Disrupting Pharma: Personal medicine, maybe too personal?

One of the chapters in "The Innovators Prescription" by Clayton Christensen et al. is about how pharmaceutical research is going to work in the future.
One good thing about the book is that the authors clearly distinguish between what they call "precision medicine" and the current buzzword du jour "personalized medicine". For them precision medicine is about using technology to go from intuition-based medicine to a clearly analytical and data driven approach, where diagnostics, biomarkers and such are going to play a major role, and not the individual experience and, well, intuition of the MD you are talking to.

Instead of developing a single "block buster" drug that is going to do a little for a whole lot of people, they believe that the drugs of the future are going to be targeted on sub-populations of people for which the impact is going to be much larger, since the drug is going to affect pathways with clear clinical significance for that sub-population, i.e. a big bang for a smaller group of people than the ho-hum effect of the block buster.
If you have a drug that works well for a certain pathway, all you need is a diagnostic test to check if that particular pathway is the right one to target and you can be pretty sure the drug is going to work (the precision medicine part).

Question is: How do you identify the targets and the sub-population initially?
This is where the term "personalized medicine" and genotyping are typically used. The thinking is that all you need to do is to look at the genes of patients, and the variations therein, and presto, the differences tell you for which pathway to develop a drug for.

There is one little problem with this: The emerging research indicates that the sub-populations might be smaller than you think, and the big bang might also not be what everybody hoped for.

The story goes like this:
When researchers currently look at variations in the genome, they look at single changes in the sequence, a so-called SNP. You take a whole bunch of people, some healthy, others suffering from some ailment you want to investigate, and you look at known SNPs in the two populations, trying to find disease relevant SNPs.
In the ideal case, one of the changes occurs only in the sick population, but not in the healthy.

In reality, the ideal case never happens.
The more experience researchers get in running these studies, the more it looks like that the sub-populations are very small indeed, or alternatively, if you find something, a lot of people that have that SNP are perfectly fine.
Even for diseases like Schizophrenia, where it is known that genetic predisposition is increasing the likelihood of suffering from it dramatically, the most frequently associated SNPs identified so far can only explain a few percent of the Schizophrenia cases.

There might be a good explanation for this: If a large percentage of a population suffers from a disease that affects their chances of survival, over time evolutionary pressure would eliminate that sub-population, or would lead to other changes in the genome that would make an individual more robust for the effects of that single change.
So after a while of evolution running its course, what is left are disease-related genetic changes in the gpopulation that either occur only rarely (affect only a very small portion of people), or are not very significant (people have that SNP, but some other pathway can compensate for that change and the SNP in itself can not really help distinguish between the sick and the healthy).

This might explain why for some relatively new diseases, like HIV, the analysis of SNPs works well, but for "older" diseases, like hypertension, the analysis of SNPs has not really worked that well, since evolution had a chance to take care of this.

Since pretty much every pharma company on the planet seems to be jumping on the "personal medicine" bandwagon, it might be a challenge to come up with a business model that would work for a truly, very personal medicine.

References:

Need, A., Ge, D., Weale, M., Maia, J., Feng, S., Heinzen, E., Shianna, K., Yoon, W., Kasperavičiūtė, D., Gennarelli, M., Strittmatter, W., Bonvicini, C., Rossi, G., Jayathilake, K., Cola, P., McEvoy, J., Keefe, R., Fisher, E., St. Jean, P., Giegling, I., Hartmann, A., Möller, H., Ruppert, A., Fraser, G., Crombie, C., Middleton, L., St. Clair, D., Roses, A., Muglia, P., Francks, C., Rujescu, D., Meltzer, H., & Goldstein, D. (2009). A Genome-Wide Investigation of SNPs and CNVs in Schizophrenia PLoS Genetics, 5 (2) DOI: 10.1371/journal.pgen.1000373

McCarthy, M., Abecasis, G., Cardon, L., Goldstein, D., Little, J., Ioannidis, J., & Hirschhorn, J. (2008). Genome-wide association studies for complex traits: consensus, uncertainty and challenges Nature Reviews Genetics, 9 (5), 356-369 DOI: 10.1038/nrg2344

GIBSON, G., & GOLDSTEIN, D. (2007). Human Genetics: The Hidden Text of Genome-wide Associations Current Biology, 17 (21) DOI: 10.1016/j.cub.2007.08.044

Zapping malaria

The WSJ and The Economist already reported on this one. But better late than never, I just can't resist posting this:

Intellectual Ventures, a company founded by ex-Microsoft guys, is working on a new way to limit the spread of malaria by taking aim at the mosquitoes that spread the disease - literally.

The company is working on something that sounds like a parody of Reagan's "Star Wars" missile defense initiative: A high-tech "fence" that can distinguish mosquitoes from other things (like, for example, humans) by the sounds they make and kills incoming mosquitoes mid-flight using lasers.
Or, as the company puts it so eloquently on one of their web pages: "Shooting mosquitoes with frickin' lasers"

It is definitely an entertaining idea. But, most of the spread of malaria affects regions where people have trouble affording insecticide-treated bed nets costing less than 10$, so I am not sure how big the market for this is.

Disrupting healthcare for good

I recently finished the book "The Innovator's Prescription" by Christensen, Grossman, and Hwang.
For those who might not know this, Clayton Christensen is the author of the classic book "The Innovators Dilemma" and coined the term "disruptive technology", explaining how even well run companies can disappear quickly if they miss the threat from cheaper and rapidly evolving technologies.
For this book, Christensen, a Harvard Business School Professor, has teamed up with two MDs, Grossman and Hwang, and takes a stab at healthcare.

This time around it is not about warning managers of companies within our current healthcare system that they might go the way of the steam engine manufacturer. Just the opposite, the aim is to figure out how the current healthcare system will meet the same fate the steam engine did: to be replaced with something much more efficient and cheaper.

The problem with our current healthcare system is that there are no free-market forces at play, and the whole thing is something a central planner from the former USSR might be proud of, or rather not be proud of. It is so bad.

The strength of the book is the analysis of the current situation from an economic/business viewpoint. A good number of the proposed solutions are driven by technology, which has its weak points in some places. The problems of the biggest pieces of the current mess are analyzed: hospitals, medical education, pharma companies, regulators, insurance companies.

Overall, it is a thought-provoking book, and having read this analysis, it is surprising how little of the current "healthcare is an economic problem" discussion is based on (good) economic arguments and business thinking.

I will have some more posts about this in the future.

As a side note: "The Innovators Dilemma" was also mostly analysis. However, Christensen made one prediction in the book: That electric cars will disrupt the automobile industry.
The book was published the same year the Toyota Prius came on the market in Japan, 1997, and the Prius would not be introduced to other markets until 2001.

Did anybody at GM or Chrysler read the book?

A shift at Pfizer

There is an early access article at Drug Discovery Today (via ScienceDirect) titled "New working paradigms in research laboratories" by two researchers at Pfizer.
There have been all kinds of news and rumors about reorgs at Pfizer going around for quite some time now (check for example here and other posts at pipeline.corante.com).
Maybe this article might offer some clue.

So, according to this article, what is Pfizer up to?

First, the article is only about the in-vitro screening part of the business, and without stating so, I think we are really talking high-throuput screening (HTS) here.

And the new paradigm: working shifts.

One of the perpetual problems of large pharmaceutical companies is to find a balance between doing basic research, where a certain amount of chaos, err, I mean creativity is needed, and running a well-oiled industrial process where you put money in at one end, and pills that earn you even more money pop out at the other end. In a regular, predictable manner.

HTS is probably more on the industrial end of the spectrum of the various activities that are going on in a pharmaceutical company. So looking at this from a resource management and allocation point of view makes some sense. Working in shifts probably really does allow to run more screens and utilize all those expensive robots better.

But, reading through the article, there are quite a few changes that were made to enable the shift work (which is two shifts, from 6am to 2pm and 1pm to 9pm, alternating every week):
- unhindered access to equipment
- ability to focus without the distraction of meetings
- hand picking the staff
- new processes which were trialled in the team

One can only wonder how much of the increase in productivity really came from working in shifts and how much came from these other four points.

Item number 2 is a winner in my book.

Burning biomass better than converting it to biofuel?

Well, it seems to be more efficient.

This article and the companion editorial in Science magazine compare the efficiency of powering cars using biomass converted to ethanol in combustion engines versus burning the biomass to generate electricity that is then used to power a plug-in electric car.

Their conclusion: With current technology it is far more efficient to burn the biomass and convert it into electricity. For biomass-to-ethanol less than 10% of the original energy stored in biomass is available to power the vehicle. For biomass-to-electricity the numbers go up to 20-25%.
The study looks at conversion efficiency from biomass to transportation only. What is missing is things like environmental impact of old batteries, but also things like using the excess heat for residential heating, which is used quite successfully in Europe.

Also, and importantly, a plug-in electric vehicle would allow to decouple the energy source from the intended use of the energy. Electricity from biomass, sun, wind, coal, atom - everything would feed into the same grid and end up being usable for transportation (or something else).

The authors estimate that the current grid is sufficient to charge up to 70 million vehicles overnight, but fueling this number of cars with 60 billion gallons of biofuels would require additional infrastructure and would require much more land being dedicated to biofuels. Using biomass-to-electricity to power that same number of cars would require only little additional farmland.

Now, burning things has gotten a bad reputation lately, so remember that the only CO₂ released would be what was captured by the plants when they grew. If you start to sequester the carbon-dioxide produced during burning, you would in effect remove CO₂ from the atmosphere.

So, considering current technology, where would you put your money?

Discomfortingly, the current focus at DOE and USDA seems to be on biofuels. In 2008 an estimated $9 billion was dedicated to investments and tax advantages in that area, which could go up to $30 billion under current legislature (these numbers are from the editorial).