Funding research in the new (poorer) world

The world has changed. Money is tight, the large foundations and governmental granting agencies are risk averse........which means senior scientist will get the $. 

This means that innovation is going to die. Once you get to be a senior scientist you don't have time to fail you have to feed the beast. I think the best allegory is Wall St.- Yes "to big to fail, I need a bail-out Wall St." is exactly what most large labs in the world are!

Rather than launch on some Quixotic diatribe about how bad this is for health and science as endeavor,  Ill just talk about how to make it irrelevant.

The answer is small foundations. They have the focus, passion and community to start a real long term relationship with young scientists. Brand new, too ignorant to know better scientists who got their own lab by being the most innovative and best prepared post-doc is exactly the one who will take the chance-if their is money involved. 

All foundations seem to be focusing on drug discovery and biomarkers. This is a great space for smaller disease focused foundations to occupy. The problem is that most of the organizations do not have the gobs of money to follow it through in a comprehensive manner.

Getting effective novel therapeutics requires engagement of talented, creative scientists. 

For disease focused research foundations this can be difficult. In the current economic environment foundations must have some method to "hook" scientists whether it be large per year grants, limited restrictions on spending or speed of review. 

For rare diseases this means getting in their early phase when they shape and limit the vision of their lab. Rare diseases research requires passion and a way to find general funding that will maintain the lab. 

In this day and age when peer based mentoring is sadly lacking a foundation that can provide some guidance on where/how their researchers can leverage funding and expertise can gain loyalty and expand by word of mouth. This will then lead to larger "sexy" studies and fund-raising. 

This kind of thinking can work hand in hand with maximizing fund raising as you can tell fund raisers that a large portion of their money goes directly to attempting to cure or ease their disease rather than greater good. 

Overall:Small foundations should look to maximize the effect of their funds to effect change in their specific disease. 
Through targeting 2 areas of research:
1 Cellular characterization of the disease (ie what are properties that are different between normal & disease)
2 Drug/therapeutic design and testing-no matter how speculative. This assumes that the idea or test system can pass peer review 


The 2 areas would have separate competitions, 2 separate funding paradigms:

1 Short funding cycle-a micro-finance model. Short grants with quick turn around. 2 year grant with  a hard progress report with mutually agreed upon measurable progress. 

2 A prestige grant larger "no questions asked" funding 5 year funding with no reporting for 2 years. Again mutually agreed upon defined goals that MUST be met to receive final 3 yrs of $    


The grants would be open academia and small biotech. There would also be a bonus for academic lead Pharma-academic RFPs. There would be a significant and clear partnership NOT just "in-kind" contributions. 


The research and fund-raising would have a high degree of back and forth. The foundation would hold a stakeholders conference where selected funded scientist would come and explain the state of research in layman's terms. 


There has to be greater out-reach from the scientists at foundations. The Office of the CSO should engage in various forms of social media to engage and find funds (with the guidance of the Exec board). This can no longer be left to that summer intern who just finished Bio 101. The public is too smart for that and frankly if I was looking for a small foundation for funding I want to know that the scientists are engaged. It should be an expectation not just a hope that scientific merit is judged by scientists. 

Time for some convergent evolution in knowledge management

As I move from the ivory tower of Neuroscience to the practical, business related advice that Info-Tech gives clients on their IT environment I'm amazed at how many parallels I see in the needs and the solutions in all kinds of human endeavours.

For example, I just finished talking to a vendor about how Enterprises can manage and maximize their content (images, documents, blogs, etc). Much like my own thinking on this, @OpenText is convinced the core issue is about information movement not what it is stored in (i.e. a word doc VS a excel).

For me this comes back to a practical problem that I had as a graduate student. My Ph.D was on how gene expression relates to brain development. The brain develops in a fascinating manner; it starts out as a tube that grows outwards at specific points to build the multi-lobed broccoli-esque structure that allows all vertebrates but particularly mammals to have diverse behaviours and life long learning.These complex behaviours rely on an the immensely diverse set of brain cell types. Not only is their great diversity of cells but each cell needs to get to the right place at the right time.

Think of a commute on the subway; not only do you need the right line but if you don't get to the station at the right time you won't get to work on time. This could lead to you getting fired. For brain cells this could lead to death. For the organism it could mean sub-normal brain function-and potentially death. The fact that the process works is a testament to the astounding flexibility and exception management built into cells by their epigenetic programming.

There is however one big problem with the type of brain development: the skull. The skull limits the number of cells that can be created at any given time. Practically this means that the level of control that must be exerted on the number of any one cell type is very tight.The control comes from coordinating which genes are expressed in each cell type to allow cells to make decisions on the fly. Usually it starts by the brain cells take off in a random direction that then informs them of what type of brain cell they will end of being when they arrive. The cells then proliferate as they move based on the contextual information that they receive about how many more cells are needed. This all happens through cell to cell communication and rapidly changing patterns of gene expression.

(Wait for it Ill get back the parallel problems honest....)

As you can imagine this was (and still is) a daunting problem to investigate. My research involved a variety of time staged images; reams of excel workbooks on cell counts, brain size; word docs on behaviour and whole genome expression sets. It was the a big data problem before the phrase existed. (Business parallel No.1). In reality I had no problem keeping track of all this data and looking at each piece and doing the analysis on each piece. I had very good notes(metadata) and file naming conventions (classification) to ensure that I could easy find the file I needed. I was in effect a content management system (Business parallel No.2).  The problem was synthesizing the separate analysis into a cogent piece of information i.e. something that can be shared with others in a common language that allows other to build their own actionable plan. (Business parallel No.3).

Any scientist reading my dilemma from 15 years ago can probably relate-and so can anyone else that uses and presents information as part of their job. The reality is that technology can only solve the problem if people recognize the problem and WANT to be systematic in their habits.......the will power to be repetitive in their approach to work is sorely lacking from most knowledge based workers. Ironically a lack of structure kills creativity by allowing the mind too much space to move within. The advent of the online databases by NIH from genomic, chemical and ontological data has given a framework for scientists to work within to quickly get up to speed in new areas of investigation. Unfortunately this has not trickled down to individual labs (again more proof that trickle down anything doesn't work effectively-its just not part of human nature).

This lack of shared framework across multiple laboratories is becoming a real problem for both Pharma and academia (and everyone else). The lack of system has led to reams of lost data and the nuggets of insight that could provide real solutions to clinical problems (Business parallel No. 4). This also leads to duplication of effort and missed opportunities for revenue(grant) generation.(Business parallel No.5).

From a health perspective, if we knew more about what "failed drugs" targeted, what gene patterns they changed and what cell types they had been tested on we could very quickly build a database. From a Rare disease perspective the cost of medical treatment is partially due to the lack of shared knowledge. How many failed drugs could be of use on rare diseases? We will never know.

This is a situation where scientists can learn from the business community for the technical tools to really allow long term shareable frameworks. These technical controls are available at any price. Conversely the frameworks and logic that scientists use to classify pieces of content to link them have lessons for any knowledge worker.

Its time for some open-mindedness on both sides, the needs for all kinds of organizations and workers are converging-too much data, too many types of data, not enough analysis. Evolution is about taking those "things" that work and modify them for the new environment.

Health IT and clinical research

I recently returned from the E-Health Canada conference in Vancouver. I was there as an analyst for Info-Tech research group. I spoke about secure use of consumer devices in healthcare and the potential of cloud computing as a flexible model to deal with CoIT.


I was pleasantly surprised by the IT knowledge level of the nurses and doctors that attended the conference. Why was I surprised in this age of consumer devices and self service tech? Well I spend a fair amount of my time talking to and about IT departments. The impression that I get from many of them is that while most people can set up their email on their phone they remain largely clueless about the actual tech itself.  


Well, there is certainly a core of nurses and doctors that understand the tech and have really great ideas for how to make it work better in the context of healthcare delivery. I was left with the feeling that many remain frustrated with the current solutions and the pace that E-health is moving forward. The major areas of frustration were around content delivery and system upgrade for usability. I would summarize it as “You must do something; protect the data but be flexible on the device used”. Technology should allow doctors to spend more time looking and talking to patients not with their nose buried in a tablet. Just placing a tablet in the doctors’ hands doesn’t mean it will lead to increased use of the IT solutions for healthcare.


While some may point to this as a technology problem, it was clear from talking to the vendors that the solutions available today can meet the demands that hospitals are placing on IT. As someone with a past on the research and has dabbled in clinical research it was refreshing to know that there is a variety of solutions out there to make clinical research easier. What was interesting was how similar healthIT problems are to many other industries. In my opinion the issue is now about getting the best out of the tech not when will the tech exist.


 In other words its about getting the users and the admins on the same page. 


As someone with a deep passion about Rare diseases and use of high level biomedical research its somewhat frustrating that the system that is in use today is so antiquated. The upgrades available today could add so much intelligence to how we treat Rare diseases in particular. 


The new areas of stem cell therapy and epigenetics hold a HUGE promise if we can understand the relationship between disease and biology in these patients. Since they are so rare at any given location it is imperative that we have a way to share the data that is safe enough to share patient history across borders.

Rare diseases and open access.

Ive found myself completely mesmerized by the open access/open science debate. As a recovering bench scientist, it has made me think about a variety of things but one that is really interesting is the implications for Rare disease research and speed of turning great benchwork into viable drug targets. Ill deal with the larger debate on open access separately but I wanted to put forward something today(Feb 28th 2015 Rare disease day). 

2016 update: In my opinion not much has change in Rare diseases in the last year. There have been some moves forward but like anything in the drug and/or therapeutic research- it is time consuming. I hope that the silence is because we are getting to the point where folks have rolled up there sleeves and are working not talking. 

I am really excited about the prospects for increasing the speed that potential drug targets can go from bench to bedside. The new technologies (gene sequencing, clinical data) can provide faster turn around time through efficient data sharing and new genomics technology. The real potential pay off is through new clinical data that will be available once EMR is implemented widely. The value of that much data combined with the new genome sequencing technologies can really provide some much needed guidance about the genotype phenotype relationships that may link certain rare diseases. I say may since it will really come down to data quality and wide dissemination of that data. Getting clinical data into the hands of molecular biologists and biochemist who can do the bench research is vital to drug design. 

2014 Update: With the roll-out of ACA starting to happen and the FDA crackdown on 23andMe. The landscape for studying and curing Rare Diseases just got a little better. For more information on the 23andMe nonsense there is plenty of information on the imbroglio but this one from the Huffington Post is the least sensationalist. My opinion is that the FDA made a decision based on the specific businesses lack of response it is not an indictment of consumer genetics or any paternalistic over-reach. Mathew Herper has a really great analysis of the stupidity and or hubris that 23andMe showed.  The Global Genes Project has a nice blog on the relationship between Rare diseases and ACA. 

The bad news is that the sequester has set research back years if not decades and may have very well rob a whole generation of scientists of their careers (this author included). Tom Ulrich of Boston Children Hospital has a nice blog on the subject.

\
2015 Update: The new interesting initiative is precision medicine in US. I really am proud of the way Global Genes Project is coming along. I was briefly involved when Nicole Boice started the initiative. I look forward seeing how it continues to grow in 2015. I think it does a great job of keeping the conversation on awareness and providing a site to aggregate "best practices" for the Rare disease community. 

I really hope that the continued access to healthcare that we started to see in 2014 continues. The key will be what do we do with the basic information that clinics gather about their rare diseases patients? How do we make that shareable across clinics. This in my opinion will be the key to consistent diagnosis and clear symptons, which will then better inform scientists of which genes contribute to the phenotype. This is the basis of drug discovery and treatments. 

Right now is a real nexus of information due to the convergence of new technologies with "new" fields of studies. Epigenetics is the study of how and why genes get turned, the best analogy is: if the whole genome is the book of life, genes are the words and epigenetics is the sentence, paragraph and chapter structure that gives the words meaning. The other area is off-shoot of stem cell research; induced pluripotent stem cells (iPSCs). iPSCs as the name implies are induced to become stem cells from a variety of other cell types, the most clinically relevant being skin and blood. While the debate rages iPSCs and their value for replacing non-working cells with new ones [regenerative medicine] one thing that is not in doubt is the power of these cells for modeling disease. iPSCs can be made from patient samples and then shared with other researchers. This may seem trivial but the more people looking at the same model the quicker the core problem can be found. If done right the sharing of the iPSCs to researchers who use different techniques (biochemists, molecular biologists, cancer, etc) will provide a 360 degree view of the disease. 

Update 2014: Unfortunately it seems that iPSC research is becoming marred with scandal. The new "most promising" discovering may be "less real" than one would hope.....Paul Knoepler has a blog on the subject. BTW if you have any interest in stem cells you should follow Knoepler's blog he is an excellent writer and a top notch scientist.

Update 2015: I think we are past the really bad period, unfortunately it has also diminished the enthusiasm for iPSCS as models. Although I am not surprised, it has recently been shown that iPSCs form different sub-types of cells based on their tissue of origin (see here for neural and here for heart). This seriously limits the usefulness of iPSCs for drug discovery and would just exacerbate the reproducibility issues that are plaguing science in general but particularly stem cell research. 

Once this happens it's likely that links will be found that can make drug discovery and testing palatable for biotech and big pharma. Drug discovery is expensive but if the community can gather enough information about the molecular and biochemical characteristics of rare diseases then the existing "orphan drugs" can be tested against the characteristics rather than any single disease. 

Update 2015: The orphan drug area is one where we are starting to see movement. The recent announcement by the CF foundation recieving $3.3B for the patent rights to Kalydeco. It is an interesting approach that should be considered by any rare diseases group looking to expand support and the potential therapies for their disease. 

As always the caution is who should get the money, how do you ensure that the cost of the drug to sufferers is appropriate? If the foundation funds the study (in part) do they have an obligation to ensure that the cost of teh therapy be reasonable to the average person?

The elephant in the room is of course paying for all of this. Scientists need to be able to publish to get grants to pay for post docs and reagents. While there is some money available from disease foundations but it doesn't cover all the costs that a lab needs to run. That is the job of the NIH. However their mandate really requires that grants are given out based on WIDE applicability of the research and the grantee's history of research in that area. Unfortunately this model does not serve the rare community very well nor does it foster the wide range of scientific endeavor. There hundreds of examples where a rare disease has lead to unique insight into a biological pathway that was key to some cancer or other disease. 

Update 2014: Rare disease research will survive but we need to start to fast track new funding models that focus on highly innovative projects. We know what hasn't worked we need some research that is different.

Update 2015: Unfortunately I can't say there has been too much movement on this. Frankly scientific funding is horrible right now. I think for rare disease foundations there is an opportunity to foster young scientists to be advocates and invested in their disease but this requires a new way of thinking about how to fund rather then WHAT to fund.