Category Archives: Biology

To TED or not to TED…that is the question (for researchers)

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All opinions are my own and do not necessarily reflect those of Novo Nordisk

Sharon Begley on Twitter (@sxbegle) pointed out an interesting article today about the effect of giving a TED talk for academic researchers.  The authors use a variety of library science techniques to characterize the TED-giving population.  Among other things, they found that presentations by academic researchers were generally more cited and liked on YouTube, but also that the number of citations of an academic researcher’s work did not increase after giving a TED talk.  This might suggest TED talks help researchers raise their public profile, but not necessarily their academic reputation.  There are caveats here, one of the main ones being that the scientists giving TED talks generally were measured as relatively “impactful” in terms of their publication history.  So, maybe these guys (and they’re mostly guys) were already cited as much as they would ever be.

On the other hand, getting a Nobel Prize does increase the number of times scientists are cited, so it is possible to increase your citations in some ways.  Just, you know, win a Nobel Prize.

This topic could go in a lot of directions–the role of scientists in popularizing science, the general TED phenomenon, public hunger for science versus science literacy, and maybe at a later point I can come back to that.  But in reading this study the first question I found myself asking was:  Does giving a TED talk get you more grants?  If we think about the academic research ecology, grants are the sun that feed the fields of academic research.  No grants, no research.  Also, no grants, no position.  And so I turned to the senior author on the study, Cassidy Sugimoto of Indiana University Bloomington.  I asked whether she thought grant funding might increase with a TED talk.  Her response via email:

“My hypothesis, motivated from our data, is that you would not see a significant difference. The scholars invited to present at TED were already in the scientific elite, cited significantly more than average for their fields. I would hazard a guess that they are also more likely to receive grant funding, but not because of TED. They are chosen for TED precisely because they are already elite. It’s a perfect example of the Matthew Effect at work–to those who have, more shall be given.”

And that led me to think of another question:  could giving a TED talk decrease your odds of getting a grant?  While we would like to think of the grant-awarding, peer review system of the NIH, for example, as fair and impartial, I have yet to meet a scientist who believes this.  This may not be a terrible thing–to paraphrase Winston Churchill, “It has been said that ‘NIH peer review’ is the worst form of  ‘grant awarding’ except all the others that have been tried.”  However, it does allow bias to creep in.  Studies have looked at the presence of biases in grant awarding under such theories as accumulative advantage.  Reviewers are human.  Humans have feelings and opinions.  If the human reviewing the grant of a TED speaker has strong negative opinions on the value of public engagement, or perceives TED presentations as grandstanding, would that lead unconsciously to a lower score?

On a practical level, the N is far too small and the timeframe too short to see the effect, if there is one.  Check back in 20 years and we’ll see.  But let me take this one step further and now ask, even if giving a TED talk doesn’t help in citations or grants, can it be a net positive for a researcher’s funding because it increases the probability of being able to use crowdsourcing approaches?

A number of researchers have sought research funding via Kickstarter and other sites.  However, I believe potential funders have a limited amount of disposable, impulse-driven income (I think of this as the iTunes/Latte pool), so this isn’t an endless new resource.  Right now the opportunity for crowdfunding is still pretty open but soon we could see many more scientists trying this route, especially as government sources of funding dry up.  In that case it will be a competitive market, and fame, such as might come from a nice TED talk, could be one of the factors leading to people choosing one project to fund over another.  Which could lead to what Cassidy Sugimoto refers to above as the Matthew effect.  The rich get richer.

And there are other possible negatives to crowdfunding, such as when researchers become driven to self-promotion to get crowdfunding support. To quote again from Cassidy’s email:

“…I think there are more disturbing issues in terms of branding of scholars. It is no longer sufficient to just do high quality research and publish it in reputable venues. Scholars must engage in personal branding–through social media and other means–to raise their value. Citations are not enough–now scholars also need to demonstrate their value in terms of tweets, media mentions, and the like…However, the negative implication is incentivizing branding over scholarship.”

But that’s a topic to expand upon some other day.  In any case, the possible negatives for giving a TED talk seem far outweighed by the real and possible benefits, and I’m in favor of anything that makes scientists talk to the public.

Not losing versus playing to win in Baseball and drug development

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All opinions are my own and do not necessarily reflect those of Novo Nordisk

Another in a series about parallels between baseball and drug development

A recent post by Phil Birnbaum, who runs a baseball research site, did a nice job of highlighting how he feels stastisical analysis may best serve baseball organizations:  by ensuring that they don’t make losing moves.  While everyone is trying to win, in an industry where so much is uncertain, in many cases, it may be most effective to  “First, concentrate on eliminating bad decisions, not on making good decisions better.  And, second, figure out what  everyone else knows, but we don’t.”

This is a terrific observation, and one he backs up through the body of his post with examples from baseball and gambling strategy.  I think it applies quite well to drug development too.  I’ve made the earlier conjecture that drug development can be thought of as existing on the adaptive landscape, with improvements to drugs or drug classes getting harder and harder as you climb up that mountain of efficacy.  But when you’re on a slope, it’s really easy to go sideways or backwards.  So, the analogy here is that drug development, like baseball, needs to throw a lot of resources (not just statistical and analytical ones, either) into preventing a bad decision.

This thinking is also influenced by the ecology of pharma and biotech.  Let me be very clear about my initial assumption:  drug development is filled with really smart people, almost all of whom are dedicated, sharp, innovative, and really interested in winning.  So is baseball, (well, except maybe for the Kansas City Royals).  But it’s hard to put together a good drug development pipeline.  Resources help.  Resources often help.  But they aren’t enough.  And since the talent is there, the explanation for lackluster drug development progress may partly be found in companies still making poor decisions on assets.

Let me zero in on the second part of the quote in the first paragraph:  “And, second, figure out what everyone else knows, but we don’t.”  Here’s something else that companies could possibly do differently:  share data.  A really fascinating blurb in ScienceInsider just highlighted an effort by people at Johns Hopkins to try and get clinical trial information published, as long as it’s been publicly released in other formats such as through litigation or Freedom of Information Act requests.  While all the companies would prefer this not happen, if it happens uniformly, that can only be good for drug development as researchers learn more about why given trials were halted or failed.  If R&D costs as much as it does, part of the reason lies in duplicated effort.

To conclude, let me throw out another thought on decision making:  send in the crowds.  Crowdsourcing as a method for making decisions has been tried in a number of contexts and often has been found to lead to better overall decision making than more traditional methods.  If we want to make decisions on, for example, which drugs should move forward, setting up a system to poll everyone in the organization in a controlled, anonymous way might be enlightening.  I know this would not be a popular development for people in the C-suite, since, after all, that is their domain.  And I believe the assertion Malcolm Gladwell makes in Outliers that initial, small differences in environment can eventually lead to great differences in ability down the road as individuals get training and experiences not widely available.  Therefore those who are in the C-suite are different in their knowledge and outlook and know more about strategic decisions.  But they still don’t know everything, they still are human, they still have biases.  And a technician working in a lab in Boston may have noticed something in his cell cultures that  no one else is aware of.  If we want to make good decisions, shouldn’t we make sure that everyone possible has a voice?

Reining in Hyperbole About the Role of Drug Development

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All opinions expressed are my own and do not necessarily reflect those of Novo Nordisk

“The traditional pharmaceutical research and development operating model is no longer sustainable,” says Dennis Liotta, PhD, founder of the Emory Institute for Drug Development (EIDD) and co-inventor of multiple approved drugs. “The marked decrease in the development of new therapeutics is having a uniformly negative effect on global health and threatens life expectancy, quality of life, economic development and national security. Emory’s new public-private enterprise is a bold new approach that can help solve this problem.”  From a press release from Emory University

Yesterday Emory University announced the creation of a non-profit entity, Drug Innovation Ventures at Emory, LLC (DRIVE), that aims to take discoveries made by Emory scientists and bring them to the point of proof-of-concept clinical trials.  I think this is a great idea.  While this press release is what I would call a bit overstated (while at the same time understating the real problems involved in translating discovery science into actual drugs), drug development is in need of different ideas and different approaches, and I’m all in favor of various organizations trying different things to develop drugs.  I’m also in favor of any system that gives academic researchers exposure to the steps leading to a lead candidate drug.

What concerns me, though, is the quote above.  Again, this is a press release and some hyperbole is to be expected, but at the same time is it fair to say that the reduced number of new drugs being developed is having a “uniformly negative effect on global health?”  Digging into DRIVE’s webpage, it’s clear the organization plans to focus on viral diseases, which makes the connection to global health direct.  However, I can’t help thinking that there’s a lot more involved in helping the health of people in developing countries than new vaccines and antivirals, and that while new drugs could help, the lack of new drugs doesn’t condemn those populations into some kind of downward spiral.  I doubt Dr. Liotta meant this explicitly, but his comment supports a view of a specific kind of technological innovation–drug development–as providing a cure, when I’d rather see expectations managed with a little more circumspection.  I think the industry suffers when presenting cures as being accomplished with a simple pill or a shot.  Many times, maybe most times, health problems are best viewed as the result of multiple, intertwined factors, of which biology is just one.

The Global Alliance for responsible sharing of genomic and clinical data: an Asilomar conference for today?

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All opinions are my own and do not necessarily reflect those of Novo Nordisk

I’ve been mulling over the recent announcement by several prominent genomics organizations of a set of standards for the generation and sharing of genomic data.  This is a fantastic development in the field, and one with great implications for the future of genomics data research.  It’s also particularly apropos given the recent news that the US government has been collecting internet-based metadata broadly, in a previously secret program to detect signs of terrorist activity.

People are waking up to the idea that we all produce data of all kinds, and that advances in technology now make gathering that data as easy as getting wet in the Seattle winter.  Whether that data is created digitally and automatically throughout our day-to-day life, or via an action as simple as sending a cheek swab to a company, there are some deep questions that are just beginning to be asked, by the government and other organizations, as to how the use of these data best serves the public good.

As a UC Berkeley graduate student in the late 80s and early 90s, I heard the lore about the Asilomar Conference on Recombinant DNA.  I think it was part of our standard indoctrination package, along with instructions on how to navigate Telegraph Avenue and reasons why Berkeley was superior to Stanford and UCSF.  That conference, in the early days of the age of gene splicing technologies, was an amazing example of self-regulation by a group of scientists who had the forbearance to actually stop and think about the possible implications of what they were doing,  The Asilomar conference led to a set of standards for the practice of recombinant DNA technology, and an overall greater mindfulness of what we were actually doing when we moved genes around among organisms.

The announcement of the Global Alliance has a similar flavor to me.  Again, technological advances have opened a huge window of potential research opportunities that were not possible before.  The implications, however, will be unclear for quite some time, and the effect that cheap genome (and other kinds of) sequencing will have on research, public health, ethics, medicine, and many other fields is unknown, other than that it will be huge.  We were already seeing the beginnings of chaos in terms of data repositories, standards, and practices, but this Alliance suggests that, at least at the level of key players like the Broad Institute and the Wellcome Trust, there is a commitment to taking  a step back and trying to find a good answer to the question of how to do this well, to best serve the public good, and to try to minimize harm.

I wish them luck.

Sea turtles: Nature’s smartphone

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The recent publishing of the green sea turtle genome brought back memories of my first encounter with baby sea turtles, and one of the most fun and astonishing examples of hardwired behavior I know of.  I had the good fortune to travel to Heron Island in the Great Barrier Reef during my undergraduate days.  We were there in March and April, the Down-Under Fall, when the sea turtles hatch and begin their journey to–well, to be eaten, frankly, although a few percent do make it to adulthood.

The first nest that I saw hatch emerged in the afternoon on a rainy day.  Normally sea turtles come out of the nest and make their way to the water at night, and use cooling temperatures as a cue.  Rain fools them into thinking it’s dark, and this hatch was making their break in broad daylight.  We watched the baby turtles–each no bigger than a big kiwi fruit–flop awkwardly towards the water, alternating their flippers and dragging themselves forward.  We shooed away the seagulls who watched us with petulant expressions, since the normal fate of a baby sea turtle hatching during the day is a short trip down a seagull’s throat.

But none of this is the behavior I was thinking of.  Rather, the amazing thing is what happens when you pick up a baby sea turtle.  Once the pressure of the sand beneath its belly is gone, the motion of its flippers magically switches from alternating to synchronized, both flippers flapping in unison like the oars of a sculler on Lake Union.   Even more remarkable is what happens when you tilt the turtle from side to side, or front downward or upward.  The rear fins, useless on land, become rudders, turning in just such a way as would correct the turtle’s posture in the sea so as to keep it level and moving straight ahead.

Tilt the turtle head down, both rear fins bend up.  Tilt it to the left, the left rear fin bends down and the right fin bends up, while one front flipper stops moving and the other churns frantically.  The newly hatched sea turtle needs to get out to sea fast, to avoid the predators in the reef along the way, and its coloring (dark on top, light on bottom) are optimized to make it difficult to see as long as it remains level.

This is what evolution does.  It takes random variation and selects for those combinations that lead to reproductive success.  If those variations have their root in genes, those genes get passed along.  I’m curious to see if anyone tackles the question of how the turtle keeps steady, now that we have the tool of its genome to help.  I’d love to learn what goes into hardwiring this kind of behavior and who knows?  Maybe nature’s figured out some tricks that the cellphone makers don’t know.