MUSINGS: Pretty boring stuff, I'm afraid

 

The late '60s look.  Deep Thoughts, Happy Thoughts
Also, fashionably short skirts

I am at Fred Hutch, reading things I only partially understand, and occasionally going to a window and admiring the sunshine and springtime blossoming visible outside.  I should be home, tending to my garden – but I’m not.  I sure hope I’m doing some good here.

Some of the things I am reading (and partially understanding) are research proposals.  In nearly every instance my eyes glaze over when I get to the “methods” sections, but part of the rest I understand and can comment on.   Here are some comments.

Cancer research is damned expensive.  Many of the gene-sequencing and “proteomics”  or “metabolomics” surveys I read about must be conducted on machines that cost roughly the equivalent of a battleship.  In my former line of work – paleomagnetism – measurements are made on a “cryogenic magnetometer”, after treatmens using things like a “non-magnetic oven” and/or an “alternating field demagnetizer”.   All this is conducted in a special room which has the earth’s magnetic field reduced to near-zero intensity.  All of this sounds expensive and, in a way, it is.  When I was active, during the late Pliocene, I could never aspire to such extravagant machinery.  It was only with the coming of Bernie Housen that we could afford some of this stuff.  We now have one of the best paleomagnetism labs on the West Coast – the PNWPL.  (I use this acronym to get back at the biologists who may read this blog – in the articles I have been reading every fourth word is an acronym, and not all of them are defined.  PNWPL stands for Pacific Northwest Paleomagnetism Laboratory.)  I suspect that the total cost of the equipment housed in the PNWPL would nearly pay the sales tax on some of the gadgets we have on the top floor of this building. 

Cancer research is highly inductive.  This contrasts fairly sharply with what I used to do.  (Most geologists proceed this way.)  Having noticed something geologically strange, I would sit down and ponder on possible explanations  for its strangeness.  Having done that, I would then ask myself:  “If reason A is true, what would be some other geological consequences – that is, if A is right, then shouldn’t something else have happened?”  Then I’d go out and check to see if it had. If it hadn’t, I’d go on to possibly explanation B.   I call that the semi-deductive approach to science.  Actually, that’s the way you are supposed to do it.  Probably most geologists have a preferred explanation in mind from the beginning, and they will fight hard for its verification.  Only if A really, absolutely doesn’t work will you turn to B. 

The inductive method works more like this.  You identify a “problem”.  (As a problem, cancer will do.)  Possibly guided by your knowledge of the biology of cancer, you identify as many suspicious molecules as possible, and then determine if they actually are extra-abundant in cancerous tissue.  This requires massive studies, requiring the machines aforementioned.  Having thus identified the suspicious molecules you next can: (1) use them for biomarkers – warning signals – of cancer; (2) begin to study what they do so you can figure out a way to stop them from doing it.  I have a preference for this later stage of cancer research, because it may lead eventually to the Holy Grail: prevention and/or absolute cure.

Cancer research relies on statistics to an enormous degree.  To do inductive research properly one needs very large data sets.  Enormous data sets are the playground of statisticians.  They give us  rules by which such sets are interpreted.  They tell us with what confidence one can make certain assertions based on the data set.   They help us to design empirical experiments that are likely to yield interpretable results.  They keep us humble by using terms like “parametric empirical Bayesian longitudinal algorithm.”  When I die, I want to be reborn a statistician. 

Many enormous trials cost so much money that only a drug company can afford them.  A Phase 3 trial may have thousands of participants.  If each one is to be given a course of medication costing $1000, then very quickly the cost rises above $10⁶.  Even in today’s economy that’s a load of money.  However, if a drug company has a drug that it is fairly certain will work, it might gladly fork over the wherewithall – and rebuild the investigator’s lab on the side.  I suspect that if Pfeizer has funded your research, built you a lab, and perhaps even paid part of your salary, it would be damned hard to tell them that their drug is crap.  After all, even scientists are human.

I have  lots more to say, but I have work to do.