How could you study epigenetics? Thought experiment from a dreamer

This blog is part autobiography part roadmap. 

I am often asked “Do you miss it-being a scientist”

The short answer is “I didn’t dream of being an IT consultant.”

Longer answer is, as with all things that are part of being an adult, more complicated.

• I miss discovery- the joy designing a method to answer a question and then actually knowing- for a brief moment in time- something that no one else knows.
• I miss immersing myself in a problem and building a solution.
• I don’t miss, university politics; having to know who’s ass to kiss and watching my back for potential theft of ideas.
• I don’t miss the bullshit publication process that sometimes is used for competitive reasons.
• I don’t miss trying to write a grant that appears to be both novel and safe at the same time.
• I don’t miss the bureaucracy of universities policies that protect senior faculty but burden junior faculty.

I have been “out of the game” for half a decade now but I still pay attention to science and design experiments in my head and sometimes write them down.

I was an Assistant Professor running a small lab for about 4 years, my lab was centered on a set of enzymes that control the expression of genes in response to cell signals and environmental stimuli. These enzymes are commonly known as epigenetic regulators. The work we did was pretty good given the lack of funding, the fact that the enzymes had been described literally a year before I started my lab and I was trying to combine a novel class of genes with a novel set of methods (I was part of one of the groups that published the early papers describing the histone demethylase enzymes).[Synopsis of my lab]

My real interest, however has always been in learning the answer to the fundamental question “How do you make a brain?”  

I think now, I would ask a slightly different question; which has “how do we fix the brain when it isn’t made right.” One thing that age and distance has given me is perspective or perhaps empathy I don’t honestly know the difference. I have two small children both of whom are pretty awesome- unfortunately both have inherited some of my flaws. So I am often struck by how does the brain manifest these “flaws” even if there are no major changes or developmental issues.

How would one go after such questions?

Five years ago the answer was Stem Cells with maybe some mouse genetics thrown in for good measure. Now? I would go another direction. I think the single biggest issue in epigenetic research as well as neuroscience is the lack correlation data between phenotype (what it looks like in the whole organism), genotype (what genes play a role) and biochemical output (how well does the “engine” function”). Much like astrophysics and quantum physics have mathematic models which provide probability maps for specific core particles and/or forces, Epigenetics needs probability maps for phenotype and genotype- a Heisenberg probability if you will.

As I have mentioned in other posts, epigenetics is essentially grammar for the genome. It is a big, unwieldy mess of a field that is likely at least three separate full fields that we do not have names for as of yet. Sticking with the analogy the “field” of epigenetics is at the point where Western civilization was in the late 1700s/early 1800s where we knew some words and potentially some word relationships in the Egyptian cuneiform but we were largely blind to what was actually being said in hieroglyphs until the Rosetta stone was found. To me the rosetta stone for epigenetics will be cross species mapping of real world consequences.

For example; we know that there is a link between obesity in dogs and their owners. That is a real world cross species phenotype- why don’t we look at what genes expression and epigenetic patterns are changed as both lose weight? There is still validity to the idea mammalian biology is conserved at the physiological level.

What I would do if I was starting now would be to focus on dogs as a main model; they live with us, they often eat like us, they have behaviours which at their core are similar enough to ours but distinct across breeds. Furthermore access to their health records would have less risk and potentially greater detail as most veterinarians have a depth of knowledge on their patients over a whole lifetime – and for some clients multiple dog lifetimes.

For me, I would focus on brain cancer- as a scientist it is a fascinating process to take a cell that is programmed to not multiply and make it multiply and it is a cancer type that has repercussions to ones body, dignity and family.

The lab would have five facets;

1.     Define a set of neurologic symptoms that could be tested for by a veterinarian in clinic.

a.     Use standard indications from observation.

b.     A set of typical blood markers that are used for “unhealthy’ as part of the analysis.

c.     X-rays to define rough location, size and prognosis

2.     Test brain tumour samples across gene expression, “Epigenetic profile”, potentially genome mutations

3.     Use samples to grow models tumours, testing their gene expression profile and epigenetics profile for changes in culture.

a.     Where possible have normal age specific controls across breeds (or at least a general “mutt” control)

4.     Longitudinal studies of dogs with tumors after various therapies.

5.     Map epigenetic changes in tumour versus normal as well as fresh tumour versus in culture.

I was “classically” trained as a mouse geneticist where we had the clean clear; I deleted a gene what happened to my cell type? I learned [the very hard way-  hello consulting ;{ ] that there are no one-to-one relationships in any cell type when we deal with epigenetics- it is the system that protects the cell from single points of failure.

Long term would be to identify a set of parameters that can be linked to cancer and then go back and start testing the enzymes that are directly linked to the epigenetic modifications that are related to the phenotype. 

Why do we care, as a society, about diversity?

NOTE: This is a re-post from 2014 - in todays environment I fear it will get worse but I hope I am wrong.

It is a tough question.......the fact of the matter is that SOCIETY does not care. Society as a organism, is completely apathetic to diversity. Jamelle Bouie of Slate has a great write up of an MTV research survey on Millennials (see here). Basically they believe we have already conquered racial inequality.

I categorically submit that we have not. That is not an opinion, it is what the employee demographics that Google and LinkedIn have recently made public suggest; we do not care about gender equality or racial equality.

There are a lot of areas of society where this matters but I’ll focus on areas that I have some understanding.

A lack of economic drivers.

Fostering and managing a racially diverse workforce is a difficult problem. From a company’s perspective they need talent that can help today. There is no real pressure on these companies to change their practices. There are some common refrains that we hear:

• As long as company X makes money for my portfolio, I don't care.
• I want to know that I am receiving the best care, I don't see color.
• We just choose the best candidate, we do not even look a pictures.

These are the refrain of the masses, and by masses I mean the majority of business, medical, and academic leaders. As with everything it is about context and the path through history that brought us to this moment. While I hesitate to paint a whole demographic with a paint brush, I think we need to discuss these kinds of issues if we have a goal of changing the current trends. So who are ‘THE MASSES”?

Based on most reports the average C-level executive are white males between the ages of 45 and 65.

The events of the past guide our actions

So why doesn't a generation of white men that grew up in the midst of; the African-American civil rights movement, Gandhi's pleas for basic dignity, and "Bra burning" seem to get it?

It might be because they think:

• The battle was fought and won, that we are post-racial, post feminism
• We have already sacrificed enough, if "those people" can't compete now it is because they lack the skill
• There are more important things to worry about than the diversity of my company, talk to me when the economy is better

Now before anyone gets offended and feels they have to justify their equality chops by commenting-I get it, this is a gross generalization of a large cohort. My response is; no evil continues without the inaction of good people. Sorry but my life and career have been adversely affected by the color of my skin. You cannot reasonably expect black folks-or women- to turn the other cheek when they have real world experience with being past over for a better candidate like the CFO's cousin's brother-in-law, twice removed.

So why should Google, Apple, Harvard, or any of our top institutions care about diversity?

..........I don't know. There is very little data that can be used to support the hypothesis that diversity is good for academic or corporate goals.

Laserfiche'sSimplicity blog lays out the potential reasons and some ideas to move forward better than I can. I will leave it to you to read about the reasons that we, as a society, should care.

Does it really matter once minorities are hired?

I want to take a more personal sidetrip; even when males from racial minorities or women are successful (whatever that means) there is a cost-Not only to the minority or female worker but to the organization.

As a black male, I can tell you that just knowing that these demographics exist-and have historically existed- changes my behavior towards colleagues and potential employers. I can’t properly explain what it is like to spend your career as a white elephant, to stick out in such a way that you feel you need to justify why you are there, that you are talented enough and hardworking enough to be there. It makes you less likely to ask for help, less likely to give help when you feel that you have to be better than your colleagues just to retain your place in the food chain. It colors every interaction, brings doubt to any constructive criticism, in short it stunts your growth and your ability to contribute to the companies growth.

It doesn't end at work, it also has an effect on the personal side. The feeling of having the future, of not just you, but anyone who looks like you rest on your ability to succeed is a weight that changes you-not really for the best.

I cannot explain to anyone who hasn't been through it what is like to have people shirk from your handshake-even though they know you are a professor at a university or they are paying you to be in there presence.

I cannot explain the pain and emotions that are surfaced just by meeting black folks in their 70s and 80s and the pride and hope written big on their face just from hearing that you have a Ph.D.

I personally do not want any more generations to go through that, to feel the dual weight of a multiple generation’s hopes and dreams, and the weight of knowing that you will never know if you got a fair shot.

Racial Bias exists, it is part of human nature

We can be better, the first step to reducing our personal bias is to acknowledge that we all have them. We make assumptions based on visual information. The beauty of the human mind is we can consciously fight against this visual bias. It is not easy but hopefully "we" as a society will start to hold our leading institution and businesses to a higher standard now that we have evidence that we have let these companies off easy when it comes to diversity.

Whatever happend to cancer and bad luck? The story of known unknowns

Back in 2015, Bert Vogelstein et al, wrote a really interesting theorectical paper regarding essentially "What we don't know about cancer." 

We sort of already knew what caused bad luck but we can't really articulate what it is.

 (The "Bad Luck" article itself is behind the paywall but this editorial is a really good primer on what was ACTUALLY said by the authors)

I believe, like many in my field (when I still had one) that bad luck is simply physiology that we do not understand (Yes a direct rip off of Arthur C Clarke)

Vogelstien et al caused a media explosion to start off 2015 with the bad luck line- Forbes, Huffington Post have run with it.

A year later we haven’t heard much about the stochastic models (a fancy word for random) While hesitate to wade back into this morass of jargon, layman interpretation and poor analogies- I will. I think it is important to recognize that the authors were in no way suggesting we (society) should just stop trying to prevent cancer or that individuals have no way to decrease their risk.

I also think it is important to note that this was not about media attention. Bert Vogelstein is one of the fathers of cancer research- He doesn't need media attention to get funding. The point the scientists are trying to make is that some types of tissues make more copies and that is why certain tissues have higher rate of cancer. They also acknowledge that there are areas where we have limited research and therefore may be the source of "bad luck."

One of the biological control mechanisms that is part of the randomness of cancer is an area of study call Epigenetics. This new area of study controls mutations, rate of cell divisions, amongst other "things", in a cell specific manner.

What is Epigenetics?

In a practical sense epigenetics is an in-depth look at how genes regulate each other. Genes are, at their strictest definition, the precursors to the proteins (or certain RNAs) that perform (most of) the jobs that make life possible. While genes are the stars of the show, in terms of regulation of biological processes, they are the least interesting part of the genome. The interesting part is the so-called junk DNA or more accurately non-coding DNA-as in it does not code for a protein. If genes are the stars, then non-coding DNA are the role players and the scenery that move the show forward.

The dance of how these proteins and their modifications is choregraphed is WHAT epigenetics does for the cell.

Non-coding DNA essentially act as the context for why a gene should expressed; for example certain cell specific genes will be epigenetically regulated so as to NOT be expressed in the wrong tissue. This occurs through a series biochemical and physical changes to a gene that as a group are as a group considered epigenetic regulators.

Epigenetic processes are the key to providing organisms the flexibility to respond to the environment. So what about these processes make them so important? As with any regulatory process-it depends.

The best analogy is the "genome as the book of life". If genes are the words by which an organism is "made" then epigenetics is everything else in the book. (see here for a presentation on this topic)

[I prefer the script and scenery analogy above but the book analogy fits better with the general "Book of Life" analogy for DNA]

 At the lowest level it is the sentence structure that allows the words to have meaning. At the highest level it is the chapter order that gives the story a linear order. Unlike a real book each tissue in the body can shuffle each of these elements on the fly....a choose your own adventure book based on cell type.

Keeping with this analogy the various tools that each cell uses to keep track of their progress though the choose your own adventure would be the epigenetic machinery. This machinery provides, the grammar, syntax and paragraph structure that allows the cell to respond to each potentially different path.

As anyone who has every read a choose your own adventure, part of the fun is tracing back and making a different decision. In a cell this ability to track back is vital as it allows certain cell types to re-populate after injury or during normal growth. To bring it back to cancer, the flexibility that is inherent in a choose your own adventure book leaves cells vulnerable to errors.

Imagine that each cell has their own copy of the “Book” and everytime they divide they have to make a copy of the book for their kids. The only problem is that they have to do it by had one letter at a time. Obviously, there are going to be errors but for the most part they do not change the word or change sentence meaning. On occasion though the errors do change sentence structure or alter a word. In a nutshell this is any disease; an alteration of the “Book.” Cancer is in someways a step further, just like there are verbs, nouns, adjectives, etc in language there are categories of genes. When the growth category of words are altered you get cancer or when you alter the grammar (epigenetics) that provides rules for “cancer words” then you get cancer.

What we still don’t understand is how many words need to be altered or how much can you bastardize the grammar of the genome before you get cancer. That is part of why cancer appears to be bad luck, we simply do not understand the language or the grammar rules sufficiently to judge the quality of words that we find in cells.

To put in plainer; we don’t understand genetics or epigenetics well enough yet to make predictions.

The deeper dive:

While the book analogy is interesting and useful, the beauty of the system in my opinion is that all of this is managed through biochemistry: small differences in enzyme kinetics and subtle changes in protein binding. This biochemistry leads to a wide variety of markers that can be used to denote parts of the genome.

The cell uses different types of biochemical markers for each of the particular categories; grammar, pages, chapters. Each of the different markers has a different eased of use – sort of like an e-book where how you can jump as a reader is very dependent on how the author thought you would move through the book. The ease of use is a function of the biochemical processes by which the cell adds or remove the markers. If this all seems like overkill just to express a gene...it sort of is.

All of the added layers and differing ease of use allows the cell to add very tight regulatory control. This allows the cell to mix and match different markers to make bookmarks or highlight favorite passages, often used paragraph, etc. In general the chapter markers are direct methylation of the DNA. As the name suggests it is the addition (or subtraction) of methyl groups to DNA. This alters the affinity of DNA to a subset of proteins that occlude the DNA-basically hiding the genes. Removing the methyl groups abolishes this occlusion.

Sentence structure this is more complicated but in general there are 2 types of post translation modifications that are most commonly seen as having a definitive role in this process. This usually involves the structural proteins that surround DNA. These proteins are the histones and they allow 2 linear metres of DNA to be packed a volume of 0.00001 metres. An amazing feat in and of itself! Histones can be modified in a wide variety of ways too numerous to mention here. (see here for a review)

Full disclosure; my laboratory studied the role of histones in epigenetics so I am biased when in comes to how interesting these proteins are in the scheme of life

The combinatorial placement of these proteins and modifications on DNA allows for a very precise grammar to be used. So precise that cells can communicate exactly which protein should be expressed to their neighbor. Given that there may be as many as 31 thousand that is quite impressive. What are histones? that is another story for another post. The bottom line here is that these proteins control access to the DNA- as well as generally protecting cells from misusing cancer genes and/or accidently erasing instructions.

As always I love feedback and this is one of my works in progress.

What to do now that the election is over and there is a new President

“A perfect democracy, a ‘warm body’ democracy in which every adult may vote and all votes count equally, has no internal feedback for self-correction. It depends solely on the wisdom and self-restraint of citizens… which is opposed by the folly and lack of self-restraint of other citizens.”

Time Enough For Love, Lazarus Long. (R. Heinlein)

The rest is ridiculously long and political: the TL;DR version- its not over whether you believe you are on the winning side or losing side.

[FULL DISCLOSURE: I am a US citizen but I live in Canada- so I have some distance (and protection) from the consequences of the election]

Some thoughts on the election and what democracy means in the age of social media:

If you voted for Trump because the political establishment has consistently let you down- your job isn’t over. 

The establishment is still firmly entrenched in the Senate and the House. If you truly believe that politics as usual is so unacceptable as to elect an outsider like Trump then you need to hold the establishment senators and congressman accountable through engaging with them, ensuring they know that they must change their behaviour and actually work for the disenfranchised not just big money donors. Otherwise, frankly you are a hypocrite whom has been led like a sheep.

If you voted for Clinton because you wanted change- your job isn’t done as long as you breath, you should fight for change.

 Pragmatism can be an effective weapon for change. The GOP was not given a blank check and constituents in states that went to Trump need to hold the government accountable as and ensure that anything that is passed is for everyone not just the minority of the same folks as before if there is no oversight you can bet that it will only be to the benefit of lobbyists.

If you voted against Clinton because your sick of corruption and a political system that is weighted to insiders- your job isn’t over. 

The system is corrupt, politicians routinely put their own interests above those of their constituents especially those they deem as “not their kind.” Hold “your” representatives responsible for what is best for your whole neighborhood not just your race or political party or your economic class.

If you voted against Trump because of the disgusting, sometimes racist, sometimes misogynist things that he has said- job isn’t over. 

Don’t fall into the same language and lack of self-awareness that you voted against. If you truly believe that morals and civility are important- embody that belief. Take the hard road of thinking before speaking, of attempting to understand that words have the power to hurt those that already lack power. Teach your kids that there is a wide chasm between respectful straightforward discourse and “political correctness.”

If you voted for a third-party candidate because the idea of choosing between an entrenched establishment candidate and the “alt-right” business tycoon was so distasteful you had to protest- your job isn’t done. 

If you want a real third party choice, you can’t just vote every four years. There must candidates that can articulate why a reasonable number of people who currently identify as either Democrats or Republicans what is “in it for them.”

If you didn’t vote because of apathy or sloth- congrats you get to shut the fuck up for the next four years. You are part of the problem. Get off your ass, educate your self on the issues that are important to you and vote accordingly based on your conscience.

If you didn’t vote because you are disenfranchised or have had your rights put beyond your means- don’t give in to depression.

Make your case, provide evidence but don’t let them label you as an animal or sub-human but respectful and dignified even in the face of disrespect and hate. Allies can be won by evidence and promoting shared values not by anger and insults.

Basically, if you think simply voting and then bitching about it on Facebook or Twitter has fulfilled your civic duty and you can go back to not caring, your wrong. If it wasn’t clear before the election that “We the people” need to ensure that politicians work together to govern the whole country rather than simply do what polls best with their party – it should be now.

The political establishment won at every phase of this election because no one held them accountable. Neither party has very good ideas for a better future but maybe- if both sides governed and compromised good things can happen. It is how America became great politicians knew that if they went back to their districts without having done something other than block bills and vote on the same one or two political issues over and over again they would get turfed.

Governing cannot be seen as a war to be won. Wars can only be won if you kill more of the opposition than you lose. That is not what makes democracy happen, it is the continual balancing of the rights of the majority with the protection of the minority- it is the idea that individual opportunity should not be tied to economic, racial or geographic hurdles. Right now to everyone except the super-rich and the politically connected the US doesn’t feel like a real democracy or the land of opportunity.

Communicating science when we don't really understand it

(or how the heck do we explain what we actually know about epigenetics)

I was recently part of a Tweetchat [#EPNtalks](see here for @EpigenomicsNet storify of the chat)

I threw something out there that I have been thinking about for about five years.

Where is Genetics/Genomics/Epigenetics 's Stephen Hawking- or probably more accurately for today's kids our Neil Tyson DeGrasse?

N.B. While I love the Emperor of All Maladies, that is not the direction I envision with all due respect to Dr.Mukherjee.

I find it really frustrating that with all the great communicators that I know are in the field, we do not have a book that is targeted to the general public.

It is a frustration that I think has stunted the field, allowed a bunch of illogical mumbo-jumbo to replace clear concise analogy. 

In my mind there are a lot of reasons that we have gotten here...some of them are acceptable like the fundamental changes in funding levels that have been seen world-wide in the last decade or so. There are also some that I find completely unacceptable.

Here is a short list of unacceptable reason why "our" ability to communicate genetics/epigenetics sucks:

1. We (scientists) don't actually understand much beyond their little patch of grass. I think we force a ridiculous level of specialization on trainees and students.
2. We don't have well thought out experiments. In the last five or so years we have gone with this notion that you can collect data and find clear real, unbiased answers without a hypothesis.
3. We  don't train Ph.D students to analyze (strongly related to #2). It is common fort MolBio, Genetics or Biochem graduate students to NOT take a statistics course prior to starting their Ph.D. 
4. We have fallen in love with jargon. Getting through a Science or Nature paper nowadays is a horrendous effort in acronyms and 5 syllable words. 
5. We have left public relations to the universities as we are too busy - doing science- to explain.  

I have put some thought into this and I have outline a potential book or probably better as a video series. I have attached it below. As always if you have any comments please add them below or email me directly at crwynder AT gmail  DOT com

My script/book idea for a book focused on how the machinery of Epigenetics relates to the real world examples of diversity and development.

It is not the EMR that sucks it is your lack of a information governance strategy

Hospitals are drowning is technological deficits; aging equipment, poor information security, unusable electronic health records and importantly no way to effective share patient records with patients or partners. A recent study shows that two out of three hospitals are not meeting HITECH standards for Health Information Exchanges. The authors note that even though there are fines (see here for HITECH fines), it is unlikely that these will spur adoption of health information exchanges (HIE).

Bernie Monegain (Editor Healthcare IT News) does a great job summarizing the article. From a software vendor perspective this seems like a perfect storm; a gap in capabilities, upcoming deadlines and a change in revenue models. In any other industry there would be lines of vendors at every hospital's CFO's door trumpeting their ability to help them meet their deadlines. Unfortunately the usual suspect vendors in HealthIT have not seized the opportunity (see here).

As I have mention before this is where ECM, WEM, etc vendors should be stepping in to fill the gap.Hospitals of all sizes will need to be able to confidently exchange patient information and make it available to patients once Meaningful use 2 standards for patient accessibility come into affect. Providibng a mechanism to share patient information in a standardized, secure manner is not a nice to have item, it is a required item to meet obligations-it should be on every hospital CIO, CFO and CEO's radar.

It also speaks to the larger problem of what electronic health records are strategically versus the narrow software characterization. Healthcare providers and thought leaders need to acknowledge the software sucks, and is not the best place to share and view information. It is just a dumb database designed to HOUSE patient information in a safe manner- as the name suggests a EHR is part of a records management strategy.

Electronic Patient information has the potential to increase the efficiency and cost effectiveness of healthcare delivery. The problem is the variety of solutions deployed by individual healthcare practices makes integration at the regional and national level difficult. As a rule they have been bought as point solutions to a immediate problem rather than as part of a healthcare information governance strategy.

It is time to look past a single solution that has a single set of technical specifications and build a system that manages data access.

As with any application rationalization process, it is important to define the costs, benefits and integration needs for any new enterprise application. Make no mistake; Health IT can no longer be a single application portfolio, they have to move to an ecosystem approach based on both clinical and administrative needs.

The failure of the single point solution of EHR/EMR has cause many IT professionals to take a negative view of information technology itself. As I have mentioned before, the problem is not the storage of the information it is how to access the information- it is a content management issue-be it ECM, WCM or -gasp-(SharePoint). EHR.EMR systems are horrible at providing access. For meaningful use 3 compliance and for your external marketing you need some kind of content serving system.

For organizations in a position to move to the newest EHR/EMR products, there may be no reason to have an additional system.For everyone who doesn't see a rip and replace in their next five years, consider how all the devices and partnerships that you have (and will have to grow to stay in compliance with Meaningful use).

You have a variety of regulatory items to think about as you develop your information governance strategy:

HIPAA 5010 covers Electronic data exchange(EDI[X12]) compliance standards as mandated for 1/1/2012: It covers exchange of all data transmitted by FTP, HTTPs, etc. Also encompasses the letter and number codes used for identifying file types during transactions. 5010 is largely an attempt to standardize the file codes in a way that increases security through in-flight encryption with de-crypt at each end. This is only possible if there is a standard metadata set.

ICD-10 is completely different it is the International Classification of Diseases (Rev. 10). This is used mainly for e-billing purposes as part of the diagnostic reference. It is not the official standard in the US until 10/1/2013, HIPAA 5010 EDI standards is a prerequisite for use of ICD-10.

Device access Smartphones and tablet computers represent the next wave of technological innovation in healthcare not to mention medical devices and consumer health apps (see here for more thoughts).

Mobile is a key aspect of your long term success. Hospitals have a variety of high earning "part-time" and ad hoc employees with their own businesses to run. You need a way to integrate their independent process and access into your secure information systems.

As with any access decision the type of information that can be accesses has to be balanced against the need for audit and security. The key is to remember the needs of end-users:
Doctors need access to all data, so restricting parts of the records is not an option.
Nurses need to update records on the fly.

IoT devices- There has been a lot of new devices for use in healthcare- patient owned health apps, mobile phones and wireless medical devices (see here for more on this). One of the key short comings of today's EMR/EHR products is their lack of abilities on the user experience front. Hospitals need to move away from single point solution planning for applications to a information management strategy that includes integration of outside data- whether it comes from patients, partner clinics or device vendors.

IT managers need to take the initiative and do these three things:

1. Ensure that the process involves care providers and administration in the same room. These meetings cannot be for show. All decision makers must be involved. 
2. Get to know who the key decision-making doctors are in each department and develop a relationship. Some doctors are in favor of EHR find out who these are in your hospital/clinic and involve them in building a strategy for how to attack the implementation. 
3. Get care providers on-board during the demonstration phase. Take your key decision makers through the products ask questions about the mundane parts of the software (first impressions of the GUI, how to access the records) not just the big picture items.

Supporting clinical research; a conversation with LifeQ

The age of biometric data is upon us, but the science is not ready to explain what the data means. In some ways it is really exciting, the potential is huge- even if we ignore the marketing materials and focus on the potential long term use of simple data collected under real world conditions. Stephanie Lee from buzzfeed had a sobering analysis of Apple's new Researchkit that the healthcare and clinical research value of the data is pretty much zero. I completely agree with (see my thoughts on Apple's foray into healthcare here). The only group that might see some value is the same group that has access to healthcare and quality jobs (see here for primary data from Pew Institute). This means that the biometric data pulled from "iEcosystem" will not reflect the population that acutely needs to be understood biometrically. (I'll provide a detailed example of the issues later in this blog.)

In my opinion; any data that is tied to a specific mobile device or "Internet of Things" (IoT) object is useless for healthcare unless it can be compared and combined on aggregate across devices and demographics.

It reminds of the mid-nineties when genomic sequencing was going to revolutionize healthcare and disease treatment. Twenty years later and we are finally realizing that the genome is an almost irrelevant piece. That the context of how that genome is read, acted upon by the cell, and communicated between cells is more important then any point mutations or small scale genomic changes. (I have written about thishere, in the context of cancer.)

The genomic age was necessary to spark the discoveries that are starting to change healthcare but the changes in healthcare won't be realized because of genomic biology. It seems to me that we are at the same crossroad with the Internet of Things (IoT). The technology is really cool and the visualizations are solid but......what do I do with it?

For example, I have a Fitbit it has literally change my activity due purely to trying to get to 10,000 steps......I think thats a good thing- I mean I lost weight, my back is better.....but I am left wanting more, what types of activity are related to my weight loss? Have I gone far enough-am I at lower risk for all of the things that I worry about from a health perspective?

I can tell you the data collected by my Fitbit is pretty useless to answer these questions. I downloaded it all ran it through a few different statistical models and guess what? None of it appears to be relevant to my on-going good health. I still use my Fitbit to track my activity but I have no illusions about the role that the collected data plays in my healthcare decisions.

I recently had a chance to talk to a really interesting start-up company called LifeQ. LifeQ (@LifeQinc) has restored some of my enthusiasm for IoT and real impactful changes in healthcare. LifeQ has taken a different approach to the internet of things. LifeQ owns intellectual property on for an optical sensor that uses light waves to penetrate the surface of the skin to monitor multiple biological measurables; heart rate, blood pressure, oxygen saturation, with other important measurables such as glucose in the beta testing phase. The real power of LifeQ is not the measurables. Most of the metrics that their sensor measures are relativelty common place. Many devices can measure heart rate, blood pressure, glucose, these are not unique. The true value of LifeQ as a IoT vendor is really in the predicative models and software that allows identification of changes in ones own biology. As Christopher Rimmer pointed out this very similar to the model that Google, Microsoft and Apple have pioneeered. LifeQ owns the core data acquisition ("OS") and the core platform for integrating and using the information ("search engine"). If LifeQ can be half as disruptive in healthcare as Google has been in mobile, they can be a driving force for systemic cost reductions and better treatment outcomes.

The device agnostic approach gives LifeQ a wide potential market in healthcare, fitness as well as the flexibility to weather the inevitable changes to the device ecosystem that end users are willing to use. The focus on data acquisition and analysis reduces the overhead and ensures that the width and breadth of data needed for accurate modeling can be gathered.

As LifeQ told me during our conversation "You can't build a great, high quality algorithm and data access AND build multi-functional devices at the level required to collect the data we need. There are plenty of companies in the health, medical and consumer device world with the pockets and desire to build high quality readers."

It is a really smart strategy, especially in the complex global healthcare and lifestyle market(s). Focusing on their strength and being choosy about the partnerships. This strategy allows LifeQ to ensure data quality and more importantly from a medical perspective, information security. High quality data that is combinable across devices is necessary to keep the predicative models relevant, and increase in accuracy with successive iterations.

Obviously the key risks are in how to ensure the partners continue to innovate on the physical devices and the integration of different device collected data into a single model. To keep with the Google analogy how do you build the back end to protect against the fragmentation of the device type when each device manufacturer has specific needs and market segments. The kind of companies that they are dealing with understand the necessity of spending on the hardware.

Not surprisingly the initial partnerships are consumer focused, within the personal potential niche, for example those that cater to extreme athletes. Some wider consumer focused. An interesting aspect will be how LifeQ can integrate the niche data into the predicative model without biasing against normal peoples fluctuations. For example, we know that part of what makes elite atheletes, well elite, is speed of recovery; their heartbeat decreases at rest faster, their rate of breathing decreases faster, muscles recover faster. So as LifeQ collects this data, what value does this data have for us "normals" will the models be accurate?
It is not an insurmountable challenge but the awareness of how the data can influence the model and vice versa is a concern for any IoT or Quantified Self technology. It is the early adopter problem, your initial feedback from fanboys and people who share your vision can blind to the general publics use cases and expectations. It is the exact problem that caused Google to shutdown Glass.LifeQ seems quite aware of the potential founder effect problems.

A more important (to me at least) is that they are also engaging the medical community to enable the kinds of use cases that have long term quality of life and better diagnostic test values for health monitoring. These kinds of markets are a growth market and can provide a reliable revenue stream. For example, at home monitoring or ambulatory care for basic monitoring of HR, breathing, Oxygen levels, blood glucose (coming soon). All of which can be monitored today by the LifeQ powered devices. The problem being that the current monitors that have the accuracy that LifeQ needs are cumbersome but they are easier to where than what most hospitals have- and can be worn for long periods of without patients being strapped to wires or stuck in bed. The potential for clearer test results under real conditions is tantalizing.

What is next?
Like all start-ups LifeQ is focusing on ensuring their product is the best by ensuring that every element that could negatively affect its core product. The really interesting piece will come from the meta-analysis once the number of users hits a large enough N to ensure predictability across populations.

LifeQ acknowledged the potential limitations of a optical sensor; skin color, lean muscle to fat ratios, as well as stability issues cause be user activity. They are working expanding the repetoire of sensors that LifeQ can collect data from as part of the platform.

The real issue that faces LifeQ and any of the more robust quantified self devices and analysis platforms really comes down to action steps. For that matter the same issue exists for personal genomics. What is the line between variation of the population and dangerous biometric signature? Is there more harm then good from telling folks everything?

LifeQ has a great platform, and appears to have all the pieces in place to be the "Google for healthcare." They certainly bear keeping an eye to see what they do next