Over the last year or so, there has been an inordinate amount of press questioning the safety and tolerability of various drugs, whether in clinical trials or on the market. A lot of the concerns are quite valid and both regulatory agencies and the pharmaceutical industry are taking steps to improve the track record.
The recent hospitalization of people participating in a British clinical trial for TGN 412, as well as the rampant lawsuits against the makers of products like Vioxx, have shown the industry that it clearly has a lot of work ahead of it when it comes to maximizing the safety of people taking its drugs. While it has been widely acknowledged that animal studies will only take science so far in understanding a new drug's behavior, I wonder if we still don't put too much stock in animal models as a gauge of human response.
Partly to address this issue, companies like Entelos are scouring the literature to build computational models of human systems. By testing virtual drugs on virtual patients, it is hoped that we can avoid the nasty surprises that sometimes arise. With all due respect to Entelos and its ilk, however, I don't know how confident I am that the data sets are large enough or complete enough yet to get fully reliable results. That being said, I applaud and support the efforts of these companies and wish them well.
As we've reported recently, other groups are taking the problem one step further back in the discovery and development chain, focusing on what I might call QSTR or quantitative structure-toxicity relationships. (BTW, if this is a novel usage, please feel free to run with it.) Instead of modeling biological responses, these scientists are trying to correlate chemical constituents of known and novel drugs to identify potential toxicity issues before anybody even does the chemical workup. Again, while I applaud the effort, I question the quantity and quality of the existing data.
The reality facing drug companies is that they can only afford to test a new drug on just so many people before presenting the data to regulators. The clinical component of drug discovery and development already accounts for the largest share of costs to put a product on the shelf. Increasing the hoops through which companies must jump will likely only result in new drugs coming out more slowly and more expensively. And both of these scenarios are anathema to an ageing Western population that is addicted to feeling younger than they really are.
But perhaps the biggest challenge facing everyone involved in making drugs safer is that no amount of modeling, no amount of pharmacogenomic profiling, no amount of clinical trials can ever prepare drug companies, regulatory agencies, and physicians for the fact that some people like grapefruit juice.
In the May issue of the American Journal of Clinical Nutrition, researchers at the University of North Carolina at Chapel Hill published a report suggesting that furanocoumarins from grapefruit juice interfere with specific intestinal enzymes (CYP3A) that normally degrade various drugs, triggering excessive uptake of certain blood pressure and cholesterol-lowering drugs. Grapefruit juice has been shown elsewhere to have similar impacts on drug ADME properties, while the proanthocyanidins of cranberry juice may facilitate antimicrobial treatments through the inhibition of bacterial adhesion in places like the urinary tract.
All this to say that secondary and tertiary factors like morning beverage preferences cannot be realistically incorporated as parameters during a typical clinical trial and are therefore often lost in the noise that arises in data accumulation.
At best, these parameters may be identified during Phase IV follow-up studies, but I would expect that this would only occur if the impact is dramatic, by which time, the social and commercial damage has been done.