This comment was originally posted in response to an article by David Shaywitz at Forbes.  http://www.forbes.com/sites/davidshaywitz/2013/05/10/whats-holding-back-cures-our-collective-ignorance-and-no-not-a-pharma-conspiracy/  I hope to eventually expand on these ideas in a later piece.

Thanks for the interesting take on the pharmaceutical industry and the problems of finding truly new and innovative drugs. The reasons you put forward are, I think, a large part of the problem. Biology is hard and we’re discovering just how hard it really is. Just as an example, something like ENCODE comes out and one learns about the vast amount of transcription going on in the genome across the many different cell types profiled, and one realizes there is no clear way to make sense of all of it, or even really know how much of it actually means something and how much of it is noise. As other examples of how hard it can be, some of the other commentors have pointed out the inherent unpredictability of biology, including the lack of translation from in vivo, controlled results in a dish to organismal biology, and also the complexity of a system with billions of moving parts.

While I’m still optimistic about Systems Biology approaches, I don’t have much faith in top down engineering models employing circuit diagrams and differential equations. Systems level measurements have shown how much variability there is among individuals in things like transcripts, proteins, metabolic rate, etc. And yet at the same time organisms generally function despite undergoing what amounts to a complete rewiring every generation due to genetic recombination and gamete fusion. It may be that a better understanding might come from study not of the specifics but of the generalities of systems that allow them to remain stable despite the diversity of all the parts. Trying to comprehend how evolution has solved the problem of balancing stability with variation.

Another aspect of the problem facing pharma today I think has to do with being victims of our own success. Many of the biological approaches of the last century, including the phenotypic screening mentioned earlier, helped illuminate many of the major pathways and a lot of the key regulators in human biology. That wave of information helped inform the highly successful drugs developed in the 80s and 90s. However, once you have a decent drug, it’s difficult to go one better. Improving on a statin is hard. Anything obvious, with a big effect on biology (and, it must be noted, big side effects) has probably already been found.

I’m reminded of the metaphor of the adaptive landscape from evolutionary biology. The concept is that a given phenotype of a species occupies some position on a landscape consisting of peaks and valleys, with peaks representing local maxima for fitness, and valleys representing poor fitness. In evolution, favorable mutations allow some phenotypes to move up the side of a peak, approaching ideal fitness. I sometimes think of drugs today as occupying a similar fitness landscape with peaks representing diseases and many of our existing drugs positioned near their respective therapeutic peaks. Once you start moving up a given peak, it’s progressively harder to make a change that will move you closer to the top as opposed to sideways or backwards. So you get Zaltrap and Avastin.

The way out is to change the landscape itself. To stretch a tortured analogy further, your comment, David, about possible new therapeutic modalities could be likened to the development of the first feathered, gliding dinosaur. Suddenly the adaptive landscape changes, shuffling the peaks and valleys so that they can now be exploited in different ways. Maybe a radically different kind of drug, like siRNAs once were thought to be, could completely revamp the drug development space. Fundamental insights into biology might do the same.

Disclaimer: all opinions are my own and do not necessarily reflect those of Novo Nordisk.