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!

Looking forward to seeing you on August 18^th.

Been busy working on some consulting engagements recently.  That’s a good thing for me, but bad thing for Medicine Think.  I’m working on a new entry for later this week, but for now I’d like to share one of my favorite graphics from Bud Caddell over at What Consumes Me created this awhile ago and I’ve been meaning to share.

Sometimes, as a one-man consulting business you feel a pressure crunch that most big firms don’t face.  It almost feels like what an artist or graphic artist must feel.  Most folks want things for free, they have some sort of expectation and only few ever plan on compensation.  The trouble is that I find most of the consulting problems that come my way to be really, really interesting.  I’m happy to report that I’m bringing Square6 closer to the middle!

And, for those of you who love infographics – head over to What Consumes Me! Fantastic work!

The Tesla Roadster Sport - really, there's nothing like it

Here’s a non-traditional Medicine Think entry, but I wanted to share my first drive of an all-electric car – the Tesla Roadster Sport.

I feel like last night I had one of those rare experiences where you feel like you’ve seen the future.  It might sound like a hyperbole, but that’s what it felt like to test drive the Tesla Roadster Sport.  And, no, I’m not in the market for one, but after driving it, I really wish I had about $110,000 in disposable cash laying around.

So, what is it about the Tesla that makes it feel so futuristic?  It’s an all-electric car – there’s no hybrid or gas component – it’s a 100% electric motor.  That means that from the moment you put your foot on the “gas” (is it more appropriate to call it an accelerator pedal? The “electric?” The “juice?”) it’s a different driving experience than you’ve ever had.  The only similarity is that there are four tires, the car looks like a Lotus Elise, and there’s a steering wheel – most other experiences are different.

There’s no engine noise.  Honestly, you don’t miss it.  An electric motor, by nature, has 100% of torque at 0 RPM – that means the thing accelerates so rapidly that it’s hard to believe.  0-60 in 3.6 seconds – that’s Lamborghini fast.  Instead of having to “rev” the car up, all the power is there and ready to go when you push down on the pedal.  It’s unlike any car I’ve ever been in.

There are no gears – nothing to shift, no transmission beyond forward and reverse.  After the car bolts to speed, the engine itself has a tremendous amount of braking power.  The moment you let up from the accelerator, the car begins to drag to a stop.  You literally don’t need a brake other than to come to a full stop at stop lights.  Put another way, to maintain speed, you have to keep the pedal down – even on downward slopes where gas power cars would shift to neutral or have a very low factor of engine braking.

Apparently, a lot of Tesla’s patents and intellectual property in how the car electronically mimics the way we drive today in gas cars.   By that, I mean it’s not in the nature of an electric car to cruise forward when you let up on the brake.  But the Tesla does – that’s a purposeful design and apparently very hard to do in an electric car.  From my understanding, this technical achievement will be difficult for others to mimic.  Apparently this technology bleeds over in to how the car accelerates smoothly and the car reaches cruising speed.  Whatever they’re doing it’s definitely working.

With the electric engine comes the need to store the electricity to power the car.  The battery “pack” alone weighs just shy of 1000 pounds.  That’s a lot of weight.  It’s positioned mid-car just like in a gas powered sports car, which helps balance the handling overall.  Regardless, the 1000 pounds is a lot of weight, especially when the car weighs a mere 2,700 pounds overall.

Otherwise, the car is definitely a stiff little roadster and to be honest I had a hard time seeing through the windshield.  I’d love for the car to have a few more inches, and I hope that comes at a later date.  Maybe by the time I can afford one.

It was truly an exhilarating ride, and I don’t think it really hit me until I stood up and I felt like I had just stepped out of a rollercoaster – the same shakes and legs feeling almost like rubber.  I don’t know if that was because I’m a pretty novice sports car driver, or the all-electric roadster really is that cool.  My gut sense is that the car really is that cool.  I was on a high for the entire rest of the night – I’m not kidding.

And, this sense had nothing to do with the environmentally friendly nature of the car.  That said, I’d be really curious of the overall carbon footprint of a mile in a Tesla versus an efficient gas car.  How many carbon emissions are released during the production of the electricity to power the car?  Is it really less than driving a mile in a gas car?  Either way, the electric car really is that cool.

Heading back tomorrow to get a behind the scenes look at the dealership and shop in Seattle.  More to come!

Combining medicine and technology hasn't always been smooth for people like diabetics

I’ve been thinking a lot recently about people’s [in]ability to integrate and think about a lot of different data points, particularly over time.  Specifically, I was thinking about consumer healthcare solutions that have been popping up.  I was advising a couple friends last night on an idea that they had in the consumer wireless space to help people manage a specific health condition – let’s say blood sugar for type 2 diabetics.  Seems like a noble goal, right?

I thought so too 3 years ago when I tried to create my first start-up, Element Mobile.  With our first product, CurrentCare, we were aiming to help diabetics easily, quickly and seamlessly track their blood sugar and other related statistics.  We were aiming for both type 1 and type 2 diabetics.  However, the interesting thing in the marketplace is that there’s about 1.5million type 1 diabetics (those who require insulin to live) and about 22.1million type 2 diabetics (tend to be more obese and insulin resistant) in the United States.  We were aiming for both populations with CurrentCare.

But, here’s the rub.  Type 1 diabetes patients tend to get used to a routine and learn how their body reacts to insulin and over time they lose the impetus to continuously and religiously track their blood glucose levels.  And, for the most part they do pretty well and live relatively healthy lives.  Type 2 diabetics tend to be individuals who haven’t taken as good care of themselves – if most were to lose weight and track their blood sugar levels (among many other lifestyle changes) they could probably get their disease under control and maybe even become totally healthy once again.

And, by “healthy again” I also mean that if they get back to healthy, they could avoid complications like heart attacks, toe and foot amputation, kidney failure (which requires dialysis), blindness, etc. Caring for complications of diabetes alone cost the US healthcare system about $116,000,000,000 a year – yes, $116 BILLION – and another $58 billion in associated costs.  That’s enough to scare the bejeezus out of me, but most type 2 diabetics don’t manage to control their blood sugar or attempt to lose the weight they need to avoid these ills.  Why?

One of the problems is that these complications occur many, many years after the initial onset of diabetes.  It takes 10-20 years of neglect (sometimes sooner) to run in to these issues.  It’s hard for type 2 diabetes patients to really be scared of something that’s 10, 15 or 20 years down the road, particularly if they don’t feel that bad today.  As a side note, type 2’s do report feeling worlds better if they kick the disease through diet and exercise, so there would be some immediate, near-term benefits to becoming healthy.

The same applies to people with high blood pressure, poor eating habits, or who are overweight, etc.  Most of these people feel “fine” today – they’re getting along just fine and don’t feel the need to change.  The punchline, however, is that 10-20 years down the road when the deleterious effects of a lifetime of neglect kick in, it’s almost surely too late to recover to 100% health.  This leads to the inherent problem with consumer healthcare and “health 2.0.”

If people aren’t inspired or driven to take care of their condition because they can’t see the deleterious effects that loom 15 years down the road, why would people be inspired to care for their conditions with new internet and wireless tools?  Even if these techniques and tools lower the barrier to adoption and make tracking super simple, for a vast majority of people it’s simply not worth it to care for or improve their condition.  It’s one thing to create an elegant solution and another to gain adoption among this population of people. Creating these solutions faces the problem of getting multiple types of users on board – providers, patients and payers.

All too often we only really care about our health when something is staring us in the face – like an illness or a cancer diagnosis or heart attack.  Or even something as joyous as pregnancy. And even then we go online, look up a few web pages, maybe do a bit more of investigative research and we’re satisfied.  Because of this, the opportunities to monetize these interactions and create a sustainable business is somewhat limited.

There’s an inherent human behavioral trait that’s just so hard to manage in a way that causes people to change.  However, the person or company that can solve this problem – to create a health tracking solution that gains steady user adoption and traction – will almost certainly win the start-up prize. But, until then, I think there are (unfortunately) going to be a lot of dead startups in the middle of the road. I think the answer lies more in consumer behavior rather than creating effective clinical solutions.

How are things going to ultimately change? Is it scaring people out of their wits to change? Is it substantially lowering the barriers to adoption? Is it some other intuitive device or solution? Or something completely different like incentive or disincentive programs that get people to change? What do you think?

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?

In the past I wrote about getting a start-up off the ground. More precisely, about how to take an idea and give it legs and maybe get it running – how to mold an idea and begin to improve it. I call this socializing the idea (with the next steps being socializing the company/concept). But, how do you take it to the next level? Making that transition between idea to fully operating start-up is tough, particularly if you’ve not done it in the past (read: if you haven’t been a successful entrepreneur in the past).

A good friend, who has successfully sold two pretty large start-ups, gave me the advice that angel (or seed) investors tend to only invest under three conditions: 1) you’ve been successful in the past, 2) they know you personally (worked with you, are a family member, want to get in good with your family, etc), or 3) are intimately tied and invested in the space you’re working in. While I took in his advice, I’m not sure we followed it well in my first start-up. None of us in the venture had successfully launched a start-up, we didn’t come from money and most investors didn’t like to invest in the healthcare space (at least at the time). Turns out my friend was more right than I could have guessed. This made it incredibly hard to pitch to angels, and ultimately we didn’t get funding (but that’s another story).

One other thing about starting that I’ve learned over the past 4 years is that often times it has taken companies a lot more effort than they showed or they had some sort of secret weapon to getting started. Almost no one company starts go smoothly or easily. One company in particular that comes to mind was lauded as having been an amazing story and elevated its founder to a great reputation. They raised a little under a million dollars and sold for $25M. That’s a great story. Then you peel back the layers back and realize that one of the co-founder’s father invested a majority of that initial $1M (they didn’t raise it from a typical angel investor) and that father was also an executive at the company that eventually acquired the start-up. Don’t get me wrong, this start up still took a tremendous amount of work to get the product to grow and to accumulate users. But, as a note to up and coming entrepreneurs, stories like this one, including the message that was told to the public and meetups regarding the ease they had fundraising are often misleading. It’s still a success story, but definitely not as shiny as it initially seemed.

But where does that leave first time entrepreneurs without a track record or the good fortune of befriending a Silicon Valley maven or a PhD in computer science? A couple new efforts have really filled that niche for talented, but new entrepreneurs. The most well known and a pioneer of these efforts is Y-Combinator – a Silicon Valley and Boston based effort that hold biannual “try-outs” for new start-ups. Essentially, you make an appointment for the try-out session, pitch to Y-Combinators’ board and if they like you they’ll give you some minimal seed funding ($10k) and help set you up with the resources you need. More importantly, being accepted as a Y-Combinator company pulls you in to their social circle which works wonders in being connected to partners, customers, getting advice or going for a larger funding round. Perhaps most important in this effort than having a great idea is who you know and who you have access to – funding from Y-Combinator can help you gain that toe-hold and help you jump in to the game. They also have great partners, including Paul Graham who has a widely read start-up blog. In other words, it’s less about the amount of funding and much much more about the connections being one of their companies brings you.

Now, utilizing efforts like Y-Combinator doesn’t come without a price – namely that it’s reported that they take 10% of equity in a company. That’s definitely very, very expensive. However, at the same time it’s indispensable if you are new to the start-up game, particularly in the Bay Area. Other, less well known efforts are also taking root, including Adeo Ressi’s The Founder Institute. Their model is a little different – they take a smaller chunk of the company if it gets funded and then splits the profits from this equity pool amongst other founders. It’s too much to really explain here, but suffice it to say that the Founder Institute is more about gaining connections than anything else.

A third option is a location in San Francisco named Dogpatch Labs. Run by Polaris Ventures, Dogpatch Labs gives entrepreneurs very inexpensive, shared workspace with other start-ups. It’s more about community and connecting with your fellow entrepreneurs, but it’s also a great networking tool. In this case, entrepreneurs and young companies need to pony up some cash for the space, but in a place like San Francisco, a resource like Dogpatch Labs is invaluable to the start-up community.

Last and certainly not least is i/o Ventures. Just announced today (January 6, 2010), i/o Ventures looks to be both a small seed round along with a new, open workspace in SF. It’s got an impressive list of advisors and other folks surrounding it, including the likes of Michael Arrington. Pretty amazing exposure and a mashup of some of the concepts from other incubators/labs. Sounds like they’ll be shelling out more money for a smaller percentage of the company as well (compared to Y-Combinator’s $10k and 10% take). Watch out for these guys in the future.

Overall, these efforts give an amazing amount of camaraderie, work space, inspiration and most importantly legitimacy in the eyes of potential users, customers, and funders. It’s a fantastic way to start if you’re new to the game. I’m sure there are other spaces like these, including Hacker Dojo in Mountain View, CA – more of a meeting of the minds and place for work inspiration and perspiration. Did I miss something? Who else should be included in this list? Leave a comment about them below!

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.