"Junior Manager" Training for PhD Students

Peter Fiske, at naturejobs, has a great opinion on how graduate training can be improved:

Academia might do well to look to the private sector for a model that broadens the soft skills of PhD holders and expands their prospects. Many businesses offer their executives short, intensive training programmes that stimulate their professional development in key areas such as leadership, innovation and management. ... The goal is simple: to develop the capabilities of junior managers without costing a lot in terms of time, money or disruption to their jobs.

Very well put!  Of course, there has to be buy-in from faculty, schools, and students, and people will definitely need to get over the perception that this is a more 'corporate' culture of training.  In closing, Fiske highlights one last challenge with the scheme: Money.

But how to finance them? Those who benefit should pay. That includes not only funding agencies, but also students. They might pay through general student fees. Even better — to ensure that they are fully invested — they might devote credits to an actual course on career planning 

While the question of paying more for this kind of "extra" training is just one about numbers, I would argue that it be included in current tuition fees, which hover around $6,000 to $8,000 annually (and up from there, if you're in the United States).  After paying for my PhD coursework (which in retrospect was a more or less average value for my educational dollars), tuition dollars seemed to fall into a black hole of university upkeep and expensive paper shuffling, especially in the late stages of a PhD when my demands on the school were almost nothing.  It would have been great to take courses like Fiske describes, even if only a break from writing a thesis!

Hypothesis Generation in Biological Research Grows

Titus Brown wrote a long, yet wonderful, narrative of how the ease of doing 'discovery science' and generating tons of data (by sequencing or other 'omics approaches) is rapidly leading to extended periods of analysis prior to doing more experiments:

Hypotheses are now cheap (because data is plentiful) and I think we should focus on developing likely hypotheses and winnowing out the dumb 'uns computationally before we ever pick up a pipette man to test 'em. That is, expand the hypothesis-generation and analysis stages so that we're more likely to develop a comprehensive and interesting hypothesis.

Most computational biologists have experienced the tension between needing to analyze data and actually doing more experiments to test ideas.  The underlying source of that tension is usually another scientist that believes in a mistaken assumption: Doing experiments counts as work; Data analysis does not.

Thankfully, it's also an idea that's rapidly becoming anachronistic. 

More and more biologists (i.e. bench scientists) are becoming dependent on people programming and using computers in ways that a regular desktop users does not.  Using Excel to do bioinformatics doesn't cut it.

The Importance of Keeping a CV (or a Backlist if you're a musician)

I've always liked Seth Godin's daily bits of wisdom. 

Here, he espouses the idea of keeping a "backlist" of everything you've created, which is much like maintaining an academic CV, except it is much more public.

Besides being as a resource to direct people back to your work, Godin points out that keeping backlist has a subtle, yet very important function:

You’re going to become a lot more aware of the posterity of the work you do. It’s all on tape, all left behind. Just as you’re less likely to litter in your own backyard, the person aware of his backlist becomes more careful and civic minded.

In other words, if you make it easier for people to see everything you've created, you're more likely to focus attention on producing quality work.  It's a focus is directly applicable to many creative endeavours, including science.  If make it easy for everyone to see your CV and what you've decided to spend your time on, over time, you should become more selective of what ends up on it.

Sometimes producing great work isn't about producing a lot and selecting only the best examples, it's in avoiding the projects you shouldn't be wasting your time to begin with.

Pervasive Sequence Patents Covering the Genome

A new paper in Genome Medicine argues that there's a huge body of patents on DNA sequences which, according to current legal definitions of a minimally patentable sequence (15 nucleotides long), are easily infringed upon:

Current patents for both short and long nucleotide sequences are extraordinarily non-specific and create an uncertain, problematic liability for genomic medicine, especially in regard to targeted re-sequencing and other sequence diagnostic assays.  

Basically, their argument is that patents on a particular sequence for one function restrict the ability of others to use the same DNA sequence for other purposes.  The problem seems very serious, given the bare minimum length of a patentable sequence.

An analysis of all current US patent claims and the human genome presented here shows that 15mer sequences from all human genes match at least one other gene. The average gene matches 364 other genes as 15mers; the breast-cancer-associated gene BRCA1 has 15mers matching at least 689 other genes. ... Furthermore, 15mer-length claims from bovine and other animal patents could also claim as much as 84% of the genes in the human genome.

To my knowledge, a patent on a molecule (be it a chemical or a nucleotide sequence) is on its use for a specific function.  So the patent for a DNA sequence to detect Gene X can also be patented (separately) to detect Gene Y, and it makes little sense to grant rights over Gene Y as a bonus for the inventor that originally worked on Gene X.  If any readers have specific examples of this, please email me.

This situation clearly provides a disincentive to work on things that might be considered to be infringing, and it's actually absurd, on a social level, because inventors usually don't have the resources to develop all possible uses of their original invention, and other people will fill in the gaps if given the chance.

When a Strength Becomes a Weakness

I come across a lot of bright people doing research, be they graduate students, scientists, technicians, or project managers.  One strength common to all these people is that they're able to learn new things, usually very quickly.

I usually pin this ability down to people having an innate desire to experience the "Wow, that's cool!" moments that come with gaining knowledge of something that's not known to you.  After many years, it's a character trait that can't be quashed very easily and so it permeates many things you do.  These people are drawn to learn about new and unknown things which is why they ended up in a research career. 

Learning new things is a great strength when you're trying to discover a scientific story that's completely new to the world.

Sometimes, however, this strength becomes a huge weakness.

A lot of work that goes into scientific discovery isn't glamorous, breathtaking, or interesting (even to people doing the work).  Stocking labs, doing inventory, managing software, documentation, and many other tasks are neccessary but not central to discovering new science, but there's always something to learn within each of these activities. 

Here's where the skill of recognizing when 'good enough is good enough' comes in handy.  The desire to learn about any of these task in great detail leads people down roads with little payoff, compared to becoming the expert in the one thing you're actually trying to accomplish.

On Science, Statistics, and Lamp-posts

"An unsophisticated forecaster uses statistics as a drunken man uses lamp-posts - for support rather than for illumination." - Andrew Lang

I first heard this quote a few weeks ago at AGBT, describing an unsophisticated scientist for the sake of the audience. 

The gist of the talk was to explore how high-throughput sequencing of RNA can help discover alternative forms of a gene that happens to be a drug target - this is particularly important as the alternative forms might bind the drug target poorly, or not at all.  The speaker emphasized that statistics, particularly when dealing with big data like genomic sequencing, should be designed and used very carefully and that users need to be aware of what stats can tell you, what they can't, and when obsessing about the right statistics to use isn't worthwhile.

Most importantly, she criticized the use of stats used to lend significance to an already obvious conclusion.  If two observations are really that different, a t-test to hammer home the message with a P-value of 10^-167 is overkill, especially if it's part of a series of experiments that close the book on the statistical question in the next figure.

Using stats for the wrong purposes can also raise a red flag for people reviewing your work, for if the test you've used isn't appropriate for your data, it can mean two things: you weren't aware of the right test to use (which is ok), or you don't really care and your stats are just for show (which is not).

In the end, it's better to use rely on statistics to help guide questions than to 'prove' something that's already self evident in the data you're communicating.

Private Donors Organize to Fund and Participate in Parkinson's Research

Bradley Fikes, U-T San Diego's biotechnology reporter, wrote an eye opening article describing how people suffering from Parkinson's disease are organizing private donations for research that they themselves will by party to.  It's a potentially very powerful method of organizing and pitching research projects that have huge potential but are still too risky (for various reasons) to receive government funding.

The project itself is fairly obvious and Fikes describes it as the "low hanging fruit" of stem cell therapies: generate dopamine producing cells from a patient's own induced pluripotent stem cells and reintroduce them to the patient.  The fundraising hopes to get around one big obstacle:

Because the technology is so new, getting government grants hasn’t been possible, say scientists on the project.  So the eight patients and their supporters are raising the money to finance the research themselves, under the name of Summit4StemCell, operating under the nonprofit aegis of the Parkinson’s Association of San Diego.

In essence, they're eliminating the granting agency and acting more like a private foundation, except here the foundation is being run by and for the founders and is pitching a very unique opportunity.  They've identified a worthy line of research, they've assembled a team capable of delivering on the project, and they've lined up a cohort of willing research participants to top it all off.  Recruiting participants can be an entire standalone part of the project, and they've already done it.

Now all they need is money to grease the wheels and get moving.

Matchmaking for Collaborative Science and Discovery

Simon Williams, at Soapbox Science, has this to say about the changing style of science:

The days of the lone scientist, immersed in their laboratory, locked in their disciplinary silo, narrowly focused on basic research problems is rapidly becoming a thing of the past. In their place, we see the emergence of a new breed of “Team Science”; where  large, cross-disciplinary teams focus on complex, applied and translational problems.

Not only has the 'disciplinary silo' of days gone by become a rarity, I would even say that it's an unappealing career prospect to most people going through science training.  People like to share their experience and discoveries with others.  Williams write about the Team Science Toolkit, a National Cancer Institute sponsored site to connect these kinds of researchers.

The idea itself isn't new, and I don't claim to be the first one to voice it.  But I've previously commented on how running projects in 'stealth mode' is a bad idea and wrote up a conference session featuring Stephen Minger from GE Healthcare, who described a collaboration between GE and Geron that was essential for learning about industrial scale cell culture.

In addition, there's an interesting description in Williams' blog post of a toolkit developed by Michael O’Rourke at the University of Idaho, who believes that collaborators can be matched based on a set questions that explore their views on how they like to do science:

Examples include whether a researcher prefers quantitative vs. qualitative methods, or reductionist vs. holistic approaches.  By asking questions, the idea is that, by making our dispositions more explicit, we are able to more effectively work through and round them. 

It sounds a lot like a dating service, but putting that aside, it's a very neat concept that should work with professional relationships. 

I'm not sure how many people would take a personality test prior to striking up a collaboration with another investigator or student, but it might be very useful for groups like collaboration centers (like MaRS, where I work) to identify compatible people and make the effort to introduce them. 

And why not? Serendipity plays a big part in discovery and invention.

A Very Thought Provoking Interview with a Google Statisitician

From an interview with Nick Chamandy, via Simply Statistics:

Grad school teaches us to spend weeks thinking about a problem and coming up with an elegant or novel methodology to solve it (sometimes without even looking at data). This process certainly has its place, but in some contexts a better outcome is to produce an unsophisticated but useful and data-driven answer, and then refine it further as needed. Sometimes the simple answer provides 80% of the benefit, and there is no reason to deprive the consumers of your method this short-term win while you optimize for the remaining 20%.

I wish more people doing academic research thought this way.  Striving for perfection is a habit that dies very hard.

Link

The Natural Breakup of Geron Discussed at Signals Blog

An article I wrote discussing BioTime's recent purchase of Geron's stem cell program was just published on Signals Blog. 

The transaction was very obvious once you consider all the executives involved.  Two former Geron executives, Michael West and Tom Okarma, have been involved in stem cell research for decades and lead the companies acquiring the research program.  Geron becomes a company commercializing a portfolio of oncology drugs with leadership to match the needs of those ambitions.

An Argument for Sharing Medical Data

A very interesting TED talk on pooling medical data.


With an interesting comment at 4:49 on how patient consent methods now have unintended consequences:

That was 70 years ago, and the way we gain informed consent, this tool that was created to protect us from harm, now creates silos. So the data that we collect for prostate cancer or for Alzheimer's trials goes into silos where it can only be used for prostate cancer or for Alzheimer's research. Right? It can't be networked. It can't be integrated. It cannot be used by people who aren't credentialed.

Harvard Searches It's Own Email Accounts, Staff Enraged

There's a nice commentary on Harvard searching staff emails at the New York Times:

Faculty responses revealed a gap between expectations in academia, where privacy is often seen as integral to academic freedom, and the corporate world, in which employees are often told to assume that workplace e-mails are not private. Some professors wondered aloud whether they had been naïve to think that things would be different at a university, and said they were forced to re-examine assumptions about confidentiality. 

The article does explain that Harvard searched resident dean accounts, which are arguably work related, and even then only searched subject headings for evidence that a particular email was forwarded.  If the @harvard.edu account is a work related account, the content belongs to Harvard.

This is a life lesson for all learned people with university accounts: Unless the email account has explicitly been made for your personal use, it's probably a workplace e-mail.

Bees Demonstrate How Caffeine Improves Your Memory

From New Scientist:

Bees given sugar water laced with caffeine were twice as likely to remember the scent – and stick their tongues out in anticipation – three days later, than bees fed on sugar alone.

and

Looking at how far bees will go to get their caffeine hit – and whether they willingly put themselves in danger – could answer a fascinating question, says Wright: "Can an insect become addicted to a drug?"

In mammals, caffeine inhibits adenoside receptors in the hippocampus, encouraging the formation of long-term memory, says the original Science article of this study.  Bees have a similar region of the brain and can model the same effect that caffeine has on humans.

Just another thing to ponder when you sit down to work or study with your usual cup of coffee or tea.

Link to article at New Scientist
Link to original Science Article

Versatile Breast Stem Cells Become the Next Big Thing (Maybe)

Ron Leuty, for San Francisco Business Times, writes about a new type of stem cell discovered at UCSF:

Endogenous pluripotent somatic, or ePS, cells could give rise to a new line of companies hoping to harness the potential therapeutic power of the discovery.

and

ePS cells don’t appear to be left behind by embryonic stem cells, like pieces of bread dropped on a path to help someone find the way home, [Thea] Tlsty said. The ePS cells, she said, have different expressions, surface markers and other characteristics than those found with embryonic stem cells.

The cells sound interesting, probably ethical, but a lot of work is needed to determine what the cells are useful for.  The abstract of the paper itself doesn't scream that the cells are going to bring a new era of stem cell research, so generating hype risks alienating the public from research that inevitably fails to meet expectations.

But are ePS cells something to keep an eye on?  Definitely.

Journal Allows Plagiarized Article to be Rewritten, Republished

An interesting case of academic plagiarism described at Retraction Watch:

A reader  flagged the plagiarism in the original paper, “Protein domains, catalytic activity, and subcellular distribution of mouse NTE-related esterase,” by Ping’an Chang and colleagues, which led the research team to revise and resubmit the manuscript. 

With an interesting comment from reader scott allen:

Universities have lawyers on staff, who should be more active in this area, granting agencies should be more proactive in the recovery monies, why shouldn’t universities, professors be required to return the grant money. Any honest researcher who didn’t get a grant that was given to one of these fraudsters should be mad as heck.

Maybe not mad as heck, but pretty damn annoyed that the research system isn't more efficient at rooting these people out.

Mindboggling Medical Billing in the USA

At TIME Magazine, Steven Brill wrote a tremendous essay on why the US medical system suffers under the extreme weight of it's billing practices, especially the disconnect between costs of providing service to amounts patients pay.  Brill describes it as "the ultimate seller's market":

When we debate health care policy, we seem to jump right to the issue of who should pay the bills, blowing past what should be the first question: Why exactly are the bills so high?

I wonder the same thing.  Why did one woman in the article pay $21,000 for a false heart attack while someone I know, in Canada, pay $45 for essentially the same experience?

Crowdfunding: A Bad Fundraising Strategy for Biotech

This article in GEN suggests that crowdfunding isn't all it's made out to be, at least for biotechnology startups.  Here are a few of the main reasons:

1. Regulation is still in flux.  Regulations surrounding equity based crowdfunding are still being hammered out and investment-based crowdfunding will still need to go through brokers.  Seems like the crowdfunding platform is an extra layer of complexity in this situation.
2. Low ceiling on funds raised.  There's a maximum of $1 million raised per 12-month period.  This is completely absurd for most biotechnology projects.  You might be able to hire a small group of software developers for a web startup for this amount, but $1 million per year is the burn rate for a medium- to large-sized academic lab consisting of graduate students and postdocs (who make 50-70% of market wages with no loaded labour costs of benefits or pensions).
3. 10-20% of the total amount raised goes to fees.  Enough said.
4. Loss of confidential data.  If you need to disseminate information to the crowd to raise funds, it's guaranteed that a competitor will see it.  In biotech, competitors with more people, funds, and technology will take a key idea and run with it - way faster than you can.

The rest of the article at GEN is definitely worth a look!

Organic Food Preservatives Being Developed

Are you one of many people who dislike eating food with artificial preservatives?  Or do you hate throwing away preservative-free food because it's spoiled?  Soon, you could be in both camps.

Here's a short article at Biotechnology Focus that describes work at the University of Alberta to develop organic food preservatives.  They goal is to increase production of antibiotic peptides secreted by lactic acid producing bacteria and use the bacteria as preservative agents.

Many bacteria produce antibiotic peptides, called bacteriocins, to compete with other bacterial species.  The nice thing about these peptides is that they've evolved to target a small group of competing bacteria while leaving other closely related microorganisms alone, so in principle they shouldn't have any adverse affects on mammalian cells.

The work described teams up researchers with CanBiocin, an industrial partner with extensive experience in the cultivation of Lactobaccillus and development of products from the bacteria.  In fact, they already produce a product called Micocin, which appears to prevent the growth of Listeria better than "a chemical preservative".  Micocin has been approved for sale in Canada since November 2010, two years after the 2008 Listeriosis outbreak that killed 22 people and created a huge overhaul of meat processing at Maple Leaf Foods, the origin of contaminated products.  I'm not sure what the cost of Micocin is versus traditional chemical preservatives, which are probably just nitrites.

It's a great idea, but I'm left wondering how people will accept the framing of bacterial peptides as "organic food preservatives".  While it's true that the peptides aren't chemical based, and that they are naturally derived, marketing Lactobacillus peptides as "the same preservatives naturally found in yogurt" might be a better sell.

Ultimately, if the performance of the peptides beats chemical based preservatives, like Micocin apparently does with Listeria, the "organic" label won't even be necessary for market acceptance.

Biotech's Model of Creative Acquisition

Leslie Glick, for GEN writes:

What is almost unique about biotechnology today is that competition to provide a particular product does not necessarily result in winners and losers, because the potential marketplace for a wide variety of biotech solutions is so huge, and both the technology and the underlying science are advancing at an ever-accelerating pace. ... Today, the ability to raise capital, the inventiveness of a company’s scientists, and the leadership capabilities of management are more likely to determine the success or failure of the company, rather than whether or not some other company develops a similar product first.

It's a very interesting conclusion, in the sense that success of companies, specifically biotech companies, is dependent on people from three different disciplines - finance, science, and management.  If one is lacking, the whole triangle collapses.  This is in stark contrast to what a die-hard scientist will tell you: Science speaks on its own, which is an incomplete viewpoint at best and delusional at it's worst. 

Glick continues:

Around 70 years ago, Austrian economist Joseph Schumpeter coined the term, “creative destruction”. In essence, entrepreneurial innovations disrupt the status quo. Up-and-coming companies overtake the former leaders, which then fade away. As I noted in the January 15, 2011, issue of GEN, “When one considers the vibrant pattern of financings, internal growth, acquisitions, and yes, closings in the biotech industry, it clearly fits Schumpeter’s model of creative destruction.”
However, that is not the whole story. While creative destruction certainly applies to the biotech industry, so does what one might call creative acquisition. In other words, successful firms do not necessarily lead to the failures of other firms but rather to their own acquisition by larger firms. Creative acquisition is a function of the ever-increasing growth potential of the biotech industry.

Creative destruction isn't a new concept, but the idea of 'creative acquisition' is a natural one for biotech.  The skill-sets at each step of research and development are extremely specialized and unique, and since an idea/invention needs to go through multiple steps to end up profitable, let alone used in the market to help people, development inevitably behaves like relay race instead of an all-versus-all competition.