August 18, 2014

Should every drug have to pass a clinical trial?

If a pharmaceutical company wants to sell a drug, it first has to prove that it works and is safe by doing a double-blind controlled trial. Everything else is quackery.

At least that is what I used to think, but now I am not so sure any more. A major reason for my new-found uncertainty has been Peter W. Huber's book The Cure in the Code. Huber is a senior fellow of the Manhattan Institute, a free market think tank. Whilst his book is political, it raises points that should transcend the political divide. His central aim is to show that the top-down drug licensing process, as it is currently implemented in the United States and other developed countries, is not in the long-term interest of patients.

Consider the rare diseases that we study at the Sanger Institute, where I am a postdoc. In many cases, they are caused by a single mutation disrupting a single gene. Because the mutation is rare, not enough people have the disease to make it profitable for anyone to invest in developing a drug.

Nevertheless, sometimes doctors are able to repurpose a drug that has originally been developed for a different disease. For example, if the causal mutation disrupts a gene in a particular biochemical pathway, the doctor may know of a drug that upregulates the expression of another gene in the same pathway, therefore compensating for the mutated gene. That is great when there is a drug that can be repurposed, which in most cases there is not.

This issue is not limited to rare disorders. Complex diseases such as autism or diabetes have a large genetic component, but rather than a single causal variant there are tens or even hundreds. Each patient has a different combination of variants, and it is therefore unlikely that there will be a single drug that works for everyone. This makes a personalised medicine approach necessary, where the drugs that are prescribed are adjusted based on the patient's genotype. As with rare diseases, this means that patients with less common genotypes may lose out because there are not enough of them to warrant the development of a new drug, and because no drug that has been licensed for another disease is likely to help.

The higher the level of proof that is required before a drug can be sold, the lower the number of drugs that pass this threshold will be. Always requiring the highest level of proof may seem like the safest option, but is not necessarily in the public's interest if it means that many drugs will ultimately be unavailable. There is legislation such as the US Orphan drug act and a number of accelerated approval rules, but they only partly address the problem. There are still plenty of examples of drugs that may work in a subset of patients, or that may in the future be repurposed, but that are killed off in the licencing process and are therefore not available to anyone.

What is to be done? Creating legislation that allows the use of any compound whatsoever for the purpose of treating people with rare diseases or rare genetic variants could be one option. Of course, such a laissez-faire approach to drug licencing would be controversial and could encourage unscrupulous practices.

Right now, it is unclear to me what the balance between the two extremes of complete permissiveness and complete top-down control of drug licensing should be, but I doubt it is the status quo. I would welcome any views readers of this post may have.

August 3, 2014

How important is health care system quality?

A few weeks ago, I came across an article comparing the health care systems of eleven developed countries. This made me wonder how much health care system quality impacts physical wellbeing, for which I used life expectancy as a proxy. I was expecting a strong correlation between the two, but in fact health care system quality doesn't seem to be that important.

Healthcare system ranking (from best to worst) and life expectancy of eleven Western countries. The correlation (r) is -0.32 (solid line), or 0.06 when excluding the United States as an outlier (dotted line). In either case, the 95% confidence interval of the correlation spans zero, meaning that the data does not support any relationship between the two variables
Health warning: Do not overinterpret such a small dataset. This is me messing around with a few numbers I found on the internet. I am not a health economist.