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.

Open access and generating senior scientist buy-in

There is a vibrant, intelligent but completely impractical debate happening right now around publishing scientific papers just use #openaccess to see the volume of twitter posts. The concepts are great-faster dissemination of information, cleaner peer review process, greater collaboration. 

My issue is the lack of reality check or way to bring it into real world use. Science at its heart is a glacier- cold, unworried, progressing forward in an unstoppable manner. It also has the inertia of literally hundreds of years and in general a highly conservative set of guidelines. What needs to be fought against is this idea that peer review requires a third party outside of the scientific community. The internet and the transparency that it brings makes a third party paid watch dog unnecessary, there are plenty of folks on the internet just looking to "yell gotcha".

There is some value to the conservative mindset that works well for society and Progress-the burden of proof. The conservative guidelines protect Science from making too many mistakes and jumping to conclusions based on the unexplained. It's what prevents Einstein's theory from being torn down by a faulty wire. It also means that the younger generation of scientist must bring ideas to the hallowed halls of old science and prove that it will work by bringing real world suggestions that will fix the interwoven problems of publication, attribution, grants, jobs, and tenure. 

Otherwise its just pissing in the wind and complaining. Not my idea of what scientists do. They come up with theories, models and explanations-that are then roundly torn  down by their peers and rebuilt into a better product.

With that said lets take a look at how open access and "non-publishing" publishing could work in the real world*. 

First some challenges that I see as the main drag on process:

1. Comparative analytics. There needs to be transparent metrics to gauge the value of the research to the larger community. This can be an issue since every scientist does the most important research to the world.
2. Control over content-this may seem trivial but if I am the principal investigator I'm not sure I want every post-doc and grad student uploading their crappy, blurry images. The metadata surrounding who gets tagged, whats get tagged and the terminology is vital to ensuring that the data can be reviewed by everyone who may be interested. 
3. Clear lines of permissions-What role do collaborators play in making this public who gets to post it? where is it hosted? The university still has some co-ownership. This is not something that can be decided afterwards it has implications for grants, etc.
4. What about intellectual property? I'm all for open collaboration and sharing data with academics but what guarantees are there that pharma and biotech will play by these rules? The beauty of public research from the grantor's(read government) point of view is it maximises their investment. That is lost if [insert huge pharm company here] comes along and builds a drug based on that data and charge the public obscene amounts of money.
5. The content that is made public has to have a finished look. This can't be just thought vomit. It must have some clarity of thought and citations. Put some thought into it! Distill by putting into context, why should I care? how does it support or counter the current models. Proper citation through hyperlinks. It should be peer review not crowd sourced editing.
6. Control over comments. Comments can't be removed just because someone says your data quality sucks. This has to be transparent warts and all. You have to take reviewers suggestions of more experiments seriously. As someone who has reviewed for a variety of journals (top five to lower tier) nothing is more frustrating than taking the time to review and having someone completely disregard it. 
7. Buy-in from senior scientists. Science is largely a oral history, the reality is that for most methods just having the paper is useless for understanding how to do it or where the problems can arise. The insights from senior scientists that have seen it all are required for this to be truly revolutionary. 
8. Buy-in from Administrators. I for one do not believe that open publishing will be any less time consuming or cheap for the scientist. Someone will have to maintain the database for the content and ensure that there is enough capacity for the videos, excel files and what not that will be made available. This will have to be maintained for decades with back-ups, etc. Someone will have to know where and what there content there is AND when is should be taken down and replaced. Right now the university covers those costs for each departments website, unless there is a clear benefit i.e. grant money, donors, clarity on which faculty members are doing well and in a perfect world which require more help.

Now the potential solution:

A dedicated website where each lab publishes its own data. Personally I don't be believe that all data should be available but some labs and branches of science believe that is best. Allow the system to have some flexibility, some fields are inherently more competitive and technically nuanced than others. Scientists need to retain the ability to check data quality, accuracy and potentially fundamental flaws in experimental setup as a lab group prior to making it public. 

I like figshare and creative commons and all of the really great tools that are coming at breakneck speed. I love the idea of posting of all of the data but I truly believe that my job as a scientist is to analyse the data not just find/acquire it to send to others. If open access publication does not include this it will set back cancer and other highly nuanced fields in biomedical sciences years. These fields have moved at breakneck speed because such a premium is placed succinct analysis by the publishers. While I do not believe publishers should be the gatekeepers, I do not want to lose the analysis of data for the sake of speed of publication. 

The solution: most labs have university owned/manged websites where the Principal Investigator (aka PI, professor i.e. the person who's tuckus is on the line) owns the admin rights. These should become more of a real world home for the publication and sharing of lab data. It exists and some labs do a great job of updating it with content as it gets published. Everyone else needs to get on board bring it into the modern age with appropriate tagging and labels to ensure that it can be found through search engines.

PIs need to retain control, they are the ones that will be held accountable if the "published" result that shows a new cure for cancer that turns out a contaminant. The pervasive nature of the Internet means that the media has access to the data and need to hype themselves as getting the most interesting story. "Never let the truth get in the way of a good story" is a truism for more and more journalists. Accidents happen and while I'm alright with being embarrassed by my peers figuring it out, I'm not alright with it spinning into a worldwide story and having to explain that it was an "oops" to the public. 

Main point: Use the established website, each PI has admin rights to remove. Give senior lab members the ability to publish concise analysis with appropriate figures and links to the whole data set with metadata and clear descriptions. As part of the mentorship for new post-docs and graduates students training on what is considered an acceptable level of proof prior to making the data public. Laboratories are still training grounds, as someone who has trained students and post-docs the peer review process allows young scientists looking to move up to the majors an idea of what good science is-this cannot be lost by opening up publication. I love the citizen science movement but at the end of the day, like anything, there has always been a difference between someone who does something as a hobby and someone who has the discipline, passion and willpower to dedicate their life to a subject. Training and the culture of science has to be part of it-science is about justifying your opinion and the quality of data. 

Peer review isn't broken, the publishing models are, let's not throw the baby out with the bath water. The university controlled site allows for clear rules of engagement for pharma, media and allows for the level of control that PIs, chairs need to ensure that crappy data doesn't not spiral out of control into a scandal. The departmental chair and grant study groups can look at the metrics; website views, re-links, etc to allow flexibility into the systems for review whether it be tenure, grants or something else that no one has thought of. Open access will be a failure if it does not give everyone involved with the industry (yes its an industry! get over it people). It's not perfect but it can be piloted in a way that senior scientists from the core Cell, Nature and Science author pool can at least talk about. I think that many of the ideas that are being bandied about are much better than this for science as a whole and ultimately will be the long term solution. 

That being said I have yet to see an idea that any of the top level Cancer, Stem Cell, etc scientists will buy into. This is not a group to dismiss, they may not be the majority but they represent the main attraction for why scientists will not give up on the Elsevier or any other for profit publisher. They also are the presidents or senior leadership of some of the most influential universities in the world (Caltech, Rockefeller U., Memorial Sloan-Kettering, Max-Planck, etc). As a final reason to get them on-board they also are on the grant study groups and a variety of other activities that effect all levels of at least biomedical sciences.

At the end of the day the risk posed by publishing incorrect data needs to be balanced with greater access and conversation about what can be done next. Please comment as you see appropriate.

*Disclaimer-I only have experience with a limited number of institutes(eight) so I do not know if any of this is applicable widely. I have no idea if the issues that are bringing up are universal or limited to the institutes that I have worked at.