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DBL%20Hendrix%20small.png College chemistry, 1983

Derek Lowe The 2002 Model

Dbl%20new%20portrait%20B%26W.png After 10 years of blogging. . .

Derek Lowe, an Arkansan by birth, got his BA from Hendrix College and his PhD in organic chemistry from Duke before spending time in Germany on a Humboldt Fellowship on his post-doc. He's worked for several major pharmaceutical companies since 1989 on drug discovery projects against schizophrenia, Alzheimer's, diabetes, osteoporosis and other diseases. To contact Derek email him directly: Twitter: Dereklowe

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August 5, 2004

The State of the State of the Art

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Posted by Derek

This fall will mark my fifteenth year in the drug industry. Looking back at what things were like in late 1989, there's one thing that I find striking above all the others: that very little has changed.

Fifteen years is a pretty long time in the sciences. In a field like molecular biology it's a ridiculous length of time, but their clocks will slow down on them, too: the previous span (from 1974 to 1989) was a much bigger leap for them than the last fifteen years have been. In a mature field like chemistry we don't have such dramatic interludes, but you do see the changes piling up.

But when I started doing drug discovery, it worked like this: you got a chemical lead by random screening, and a bunch of chemists started in on it, changing the structure around to see if they could improve its activity in a set of in vitro assays. The better compounds went into a rodent model of efficacy, and you checked the blood levels of compound to get an idea of its pharmacokinetics. Once you met all the criteria you'd set, you started high-dose toxicology on selected compound in more rodents, then larger animals. And if things held up, you declared a compound to be the winner, and passed it on to the clinical development team (the scale-up chemists had already been having a look at it, to make sure that they could supply enough for longer tox and human trials.)

Sound familiar? That's exactly how we do it now, most of the time. Oh, the compound you started with might have come from a combinatorial chemistry library this time (although odds are that it didn't!) And you might have some help from the molecular modeling folks along the way (but there are plenty of projects where they can't help, and plenty where they only think they can - no offense, guys.) You'll probably have a more assembly-line approach to getting some quick-and-dirty animal dosing for blood levels, too.

But these are minor changes. Are we ever going to do things really differently? Routinely start with an in silico lead compound, say? Build our compounds by mix-and-match fragment assembly instead? Find a way to predict pharmacokinetics, at least a little bit, so we don't have to run everything through mice? Get some serious clues about toxicology, so we can get off the mouse-rat-dog treadmill on the way to human trials?

The cockpit looks pretty much the same as it has for years. All we have are fancier propellers and slightly more responsive rudders. No one has invented the jet engine yet, and I wonder when someone will.

Comments (4) + TrackBacks (0) | Category: Drug Industry History


1. John Johnson on August 6, 2004 9:58 AM writes...

On the other hand, the drug development landscape is changing a lot, but that is more due to changes in the regulatory landscape rather than changes in science. You still have to do pharmokinetic and tolerability studies, dose-ranging studies, and two independent confirmatory trials (unless you aim for one of the accelerated development cycles for orphaned drugs or unmet medical needs). The FDA (in cooperation with other regulatory agencies) are requiring hepatotoxicity (liver) and QTc elongation studies now and perhaps carcinogenicity.

In a sense, we're waiting for a jet engine also in that we need to be able to meet the demands of a (justifiably) conservative regulatory body within a reasonable time and cost. And I think it's going to have to come via breakthroughs in science and statistics (science so that we can get better estimates earlier, statistics so that we can take better advantage of the early information).

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2. Eric M on August 7, 2004 4:48 AM writes...

Here are my top three badly-informed guestimates:

Most likely in teh short ot medium term are microfluidic full body simulators - ones with tissue form all the different organs, capturing more subtle effects than in vitro alone. There should be a nice productivity boost over starting with rats, and multi species versions are an option. Automation will be a driver here.

Next likely will be genetic profiling of clinical test participants. That should allow some sense to be made of statistaclly unreliabe subgroups form clinical trials. Some progress is being made here, something recently got approved specifically for African-Americans (hypertension?). Without general testing for patients, regulatory reform is probably needed as full trials figure to be too expensive.

Shading towards a pipedream end of the spectrum, Id put transdermal dosing, esp for biomolecules. That probably would open up compuound space a bit, plus things like time varies dosing ect. Hopefully 'take two asprin and call me in the morning' will be changed to 'slap a patch on your ass and call me next week.'

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3. hound on August 7, 2004 6:40 PM writes...

I think many of the sciences, like environmental( my background) but especially the health sciences are deficient in the application of statistics, resulting in a largely qualitative and subjective product. The relatively crude application of risk assessment and epidemiology also appear to me to present bottlenecks in health science advancement.
It does seem that PCR was the biggest thing to come around in decades.
the degree of pharmacokinetic sophistication needs to be advanced.

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4. John Johnson on August 8, 2004 10:34 PM writes...

hound -

I'm curious to know what you mean by health sciences being deficient in the application of statistics. (I might agree with you.) On the clinical drug development side, the (bio)statistician is playing more of a central role, but that's usually later in drug development (Phase III and often Phase II also). I'm finding when I try to help design Phase II studies that a lot of information is sorely lacking, and we are really more guesstimating things I think we ought to have a better handle on (e.g. some ballpark figure, or even order of magnitude in some cases, of treatment effect). Of course, if this information is lacking in the planning of pivotal trials, the drug development program is in jeopardy. Statisticians are getting involved very early now so we can give guidance on what information we need to gather to design effective dose-ranging designs.

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