The first few talks this morning focused primarily on policy as illuminated by science; only the third talk was pure science.

Chiechanover’s talk was on both the history and future of drug research, which he characterized in terms of three major revolutions in the last century.

The first revolution was a period of accidental discoveries in 1930s-1960s, where the discovery of a useful drug comes first, by observation of therapeutic effects, followed by chemical isolation, and only at the end (if at all), is the mechanism of action worked out. He gave the example of aspirin. Willow tree bark used for pain relief since at least Aristotle, but the active agent (salicylin) was only isolated in the 19th century by Buchner, and it was initially useless medically: it was water-insoluble and extremely bitter. Gerhard acetylated it to make it soluble near the end of the 19th century (but didn’t take advantage of it as a clinical tool), and Hoffman (who made Bayer rich) repeated the acetylation and turned it into a useful drug, using it to treat his father, who was sick with arthritis. It’s mechanism, as an inhibitor of prostaglandin synthesis, was not discovered until the late 20th century. The drug also prevents platelet aggregation, so is also being used in heart disease prevention, and its anti-inflammatory action may also make it a preventative for some cancers. However, it is a story of complete serendipity.

Another example of fortuitous discovery was Fleming’s penicillin, which was a major factor in nearly doubling human lifespan in about a century, and antibiotics in general opened up the potential for all kinds of life-saving procedures, such as surgery.

The Second revolution occurred in the 1970s-2000s, and was planned. The key innovation here is high throughput, brute force screening of large libraries of chemical compounds, which he compared to “fishing in a swamp”. We have no idea what we’ll find, but there is the expectation that some compound will be found that will have a useful effect. It is a procedure that still relies serendipity, we’ve merely elevated the chances of finding something, and of exploiting it rapidly.

The example given was the work of Akira Endo, who knew that fungi were resistant to parasites, presumably because they contained agents to suppress bacterial cell wall synthesis by inhibiting cholesterol production. His work led to the discovery of statins, which has become a $20 billion/year industry for reducing to cholesterol levels in patients with heart disease. It has also been found to reduce the probability of heart attacks in patients who only have susceptibility for heart disease, and is now being used as a preventative in healthy patients (which is always a great way to vastly increase profits). It may also help with Alzheimers and malignancies, by mechanisms not currently known.

The third revolution is ongoing. The new strategy is understanding the mechanism first, followed by targeted design. He illustrated the problem with current pharmaceuticals by pointing out that men with prostate cancer and women with breast cancer are treated with the same tools: imaging technology, histology, and chemotherapy. These are different diseases! At the same time, two women may be diagnosed with breast cancer, but one will be estrogen sensitive and the other will be estrogen insensitive, which means that an effective treatment for one may be a lethal waste of time for the other. We aren’t treating the disease specifically, but are using a one-treatment-fits-all formula for for general disease. What we need is a molecular diagnosis of tumors to fit treatment plans individually.

He thinks we are entering an era of personalized medicine. One example he gave was herceptin, which is an antibody targeted for the EGF receptor. People with a mutant, constitutively active EGF receptor are susceptible to certain kinds of cancers, so this is a very useful drug for down-regulating EGF activity. But for people with wild-type receptors, it’s completely useless. The utility of this drug relies on diagnosis by PCR of specific alleles to find candidates for drug use.

He sees great promise in cheaper whole genome sequencing as an important tool for personalized medicine, and is looking forward to the days of the thousand-dollar genome. He also advocates a systems approach: interdisciplinary action will be needed to put together useful solutions.

The problems he foresees with personalized, targeted therapies are:

Multigenic deseases. Most of these diseases and susceptibilities aren’t going to be the product of single alleles, but of multiple, interacting genes. That means answers won’t be simple, but will require an understanding of combinatorial effects.

Malignancies are typically the product of genomic instability. They are moving targets.

Complications of human experimentation. We can’t just pin down patients and run them through a series of carefully controlled trials, so working out the effective details of personalized medicine are going to be hard.

Lack of good animal models. A mouse is not a human. We can’t do the necessary experiments on people, but at the same time we can’t entirely trust the results of animal experiments.

Costs and legal liabilities. Medicine is done for profit. How do you pay for tools that work on tiny percentages of the population?

Bioethical problems. Information has repercussions. How do individuals cope with the knowledge that they might have, for instance, elevated susceptibility to breast cancer? How will it affect their relationships with family and spouses (or prospective mates)?

This was a good talk, but very, very general. I’m hoping we get some more scientific meat in other talks.

By the way, the way the meetings are run at Lindau is a little different than I’m used to — there is no Q&A afterwards! However, what they do instead is schedule small group meetings with the Nobelist speakers and the “Young Investigator” group of attendees, to which people here as press (like me!) are not invited, which is too bad from my point of view, but is probably a very good way to give people with more direct interests good access to the speaker.