Back to the future

Hundreds of years ago, medical scientists were broad-based and cross-disciplinary. But in the mid-twentieth century, they became specialized. Postgraduates spent years studying single genes, proteins or molecules. Industry demanded scientists who identified themselves as chemists, biologists, cellular biologists or biochemists.

In the past decade, the pendulum has swung the other way. Automation, robots and high-throughput screening, combined with genomics, created a semi-industrialization of drug discovery — and enormous quantities of data. Disciplines such as chemical and biological informatics arose to deal with the information flood.

With these disciplines came the rebirth of an essential skill set. Industry again needs cross-disciplinary scientists. Today's professionals figure out how basic science and advanced technology fit together. The ball is in the court of scientists who can assimilate data from a variety of areas. We are moving towards systems biology and biosimulation to understand the complexity of human health.

Our ability to generate data has outstripped our capacity to study them. The challenge is how to use the data we generate. We need to learn ways to bring technologies to bear in a way that manages risk and reduces the cost of drug discovery. How do we translate opportunity to sort out the ineffectual compounds and push forward the winners? It is the balance of science and advanced technology that will determine where we find our answers.

Just a short while ago, if you could clone and sequence that was a great skill set to be able to put on your CV. Today, the scope of what the scientist needs to bring to the table has broadened. A solid molecular background will serve you well but you need to take the broader view, be able to work in teams, and collaborate with downstream partners.

To prepare for tomorrow, the bar will be set even higher. In another ten years we will see an increase in computer-aided drug-design applications of structural biology and protein engineering. This will be necessary because animal models are very expensive. Those who can adapt to this new environment will not only be able to forward their own careers, but at the same time move medical research closer to meeting our medical needs.