Simple, Complicated, Complex and Chaotic

How does this apply to scientific research?

I had written a rant against oversimplifying issues and delegating complicated issues into the simple category. I had came across the idea of simple, complicated and complex issues while reading The Checklist Manifesto. In this book simple issues are like baking a cake. Most people can bake a cake. Next are complicated issues. Sending a rocket into outer space is an example. It can be done but it requires much more knowledge than baking a cake. Then complex issues. Raising a kid is the example. Try as we might, we still have no way of knowing how the kid will turn out.

Chaos, in this video, added one more category to my rant. When we push complicated issues into the simple category, we slip over the edge into chaos.

Does that not describe a Cargo Cult Airport? By attempting to change the shape of the coconut headphones we fail to identify the complicated system in which the headphones play a part. We begin toiling with something that will not accomplish our goals. The question becomes when will we stop wasting our time?

How might this explain the failure rate in published research? RNA interference? Resveratrol? Biotech business models? Successful men and women in unsuccessful industries?

In my own career, the Cynefin chart helps me pin down the issues I've failed to articulate up the chain of command. One project involved a peptide library that was suppose to contain a molecule that would deliver siRNA to cellular targets. It wasn't my idea. I wondered why the MD PhD who dreamed it up thought something so simple could accomplish something so complex. In the complicated category I could create the library and start screening it against specific cell lines. In the complex arena we had no way of knowing if this library even contained a delivery molecule. Our screening methods were not very complicated. We treated cells as if they were proteins. We oversimplified, went over the cliff into chaos, and lost our jobs. As the CCS, I wondered why it took so long to end this project. I didn't predict the job loss, but I wasn't opposed to leaving such a place.

What was the decision making process from our chaotic predicament? Get rid of the white lab coat workers and send the library off to more experienced scientists. Simple! This took place in 2006/2007. The CEO and CSO eventually lost their jobs as well due to poor management and the loss of two large big pharma deals. The library lived on however because there was a simple solution, give it to someone else and let them fish out the magic molecule. The project remains in a state of chaos. The question remains, when will it end?

The library was sent off to Helsinki Finland. In spite of the expertise assumed in the transfer no progress has been made. Since biotech science has no journalistic reporting on the outcome of projects like this, we rely on company press releases to tell us what happens. No news is generally bad news. This experience is akin to what many in drug discovery R&D are facing. They put themselves in an occupation that is suppose to be complicated. However, the degree to which it is complicated is not well defined. When you start a project you cannot guarantee that you will succeed. Your leaders will insist that you do. Quite often, before you cease to be employed, you will enter the realm of chaos.

With a burn rate of $274 million a day, fewer and fewer drugs being discovered, drug discovery R&D is in a state of chaos. Massive layoffs have always been a part of industry. Scientific misconduct is rampant in academia. Published papers predominantly report useless false information. The state of science is chaos. I'm not sure it was ever otherwise. What is the future? It's complex, we can't predict. Will we continue to lose money and nurture the careers of cheaters? It's complicated but he answer is yes. Will we keep funding research? Yes, it's simple. Will we put the money where it will be the most useful? Chaos.