probably won't work. There's too many variables to make the computer model accurate enough. The computer model will be as accurate or inaccurate as the assumptions built into it. Hopefully, it will be calibrated using past unbiased drug trials data. However, corporations are known for skimping on computer code testing. Garbage In, Garbage Out. Consider this a baby step. By the way, innovation in the pharmaceutical industry means that the CEO or President heard about the "new" drug in the hallway. Academic biomedical research is where most innovation comes from since academics risk only losing their time on an idea. Pharmaceutical firms apply the successful academic ideas by scaling up production or by buying pharmaceutical firms started by academics who can't afford the expense of clinical trials. This is one reason why pharmaceutical biotechnology didn't really blossom in the early 1990's. One could say that the early 1990's biotech bubble was purely a speculative bubble created by Wall Street and VCs. Out of 1500 biotech startups, I think maybe 15 had viable products. Biotech wasn't anywhere near like Silicon Valley in maturity. Consider also the financial implications of curing someone with a single or short term treatment versus keeping someone alive with a chronic condition via a lifelong medication or treatment. Which option gives you the steadier income over time? One has to have a disease or condition which everyone gets eventually to make money in the first case. If you are a small percentage of the population with a disease or chronic condition, like HIV, bipolar disorder, etc. the second case applies. I'm not saying that this is always a conscious choice by executives, but this is how the incentives are structured.
Labels: baby steps