The biotech industry is a major force in the worldwide creation of a new health economy, with sector revenues mushrooming in value, growing by more than $30 billion in the last decade¹.

With more than 300 drug products and vaccines currently in clinical trials, biotechnology is responsible for hundreds of thousands of medical diagnostic tests, making it one of the most research-intensive industries in the world.

Moving away from medicine, the industry is also involved in foods, environmental issues, industrial applications and DNA fingerprinting. In fact, the depth of its reach is widening annually, with the total value of publicly-traded biotech companies in the US reflecting this and hitting $311 billion as of early April 2005.

Particularly in pharmaceuticals, the application of technology represents a new era in the production of medical drugs, with the potential to change the industry from a market of mass-production to a more focused and targeted service.

With the vast amounts of data involved, it would be easy for businesses to get bogged down in their own research. However, recent advances in technology are allowing companies to streamline and automate their studies, meaning research can be optimized and unnecessary analysis avoided.

The biotechnology industry is being revolutionized as new techniques, such as data mining, allow companies to focus on gathering and monitoring new information. By adopting this approach, businesses are able to gain a far more accurate overview of data, discover possible trends and deliver a more productive service.

While the market is quick to adopt this new technology, the vast benefits to bio-technicians mean it’s about time to take advantage of the possibilities. After all, as the industry grows, so does the amount of research and data it churns out.

As the market starts to expand and realize the wealth of information it has at its fingertips, it needs to find a way to reach the full potential of just what it has to offer.

Using predictive analytics allows these businesses to discover patterns, avoid potential pitfalls in the development process and predict consequences in the research and manufacturing of a product. As a result, it can deliver in a gain of one to two years in the production of an up-an-coming medicine. In drug development, this can translate into millions of dollars of saved costs.

By using advanced analysis techniques, predictive analytics allows biotech companies to analyze their data, combining information on past circumstances, present events and project future actions. Technological advances like this have been, and will be, central in moving the biotech industry forward, with the sheer quantity of data involved making it a prime candidate to adopt the technology.

As drug trials begin to take less time, reliance on animal testing is reduced and drugs come to market sooner, pharmaceuticals will soon be reporting massive savings thanks to predictive analytics combined with a good data practice.

The biotechnology industry is currently at a turning point, with the uptake of new technologies, in particular predictive analytics, set to propel it into the 21^st century at last.

¹ Ernst & Young 2005