Monday, July 15, 2013

Business/Science Dichotomy

If my blogs lately and in the near future are a bit lacking/sound somewhat robotic, you must forgive me. I’ve been working recently on many, many essays for secondary medical school applications and my creativity has about run dry.


I learn a lot through hands-on experience by shadowing folks around the building, and asking questions whenever they arise. Yet I seem to thoroughly enjoy the “car talks” that my mentor and I have when we are motoring together from one meeting to another.

As an ex-Ivy league professor, he may harbor a tinge of bitterness toward the general attitudes of his past students. With an extreme focus on securing certain letter grades versus gaining knowledge about statistics, he has told me some great tales about being bullied, cursed, and threatened because a student refused to attend class, didn’t do any work, or a plethora of other unreasonable excuses.

“You know those kids who get straight 75’s throughout high school and college? They are still somewhere out there. They have jobs too- and it is probably not on the scientific side of the pharmaceutical industry.” While he was not assuming that scientists are all high-achieving geniuses, he was making a point about the dichotomy between scientific and business rationale when making decisions within a pharmaceutical company.

“Morons with molecules!” he says. The problem is that businessmen with no scientific background do not make the best decisions regarding drug development. Their bottom line is obviously going to be related to a profit margin. Likewise, scientists with no business knowledge are not fit to make executive decisions, as they would likely approve development of a novel, $300 million asthma medication due to its innovative pharmacokinetic properties rather than consider the fact that it would cost so much and only serve a very small subset of the population with asthma.

The power of having both a scientific foundation and business education cannot be understated for many industries. I suppose I did not consider this before- as a biology student, some of the economic data I’m encountering is befuddling and forces me to agreeably disagree with decisions made about clinical development and marketing propositions. On the other hand, it confirms the value of my presence here as this financial and business expertise is something I likely will not encounter again in the near future while steeped in medical school.

Just as science and business are necessary backgrounds for powerhouse pharmaceutical decision making, they are also necessary for diligent policy making. Hopefully I can continue to increase my awareness of health economics in the future to prepare me for this public health role.

As a random note, I've been wondering about the difference between a systematic review and a meta analysis for awhile....   A systematic review is a thorough, comprehensive, and explicit way of interrogating the medical literature. It typically involves several steps, including (1) asking an answerable question (often the most difficult step), (2) identifying one or more databases to search, (3) developing an explicit search strategy, (4) selecting titles, abstracts, and manuscripts based on explicit inclusion and exclusion criteria, and (5) abstracting data in a standardized format.

A "meta-analysis" is a statistical approach to combine the data derived from a systematic-review. Therefore, every meta-analysis should be based on an underlying systematic review, but not every systematic review leads to a meta-analysis.

Sunday, July 7, 2013

Down the Shore or Up the Cape?

After several days spent with my lovely roommate and hilarious family members checking out the sites in D.C., VA, and MD, I've reached the near-end of the 4th of July break from Novo. It's funny that when I talk about it in casual conversation, I tend to say, "Yeah, I have to go back to work tomorrow..." in that typical back-to-school groan, as if I dread waking up to go in on Monday. But each time I do this, I catch myself, realizing that I'm actually quite excited to go in to work and I'll probably fight myself to get to work at 9 a.m. and leave by 5 p.m. instead of going in at 7 a.m. when the building opens and staying until 6 p.m. closing.

The Dossier project should start to dominate my agenda by the end of this coming week. Until then, Neil has graciously taken the time to nitpick through some published trial data with me so I know what to look out for with the Dossier literature search results. Basically, we kick this project off by skimming through hundreds of abstracts and flagging them for significance. Neil is teaching me how to determine if a study is airtight, whether its subject pool is too narrow, if the testing methods are consistent and leave little room for random variables to affect the outcomes, etc.

I realize this might sound quite dry thus far. While it may seem boring to the reader, I assure you that I could not be in a better place! This entire department is completely out of my typical element- as a biology major used to taking more abstract science courses based on pictures of cells and qualitative data, now I am faced with people who work almost entirely in the quantitative realm. I'm forced to think in numbers now and test the hard data using p values, confidence intervals, etc and then consider its economic outcomes (Will payers buy into this drug? Does it compete well with the other drugs in its class? Will Novo make a profit?) as well.