts from each discipline can inform and help create breakthroughs and new businesses. Image courtesy of Scientific American

I recently sat down with a friend who’s developed an ingenious way of using neuroscience concepts and neural networks as the basis for an information filtering algorithm. He’s taken that algorithm and created a personalized and customized news feed from Twitter.  In short, he’s helping to actually make sense of the Tweetstream.

So, what do I really mean by saying that he has employed neuroscience concepts as a foundation for his algorithm? First, think about the brain and how it processes incoming signals and stimuli – if it’s an important signal, say a pouncing mountain lion, it’ll get through all the other noise and register with you.  Much the same way, my friend’s technology uses a couple “filters” that determine whether the incoming tweet is relevant to your interests. If it’s relevant and important it’ll pop up in your news stream. In works much the way that neurons in the brain work – in order for a signal to pass along it’s gotta make the next neuron fire.  The same can be said about tweets this technology filters – if it’s relevant and important it makes it through the algorithm.

The second instance of neuroscience inspiration in this friend’s Twitter algorithm comes from the basic premise that how and what we forget is just as important as the things that we actually remember.  Think of it this way – if we remembered EVERYTHING that we see, hear, touch, smell and taste our brains would be overloaded and wouldn’t work efficiently.  We’d have trouble actually finding memories in our brains if we stored too much information.  The same goes for computer systems – learning how to forget, to get rid of irrelevant or increasingly irrelevant information is just as important as figuring out what to keep. However, the tricky part is figuring out what to forget and what’s worth remembering. That’s part of his trade secrets.

By merging his knowledge of computer science with a dabble of inspiration from neuroscience my friend has been able to pull together a really, really compelling product that might actually make Twitter useful for the 95% of the population that’s not on it. Where other techniques have failed to make sense of the Tweetstream, my friend’s inspiration from the fundamentals of neuroscience has greatly aided his product.

In the above example neurobiology has inspired and informed computer science design, but it’s also a clear case of how this interdisciplinary approach can help both fields make advances.  Another example would be 23&me. I clearly don’t think much of their business model or clinical relevance – but they did inspire some advances in bioinformatics through employing experienced techies to help build their data systems.

See, this is what you get when you mix biology with technology!

What I mean is that (as I’ve been told anecdotally) one of the things 23&me did absolutely right was hire a number of engineers from eBay who were fantastic at database engineering and management.  Instead of bringing in data folks with 10 years of background in bioinformatics and creating databases the way a biologist would, 23&me created an extremely efficient and scalable system for their genomic data.  This type of insight will enable science to make more advanced breakthroughs all that much quicker and effectively. It has also enabled 23&me to have a more feasible business model as well. Technology enabling and inspiring the advancement of biology.

All of this to say that in the world of entrepreneurship and design there’s a lot that the intermingling of bio and tech can bring to help inform and advance both fields.  I’m hoping that Bio+Tech can be one of those ways that technology and biology can intermingle to bring about not only a more vibrant start-up community here in San Francisco, but to help create breakthroughs and inspiration for the next generation of technologies. Drop me a line if you’d like to attend the meetup on February 17th!    windmiller[at]gmail

Biology and technology coming together isn't really a new concept - it's clearly been occurring for thousands of years. We just need to continue to encourage new interdisciplinary approaches as see what comes of it. A beer along the way doesn't hurt, either.

UPDATE: Please RSVP to: windmiller [at] gmail

This Wednesday night – January 20^th at 7pm I’ll be hosting what I hope will be the first of many meet-ups for entrepreneurially minded biotech and bioinformatics people here in San Francisco.  It’ll be at Crossroads Café in SOMA. In February the meetup will most likely be moved to a more permanent location at i/o Ventures, a start-up incubator space in the city.  Information will be updated on the meet-up’s page on Medicine Think and on my @medicinethink Twitter account (follow me!).  Feel free to pass this info on to interested friends.

Genome Valance by Ben Fry. Ben's expertise is helping to graphically represent and interpret massive data sets and information. This piece represents genomic analysis using BLAST. I picked this piece specifically because it takes a new look at how to represent and understand genomics and informatics - something I hope this meetup will help to encourage more of. More about his work from Ben at http://benfry.com/genomevalence/ (click to enlarge)

So, why the meetup?  I’ve spent the past 4 years in San Francisco in both the tech and biotech realms.  Actually, I’ve been a passively active member of the tech community – out of interest I go to events and meetups with friends.  I meet people through my wife who’s in tech PR.  I’m actually pretty well immersed in the community without really trying that hard – it’s a pretty open and warm community.

But as I’ve actively tried to network and attend events in the biotech and genomics space, it’s been much more difficult.  While I’m just about one or two degrees from most of the tech crowd here in SF, I can’t say the same about the biotech space.  And, perhaps with some good reason – the biotech/life science/genomics space rely pretty heavily on intellectual property and trade secrets, so that stunts people’s ability to be social.  Despite that, I think there’s much more room for building a more solid general community outside of the big players and established start-ups.

One of the beautiful things about the tech community in SF is the intermingling of different specialties and cross-pollination of ideas.  This leads to start-ups, improved technologies and a more healthy and vibrant tech community.  Often, these ideas, through start-ups, are passed up to the larger players through acquisitions – so from early start-ups to big behemoths the entire community benefits from this networking and open community.

The biotech community here could use more of this attitude and community.  San Francisco and the University of California has made a substantial investment in the Mission Bay neighborhood – there are very, very few areas in the country that have the foundation for success as does this very special part of SF.  And with visionary institutes like QB3, which is based at UCSF and Berkeley, I see a whole new generation of PhD and other grad students with an entrepreneurial energy that hasn’t been created at other campuses.  Combine that with Stanford’s legacy of doing the same thing and you’ve got the seeds for an amazing industry and community.

Don’t get me wrong, the Bay Area is already a leader in biotech – clearly there’s a lot going on.  But to take it to the next level, the community also has to kick it up a notch.  I hope this meet-up can serve as a partial catalyst (of course, there will need to be many, many more events, etc) to tap in to both the tech and biotech communities here and bring together a diverse and energetic crowd.  Ideally, I’d like to promote an interdisciplinary meetup – between not only biotech and bioinformatics people, but to bring in members of the tech community.  I think tech could greatly inform how bioinformatics and biotech does business – from improving how data is handled, to user interface and analytics and beyond – there is much room for tech to impact the biotech community.  And, to a certain extent, tech would also benefit from some of the thinking from leaders in biotech.  From algorithm and natural language specialties, to managing massive data sets and making meaning, to scalable software, SF and Silicon Valley is well positioned to inform biotech and informatics and help solidify the Bay Area as a leader in biotech and informatics.

If you’re in SF or the surrounding areas, please come by Wednesday at 7 to the Crossroads Café. Even if you are a tech person with a curiosity about biotech, genomics, personal medicine and the like, without a super deep background or expertise, we’d love to have you.  I think these two groups have much to learn from each other and that this type of social interaction will lead to new ideas, energy and companies that will help take the Bay Area to the next level and retain a leadership in the life sciences.

What do you think?  What would you like to see at these types of meetups?

Image of healthy tissue on the lower right (notice the orderly ring structure - in this case it's a healthy gland within the breast), while the large image is one of breast cancer. The image illustrates the chaotic nature of cancer - disorder where there was once order. Courtesy Vincent Cryns, MD at Northwestern

An interesting article appeared on NYTimes.com today that deals with “new” old approaches to the cancer thought and research paradigm. In essence, the article points to research that indicates cancer is more than just a group of genetic mutations – it’s also caused by the tiny interactions of proteins and other parts of the cell that are sometimes not genetically based.  Physical entities inside cells like proteins and other environmental aspects clearly play an important role in cancer, its prognosis and will eventually inform its treatments and cures.  At an even higher level that means that cancer is even more of a multifactorial disease – it’s far more complex than we ever thought.

The implications are that research will have to focus not only on genetics, but proteomics and cellular metabolism and physics.  An interdisciplinary approach.  However, one of the biggest problems here is that often each of these areas tend to be researched in silos – there’s not much overlap or intercommunications between research groups.  This has to change.

Thought about another way, often research can focus on specific areas for years while neglecting other important areas of research that are simply not as trendy (yes, even researchers can be petty at times).  For example, antibiotic research took a backseat to HIV/AIDS research starting in the mid 90′s, which extended up until a couple years ago.  The result is that we now have fewer new antibiotics to treat drug resistant bacteria.  We neglected one area in order to make advances in another – it’s a classic resource allotment problem as well.  Where do you place scare resources?  In this case, specifically, what research do you fund?

For cancer it’s my sincere hope that none of the individual disciplines are neglected – they all need to grow in unison and in turn inform and help each other to advance.  For example – one genetic mutation could in turn affect many different cellular processes on a metabolic level.  Understanding not only what the individual metabolic disturbances do, but how they link back to mutations and other cellular processes will be absolutely critical in understanding the disease.  These seemingly disparate areas of research will have to collaborate in order to make more breakthroughs.

Romanesco - a cross between broccoli and cauliflower. The result is a pattern that is a naturally occurring fractal - a pattern that repeats itself as you look closer and closer.

What makes it difficult now is the chaotic nature of all those cellular processes.  The cellular processes, while seeming complex today, may seem relatively simple once we gain the ‘right’ perspective, which may be many many years in the future.  It reminds me of fractals – chaos on top of chaos but from a certain perspective a pattern emerges.  And, as you go deeper you discover more and more previously unknown patterns.  If you look too closely you only see one aspect of the fractal.   If you look from too far away you might see the overall large pattern,  you’ll miss the intricacy of the smaller, repeating pattern.  An approach from both perspectives is necessary to understand the fractal.  I think the same can be said for not only cancer research, but all biological research in general.

An up close perspective of romanesco. Pretty amazing pattern if you ask me.

For biology the deeper perspective will be gained through not only new technologies but collaborations between disparate fields within biology (and potentially other sciences) that bring novel perspectives to these findings.  Tools like whole genome sequencing, biophysics modeling and the interplay between all of the fields will help transform how we view biology, which in turn will yield new insights.  Not only that, but if these currently disparate or silo’ed fields begin to collaborate my bet is that we will continue to not only make new discoveries, but continue to make them faster and faster.  And it’s not only the hard core, more quantifiable aspects of scientific research – qualitative field like clinical medicine and information from medical informatics systems will need to be included as well. But, as we know from the fractal example, the closer we look, the more we find, the more we have to discover.

Beautiful artful image of chaos - reminds me a bit of DNA. Courtesy David Nightingale @ Chromasia - http://www.chromasia.com

To get to this type of collaboration we’ll need not only advanced technologies, but collaboration tools and a willingness between researchers, corporations and other players to begin to cooperate and collaborate.  That might actually be the bigger challenge and require a whole blog post to itself (or many many posts!).  There are many perspectives in the fight against cancer and in the push to eliminate other diseases they should work harder to influence each other and promote novel ideas and create new discoveries.  I bet that approach would radically accelerate the pace of new discoveries and breakthroughs.

The bottom line for me is that I’m happy to see that these ‘old’ ideas in cancer research continue to stick around and that we have researchers and experts who continue to push the field along despite the nay-sayers.  I’m looking forward to more and more collaboration between disciplines and research groups.  And that’s no small feat.

Composite image of some of the iconic images from Apple's "Think Different" campaign.

How we frame and think about subjects clearly has an impact on how we approach and attempt to solve problems.  The first image, right or wrong, that comes to my mind is Apple’s “Think Different” campaign back in the mid 1990s. But I’m talking about the importance of perspective in a much bigger sense – we’ve defined and approached some of our biggest problems using techniques and perspectives that were modern 50 years ago.  Specifically, I’m thinking about how we diagnose, treat and research cancer.

Today we diagnose a patient’s cancer based on the tissue of origin (i.e. breast cancer, colon cancer, leukemia, etc), what it looks like to the naked eye and under the microscope, and where it has spread in the body.  The American Cancer Society has a great description of how cancer is “staged.”  Once our doctors have diagnosed the cancer, the treatment is based off of that diagnosis – most often it’s either chemotherapy, radiation, surgery or some combination of the three.  The treatment was based on how we diagnosed the cancer, which was defined on the technology we had available to better understand cancer.  But, for anyone who’s had experience with a loved one with cancer knows that the current therapies and techniques are certainly lacking – we need to do better. As a side note, the history of cancer chemotherapy is pretty fascinating and also reason for moving beyond current therapies.

The molecular structure of the origin of modern cancer chemotherapy - developed by German scientists for war in 1917 - but identified by American scientists as a treatment for cancer. It's time to advance our cancer therapies past this brutal approach.

Today we finally have better tools that enable us to better understand the core of cancer and will help us get to the root of the disease.  Genomics and informatics – the sciences of decoding DNA and then comparing different DNA sequences – are helping to transform not only how we research cancer, but in how we diagnose and ultimately treat cancer.  In theory this will lead to better outcomes for cancer patients.  If you understand the root of a disease – in the case of cancer, the genetic mutations and internal cellular processes that have gone haywire – you’ll better understand and better treat the disease.

For example, instead of diagnosing breast cancer based on exams, images and pathology slides, we’ll begin to take a sample of the tumor itself, analyze its genome and compare that to cancer genome to your healthy genome (taken from a healthy cell).  This is where the recent advances in genomics and informatics come in to play.  As we gain the ability to sequence vast amounts of DNA, we’ll greatly increase our knowledge of the genetic make up of cancers.

Specifically, genes today can tell us why the cancer has grown out of control, whether it will metastasize, and we now know it may even help predict where it will metastasize to.  But, that technology isn’t ready for clinical medicine just yet – much more research needs to be done to help us better understand the disease process.  In the future, though, instead of defining cancer by the staging system or its pathological features, we’ll diagnose a cancer based on its genetic profile.  In turn this will help us better understand the best course of treatment, the prognosis and how to prevent the disease from spreading.  My guess is that it will even help us be predictive of whether the cancer will metastasize, how fast and to where in the body.

This is a microscopic image of breast cancer (click to enlarge) - it looks pretty standard for a pathology slide, but it's also indicative of new research - the dark brown spots are cell nuclei that contain a marker that has helped to redefine how we treat breast cancer. Taken from the National Institutes of Health. Courtesy of Ronald S. Weinstein, M.D., University of Arizona.

By better understanding the genetic mechanics behind the cancer, we’ll be able to more accurately target our therapies and medications to the specific cancer.  This will drastically cut down on unnecessary side effects and ineffective therapies, and potentially lead to better and faster outcomes.  We’ll discover new therapies and drugs based upon what we discover through this genomic research. In other words, instead of using cytotoxic agents, like today’s modern chemotherapies, we’ll have drugs that are targeted to the specific genetic make-up of a cancer.  This will lead to many fewer side effects, and better patient outcomes.

Taken to the next step, we may even be able to better predict what type of cancers a person may develop based on their genetic make-up.   This knowledge will be essential in our fight against cancer.  We may even begin to better understand how to harness the power of our own immune system to target cancers.  At the foundation of all this knowledge will be genomics and our understandings of the basis of the disease.  If we have a better understanding of the genetic mechanics, then we can better define, diagnose and treat the disease.  All this advance comes from a shift in how we define and therefore understand the disease in its most basic elements.  Maybe it’ll lead to a cure, or maybe improvements in cancer therapy. It’s an exciting time in cancer research.

Neuron cells, with nuclei colored blue. Just a pretty picture.

It’s been a rough week so far – been stumbling out of my Thanksgiving food coma. So, it seems like the right time for a light, quick and fun post. Last week I came across a really interesting site from the genetics group at the University of Utah. It is a fantastic graphical comparison from a coffee bean on down to a carbon atom. Go play with it – it’s pretty fun!

Here's a good diagram of the cell and it's structures. The nucleus is the 'blue ball' (#2) in the picture. This is where DNA is stored - each cell in the body has a nucleus, and each nucleus has a copy of the human genome.

The site made me think about size relativity on a cellular scale with respect to the human genome. Within each of our cells is a structure called the nucleus. It’s the structure that contains all of our DNA – some people think of the nucleus as the “brains” of the cell, but I actually think of it more like a hard disk – the nucleus stores all of the cell’s important information. It stores our “code.”

So, here’s where the number fun starts. The nucleus of a human cell is on average 6μm (or 6×10^-6 meters) in diameter. VERY small – that’s not a whole lot of space to hold anything. Yet, at a bare minimum the complete human genome is about 20GB (that’s a fairly conservative number – some people estimate the genome at between 50 and 100GB of info). That means that the nucleus stores all of our DNA, in just 137μm³ of volume. That translates to just about 0.18GB in just 1μm³ of nucleus.

Here’s where we can make things a little more interesting. In comparison, if a modern hard drive were to have the same “data density” as a cell’s nucleus, one typical hard drive would be able to store almost 6.9 × 10¹³ GB of data. That’s the equivalent of all the data on the internet 140 times over. Put another way – if our hard drives had the same “data density” as a cell’s nucleus the typical hard drive would be able to store 140 internets. Thems a lot of tubes!

Those numbers are pretty hard to grasp, I’ll admit that. But, the bottom line is that each of the cells in your body contains at least 20GB worth of information! That’s crazy considering you’re comprised of almost 10 TRILLION cells. I feel like this is one of those “just how big is the universe” type questions, but it’s all completely within the human body.

Even though these numbers are really hard to grasp, it does illustrate to me that the body stores its genetic information in an incredibly efficient and amazing manner. That and our information technology has a long way to go before it matches the efficiency and capacity of the human body. Just a bit of a brain teaser and fun following a holiday weekend!

In PEHub yesterday an article about 23&Me and the financial issues it’s been having.  As an entrepreneur and having had plenty of great ideas poo-poo’ed by investors and industry folks alike, it’s really hard for me to understand why anyone would have invested in 23&Me as a company.  What I don’t understand is why highly skeptical VCs have invested in a business who’s central premise, while certainly desirable, is so far from reality at this point that it’s amazing anyone would invest. It’s certainly an important idea – scanning our individual genetic make-up to discern health risks and prevent them. Who wouldn’t want to understand what preventable diseases they’re prone to? I certainly would (well, to an extent – but that’s for another post).

For the uninitiated, 23&Me is a personalized genomics company that will take a couple drops of your saliva, extract your DNA and screen it for hundreds if not thousands of genetic disease markers.  The company name is derived from the 23 chromosomes humans contain – 23 from mom and 23 matching from dad. But the company over promises and under delivers.  At the end of the day, the fact is that biomedical science isn’t advanced enough yet for us to make meaningful predictions off of the information screened by 23&Me. And, to boot, there are other companies like Navigenics that have a little better model of screening, but they’re still pretty far off mark – as of yet. That said, Navigenics’ science and results are much better than 23&Me, but that’s like saying Peet’s is better than Starbucks – Peet’s may have better beans, but the coffee’s still not all that good.

A gene chip by the company Affymetrix. That little square on the chip can yield information on 500,000 different genetic variations.

Let’s dive right to the core of the issue – the biomedical science behind 23&Me. 23&Me (and Navigenics) use “gene chip” technology , which can screen thousands of genes at once and tell you where you have variation (mutations)  that are known to be correlated to disease.  In other words, if the gene chip picks up that you have a variation in a gene that has been correlated to a heart illness, 23&Me argues that you have a higher chance of developing heart disease. While that certainly seems logical – “I have a gene that shows a higher risk of heart disease, I better do something about it” – it remains somewhat misleading.

A closer look at that square on the gene chip - this is what the chip looks like under magnification when it's read by a computer. The different colors indicate different gene results.

We have to dive a little deeper here to understand why the findings from these tests don’t correlate to real disease risk. When researchers do genetic studies (the type of studies 23&Me base their tests on), most of the time they find correlations between gene variations and a disease. And I want to stress – these are correlations – and are not purely 100% causative like the genetic testing companies would like you to believe.  Put another way, these genes are found in these diseases, however they are not the root cause of the disease.  Most diseases are due to multiple genetic mutations, which means the underlying causes for these diseases are much more complicated than just one genetic mutation.

We now know of 20 genes that correlate to height, but they only explain 3% of variation in height between people. Only 3% of the difference in height between these two men! What about the other 97% of difference? More research!

For example, a study came out in the New England Journal of Medicine that detailed just how little we know about how our genes and how they become translated in to real world physical traits and disease. This review study illustrated that we know of 20 genes that correlate to the differences in height between people.  While that sounds impressive, turns out that those 20 variations explain only about 3% of the true variations in height. I’m 6’5″ – those 20 genes explain only about 1/3 of an inch of the variation in height between my 5’6″ wife and I! 20 genes!! Why then do we then think that 1 gene will detail risk for heart disease or cancer?  The bottom line is that before we can accurately correlate and make meaningful disease predictions based on genomics, much much more research needs to be done.

So, let’s come back up to the surface. I’ve detailed why genetic research to date isn’t as complete as these companies would have you believe. The personal genetic variations they uncover, while using the most advanced technology and knowledge we have, isn’t sufficient to fully explain disease risks. The companies are selling a service based on scientific misconceptions – people are accepting 23&Me’s marketing, rather than good science. And that lack of scientific and clinical substance is why the medical community hasn’t embraced these tests.

I’m going to get in trouble with these companies because they don’t directly make these claims – but I think it’s implied based on their marketing and how they discuss their product. Doing these tests even just for curiosity’s sake is even a waste of money – they don’t truly tell you anything useful.

As one caveat, Navigenics does have a much better platform than 23&Me and how they correlate gene changes to disease risk is much better than 23&Me. They do take a look at diseases more holistically – let’s say they’re screening for heart disease and for argument’s sake that they screen for 25 different genes correlated to heart disease. They take that information and integrate all the risk factors to give you a more accurate risk analysis based on population statistics. It’s a little better, but I wouldn’t spend the money for it yet.

Don’t get me wrong, these types of products and services are the future of medicine. Maybe not in this direct way, but we will be screening people for disease risk.  No, not for insurance reasons, but rather to attempt to prevent diseases before they take hold. It’s just too early for this type of genomic analysis to be accurate enough to truly act upon. Although I’d like to be an optimist, the technology isn’t there, medical practice hasn’t accepted these tests (and they shouldn’t) and the businesses like 23&Me are floundering as a result. All of this to say, as a consumer patient hold on to your money for now, the scientific community has a long way to go before we really have the information necessary to make strong clinical correlations and to make valid disease predictions.

One of the most harrowing experiences of medical school was during a surgery for a gynecologic oncology patient.  Prior to the operation we had absolutely no idea that this woman’s ovarian cancer had spread – we had only detected a spot on her left ovary.  However, during surgery we discovered that her cancer had metastasized to the lining of her abdomen (something that couldn’t be detected via MRI or CT scan).

Although experience told the surgeon this finding was evidence for a terminal diagnosis, we waited a couple days to inform the patient and her husband of 45 years because the surgeon wanted the pathology report to 100% confirm his suspicion.  After 3 days we finally informed the patient and her husband of the news.  There was really nothing we could do.  It was an absolutely heartbreaking experience.

From my personal perspective this experience, while a harsh reality of medical training, also made me want to learn more and to help save lives.  I spent time at Memorial Sloan Kettering when I could.  During my surgical rotations I usually opted for the cancer operations and office visits.  I’ve posted in the past about the US’s ongoing War on Cancer, but I think the thing that intrigues me about this disease is that there remains so much that we don’t know despite our vast experience with patients and disease.  I get this sense that there remains so much knowledge about the disease locked up in the cancer genome that with newly created DNA technology it’s finally time that we begin to unlock the mysteries of this disease. (Picture above is an electron microscope image of brain cancer cells invading healthy tissues.)

Electron microscope image of a breast cancer cell spreading "pseudopods" as it seeks out its next direction.

Indeed, this is one of the main reasons I’m so very excited about the prospect of genomic science – its crossover with cancer research and the promise that holds for better therapies and eventually a cure. Looking specifically at the genomics of cancer, a review article was published in the New England Journal of Medicine last year that summarized the details of what we currently know about cancer.  Just 20 years ago the Nobel Prize was given to two doctors from UCSF for the discovery of what we now call oncogenes.  Think about it this way – all of the cells in our body need signals that tell them when to grow and then signals telling them when to stop growing.  In cancer, the genes that typically tell the cell to grow a little bit faster are completely up-regulated (they cause too much growth) and the genes that typically put the brakes on growth stop working (effectively shutting off the brakes to growth ).  That disease dynamic makes a lot of sense since cancer is essentially the uncontrolled growth of cells.

But since that time much research has happened, and with it has come advances in cancer knowledge.  For instance, we have discovered that there are genes that actually tell cells when to die – to apoptose.  Think of that as the Control-Alt-Delete function of the body.  If something goes completely haywire, then a cell needs to be able to remove itself from the system.  However, if there’s something wrong with the apoptosis gene, then a cell is more likely to grow out of control and become cancer.

The same is true of genes that typically anchor cells to where they are – when haywire, these genes allow the cancer to detach – to metastasize.  Other genes convey an advantage to survive in other specific tissues, thus some cancers display similar traits – always metastasizing to similar, specific organs.  There are several other types of genes also thought to contribute to a cell becoming cancerous.  In a brief time period scientific and medical research went from a very limited knowledge base about  cancer to a very full and greater understanding of how this disease comes in to being.

One of the more interesting aspects is that cancer is now understood to be a disease with multiple genetic mutations.  Before, we would have looked for one or two “cancer genes.”  Today our reality is that cancer is much more complicated than the model of one gene-one cancer.  And this is a good thing.  We now understand that multiple genetic mutations are needed before a cell turns cancerous.  Growth needs to go out of control, the cell needs to split and grow like crazy, and it needs to travel from its home site. Not to mention it also has to elude the immune system!  Healthy individuals get cancerous cells every day – the difference between these people and cancer is an unfortunate set of mutations that leads to full blown cancer.

The cell at center is a cancer cell that is being attacked by the immune system (purplish cells). You can see one cell in the lower left being a "kamakazi" cell - sacrificing itself against the invading cancer. Understanding how the immune system helps to fight cancer will be a key understanding in the war on cancer.

Ultimately, what this understanding does is help us to discover that which we don’t know – we can better identify areas we didn’t know we needed to know.  As our genetic model for cancer becomes more complicated we’ll begin to better understand the disease and most importantly, make improvements in treatments and save lives. As I’ve said before, all of this research has shown us just how much we don’t know.  We need to take solace in the fact that the more complicated the true cancer genomics model becomes, the closer to savings lives we’ll be.  But there’s a lot of work and research until we make more major breakthroughs.  Fortunately for us, with the improvement in genetic and cellular research we’re closer than we’ve ever been in the past.

In two previous posts I highlighted some of the coming changes in DNA sequencing and some of the up and coming companies that will help us with the onslaught of data. But I’ve neglected to begin to explain why these technologies will be so transformative and why that matters for biomedicine.  Back in 2003 both the National Institutes of Health and Celera made a big splash as they announced that the human genome had been decoded.  While true – we had the basic sequence of the human genome – the A-T-G-Cs of it all, we didn’t really know what we were looking at.  Just because we have all 3 billion letters of the human genome sequence, doesn’t mean we know what it actually does. (Image above of a DNA strand courtesy Richards Center, Yale University)

Well, that’s only partially true – we do have lots of scientific research and understanding of certain genetic mechanisms and functions of genes.  But as of yet that knowledge has been somewhat limited and pretty elementary with respect to actual impact on clinical medicine and human health.  Very few diseases, like sickle cell anemia, can be traced back to only one mutation – a relatively simple genetic explanation (Picture at right: regular red blood cells with sickled disease red blood cells, courtesy NIDDK).  We know that multiple genes are linked to heart disease or cancer or arthritis and we’re discovering new links every day.  However, most of the the connections are still pretty weak and don’t fully explain the true genetic nature of some diseases.

And, one more thing, I’d be pretty skeptical of the commercial genetic tests that are available from companies like 23&me and Navigenics (among others).  While they have strong people behind the company, the data they’re using is still pretty weak with respect to predicting disease.  Take those tests as a novelty, not as a sure thing diagnosis – please feel free to write me and I’d be happy to explain more.

For another example, let’s take a look at cancer and its genetic root.  Scientists used to search for a single “cancer gene” – when we found one, we realized it was only a small fraction of the story and there were many other genes that had related effects that contributed to cancer.  The same thing applies to heart disease and even seemingly simple traits like eye color.  In a way, the more we learn, the more we discover we didn’t know as much as we thought we did.  It got more complicated.

To complicate the public’s understanding, the genetic model we all learn in school is Mendel and his peas.  It’s a good educational example because one gene leads to either smooth or wrinkled peas; another gene confers either green or yellow color – making the peas a really simple and useful example to explain basic genetics.  However, very, very few genes and phenotypes work this way in human genetics.

One reason the human genome, as we know it today, is not as quite as useful as all the hype in the media is that what we call the human genome project is really the genome of just two people.  It’s a roadmap of sorts to help with genetic research – it, by itself, explains very little in the way of human variation and disease (I’d like to say though, that much like the moon landing, there was a certain gravitas to actually completing the genome – it has inspired scientists and has certainly aided with scientific progress).  The genome map doesn’t have all of the gene variants figured out – it’s a raw map and it’s up to us to figure out where those genetic variants are.  More over, diseases like cancer and heart disease have many, many genetic components, making it even harder to figure out which gene has which function.  In other words, biomedical genomics is very different than the genomics lay people learn and understand.

To understand where cancer related and heart disease related genes are and what roles they play in disease, we’re going to need breakthrough technologies to not only sequence DNA, but also handle all the information that comes out of that process.  Each human genome, depending on how it’s sequenced, is between 250 gigabytes and 2 terabytes of information and costs between $100K-$500K.  That’s a lot of data and moolah, especially considering the hard drive in your computer is probably 250 gigabytes or smaller!  Each cell in your body contains more information than the disk drive in your computer.  Not too shabby of a machine, eh?  I digress.  As we progress, new models of sequencing and data solutions will become much more economically feasible, making it possible to do the necessary research.

An example of how genomics will change medicine was published last year in a New England Journal of Medicine article.  In it researchers describe how they obtained two complete genetic sequences from a person – one of a leukemia cell and the other of a healthy skin cell.  Essentially the researchers compared the cancer genome with the healthy genome and analyzed the genetic differences. When they compared the cancer genome to the healthy genome they found 3 mutations that they expected to find based off of prior leukemia research.  However, they also found 7 genes that they had no idea were involved in leukemia – the researchers arguably tripled the genetic understanding of leukemia with just this one study.  Now, with these new gene targets, researchers and doctors will have a better understanding of leukemia as a disease, which will shed insight in to next generation therapies and maybe even a cure someday.

Now, that study cost approximately $500,000 for the genomes alone – $250,000 for each genome.  With new sequencing technologies we’ll be able to get that cost down to under $100 in a matter of a couple of years. The leukemia study mentioned above was just a proof of concept that illustrated our ability to better understand disease genetics and pathophysiology  by comparing only two different genomes. To get a full and accurate understanding, these same scientists will need thousands of genomes to compare – and that’s just for each, individual disease!

Over time this genomic research will become common place and will yield great advances in biomedicine.  At this point we need more cost effective technology that will make it affordable to perform the necessary research with enough genomes to really matter.  To close this post, though, I strongly caution that this work may not directly lead to a cure.  My bet is that the research will help us to better understand that which we don’t know we don’t know.  It is a leap in to the right direction and will prove incredibly helpful.  It’s an exciting time.  In future articles I’ll dive deeper in to the genetic mechanisms of cancer and then other, new breakthroughs in genomic technologies.