A while back, my attention was captured by a National Public Radio piece describing how the US Military is applying Social Network Analysis tools and methods to catch roadside bombers in Iraq and Afghanistan.  While some on our team were surprised, Social Network Analysis can trace a direct history to the “link analysis” methods that were developed by the British Army in the 1950s as a tool to map communist insurgents in the jungles of Malaysia. The simple method of drawing lines and boxes to depict various types of roles relationships was later incorporated into the software tools that are used today by police departments  and government agencies.

I was taught link analysis methods as a young military Intelligence officer. Decades later, as a pharma industry consultant, I used the exact same methods to map connections between drug researchers and institutions. Although it led to valuable insights, manually mapping data from through hundreds of journal articles and web pages was incredibly time consuming.  It was the limitations of manual processing that motivated us to create LnxResearch in 2005 to develop the technology we have today.

In 2006, LnxResearch attended our first SNA conference, SunBelt.  Aside from a few epidemiologists from Merck, LnxResearch was the only company developing an SNA tool for commercial purposes. The other group that stood out was the several analysts from the Defense Intelligence Agency. As we bumped into the DIA team in the same breakout sessions, it was obvious that we were both working on the same problems. In the years since then, LnxResearch has developed what I’m sure is the most sophisticated SNA toolset in the life sciences — and possibly anywhere.  In comparison to most of our military counterparts, we have the advantage of massive amounts of high-quality, structured data from which we routinely map communities of 30,000-50,000 people with a very high degree of validity.  One of our challenges, in fact, is finding software that is compatible with such large datasets!  In contrast, our government peers must often work with very “dirty” data that makes analysis much more difficult and subjective.

Having seen and SNA in both these worlds, it’s obvious to me that there is much more we could learn from each other if security and confidentiality issues did not impede collaboration.  That said, I’m happy to have shed my uniform and to be creating value as a member of the Lnx Research team. I may find my job occasionally stressful but at least I’m not likely to be blown up by a roadside bomb on the way to work!  (A sincere thank-you to our government counterparts for their bravery in facing a deadly commute and other perils daily.)

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I wholeheartedly agree with Rob’s view on the topic; Lnx even published a white paper on the subject quite a while ago (see “Quantity Does Not Equal Quality In Evaluating a Scientist’s Real Importance as a Key Opinion Leader“). Our whole raison d’etre is finding consistent standards of evaluating KOLs beyond simple scoring – we pile on the analysis and apply proprietary algorithms to take it up a few more notches.  The vision is to more fully understand not just an individual’s value in terms of what they DO, but to more fully understand who they ARE and how influential they are in community and social capital. We derive key insights from their network and connected community; it’s the spaces between people that get really interesting.

A few companies understand what’s possible with this approach and are well ahead of their peers in developing KOL engagement strategies focused on finding a mix of people with good social capital. Most, however, are still counting…counting…counting…

In his one page opinion piece in The Economist, GlaxoSmithKline CEO Andre Witty gives his view on what pharma must do to stay competitive in the future.

Rarely do you see such plain speaking from a pharma CEO. But Mr. Witty paints a clear picture of the problems facing the pharma industry. He even paints a picture of what he imagines will happen. But, in my opinion, he provides little guidance on how to “do more with less and still be innovative.”

Mr. Witty suggests: “A critical dimension to determine success for the future will be getting R&D right…I foresee more innovative partnerships emerging in R&D. Pharmaceutical companies are increasingly partnering with smaller specialist firms and academia.”

Still not very clear. How do you break old habits? The natural tendency is to continue to work established relationships rather than risk building new relationships.   Even when partnering, the due diligence process usually relies on “old habits.”

Let me explain. Suppose business development has found a promising start-up company. What happens next? The due diligence. Who do you ask to help evaluate the science? You turn to trusted advisers (external experts, key opinion leaders, thought leaders) to help evaluate.  Sounds very simple, but it’s not. The advisers will all be globally recognized experts in their field. But you might be surprised if I told you they often suffer from group think. Ask the group their opinion and you’ll get the same answer.

After studying over 50 different diseases, Lnx Pharma finds scientific discovery has the same structure as big pharma. There are both “central” and “fringe” experts. The central groups tend to pursue the same research funding; the same research topics, and study the same metabolic/ disease pathways.

In short, Big Pharma and scientific research both suffer from the same problem: resistance to change.

But how do you overcome this resistance to change? One solid method is to engage people who embrace change themselves. Ask the nay-sayer. Ask the fringe expert. Get many opinions. Make sure your advisors are not all the same, in terms of backgrounds and opinions and geographies.

Having a robust method for understanding who is part of the “group think” and who is not, can ultimately help drive not just change but true innovation and new ways of doing more with less.

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• GSK’s Witty calls for an R&D renaissance (fiercebiotech.com)
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This is exactly what I saw in the cartoons of my youth.

However, nothing could be further from reality.  Thinking that there is a lone genius inventor or that innovation comes only from a profit motive does not work anymore.

Do pharma companies expect to hire a genius that will churn out innovative products by herself in a lab?  That’s not what she wants to do, and that’s not what creates true innovation.  If you want to harness innovation, you absolutely need to understand clusters, workgroups, and they way information moves.

Author Steven Johnson says, “If you look at history, innovation doesn’t come just from giving people incentives; it comes from creating environments where their ideas can connect.”

You can connect more with Steven Johnson’s ideas with his new book: Where Good Ideas Come From: The Natural History of Innovation
Or you can read a great conversation between Kevin Kelly and Steven Johnson at Wired.

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• Kevin Kelly and Steve Johnson on Where Ideas Come From (wired.com)
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Let’s analyze social networks at three different sizes: in foraging societies, the network is small (300 people or fewer), and everybody knows everybody in a detailed way. Turn the clock (or the globe) to an agrarian society where towns and even small cities form, and suddenly the network is thousands of people – an intermediate size. Next, move to the modern city where the networks include millions of people.

In the tiny group (hunter gatherers), violating a norm doesn’t really add much information to how the group perceives someone. In the medium group (farmers), where not everyone knows everyone, seeing a violation of a norm amounts to a warning sign to stay away (thus reinforcing the norm). Networks of gossip also reinforce the norms. In the large group (modern city), the norm may not even be recognized as an objective social cue, or if it is, generally most people are unaware of the violation due to the size of the network.

To quote Hanson, “The fact that norms are enforced best at an intermediate social density helps explain why higher-density farmers had stronger social norms than lower-density foragers, and yet even higher-density modern folk have reverted back to a weaker forager-like level of norm enforcement.”

Understanding the structure of scientific communities could lead to insights in norm enforcement as well. If you knew a scientific community was relatively small or relatively large, you could assume things about how norms are enforced within the community. Perhaps risk-taking and innovation happen all the time on the ends of the spectrum (small, nascent communities and large, mature ones). Whereas, the medium sized community enforces a risk-averse norm for what to research. Which group of people would you rather collaborate with?

If only there was a way to understand the size and social dynamics of a scientific community — oh, yeah, if you’re reading this, you’ve already found us, and we can do that for you.  Drop us a line.

Footnote: Hanson’s social norms are enforced via two key informal mechanisms:

1. When norms are usually followed, rare violators are often undesirable in objective ways. They may lack intelligence or self-control, for example. So people avoid violating such norms to avoid sending bad signals about themselves.
2. Meta-norms often require observers of norm violations to punish violators, such as by refusing to associate with them. This includes observers of a failure to punish a failure to punish, and so on.

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• How Social Norms Change (freakonomics.blogs.nytimes.com)

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“Measured in terms of median revenues per ex-staffer turned lobbyist, this estimate indicates that the exit of a Senator leads to approximately a $177,000 per year fall in revenues for each affiliated lobbyist….We also find evidence that ex-staffers are more likely to leave the lobbying industry after their connected Senator or Representative exits Congress.”

Now, scientific research is not Washington politics; the relationships are very different. Scientific research rests on discourse and collaboration.  But clearly when a leading scientist leaves the network, their peers are diminished until the void is filled.  How much is probably not knowable, but we all should place a higher value on our key relationships rather than just taking them for granted.

Related Posts: The Value of Political connections

Original Paper: Center for Economic Performance Discussion Paper No 993, August 2010, Revolving Door Lobbyists by Jordi Blanes i Vidal, Mirko Draca and Christian Fons-Rosen

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• Huffpost Hill – September 23rd, 2010 (huffingtonpost.com)

I applaud Carl Eliott’s recent article “The Secret Lives of Big Pharma’s ‘Thought Leaders”– I think it’s a well written article that draws in the reader and pulls them into a narrative. It’s an accessible article even for laymen to learn a bit about the mechanics of how medical experts are integrated into drug development and marketing cycles.

Unfortunately, it leads them down a solitary – and potentially biased – pathway to conclude that  the relationship between academic institutions and the business community is a bad thing.  Elliot writes, “Universities could easily clean up the problem, simply by banning or capping industry payments.” Yet he opines “that is unlikely to happen,” and further implies that it’s “because academic physicians would object “ and “many high-level university administrators have lucrative corporate relationships.”  Most damaging, he leads the reader to believe that all pharmaceutical thought leaders have secret lives pretending to be a medical experts.

Wow, is that not a “scorched earth” view? Perhaps it’s such a stark view solely aimed to create controversy for the sake of promulgating discussion.

Could you imagine a world where academic research is segregated and isolated from business? A place where business could not hire an expert to evaluate the efficacy of a new product, or ask for help putting a newly discovered invention into production? A world where a scientist could not leave academia to start a new company, or verify that her invention has a wider application?

No matter what the pharmaceutical industry calls them – Thought Leaders, Key Opinion Leaders, External Experts –  they are all External Subject Matter Experts that provide advice and services.  Under Eliott’s logic, is it not the same “influence peddling” when a government convenes and compensates through a grant or award a panel of experts to develop Disease Treatment Guidelines?  Are these panels not selling their opinion on what is appropriate?

It’s not an easy answer, and it’s not a debate that is likely to die down soon. Merely skimming through the Comments on Elliott’s posted article reveals a passionate set of opinions by academics and medical professionals. Regulations continue to be handed down to restrict abuse of influence, and pharmaceutical companies struggle with flux, caught between their needs and a muddy lens of regulatory requirements. If, in the end, academic researchers are fully cut off from their relationships with pharmaceutical companies, I believe the outcome would not be advantageous to the public at large who have come to depend on the private pharmaceutical  industry to drive innovation in treating their diseases.