Deeper Dive: Life Sciences

As Inkling introduces prediction markets to more and more companies, we are beginning to notice some issues common to each industry. This is the first of a series of postings that will discuss how Inkling is being used to address some of these issues. The first example I want to share in detail is in the life sciences industry.

To understand some of the issues life science companies are facing we need to understand some macro trends:

• In 2006, people in the first wave of the baby boomer generation reached their 60's and by 2024, all boomers will be over 60. In 2030, the elderly, defined as over 65 are expected to represent almost 20% of the population versus 13% in 2010.
  
• The biotechnology industry continues to thrive. New medications, devices and other medical advances continue come to market at an ever increasing pace.
  
• With the human genome mapped and a greater understanding regarding the role of genetics in chronic illness, personalized medicine is gaining increasing acceptance. As a result, new diagnostic equipment and tests are being developed to identify a patient's genetic composition and determine if the patient has a greater chance of developing certain diseases.
  

Alongside these macro trends is a great amount of uncertainty:

• Constant potential for new regulations
  
• Modification or even a complete transformation of the U.S. healthcare insurance market
  
• Changes in how the FDA may evaluate and ultimately approve new drugs, with more attention being paid to safety and tolerability of compounds
  
• Greater generic competition
  
• Greater oversight in the direct-to-consumer (DTC) market
  

Knowing how uncertain the future is, how do life science companies create strategies for growth while at the same time, avoiding the paths with pitfalls that can negatively impact their business?

Prediction markets are an excellent way to assess and evaluate the risks that life science companies face.

For example, a pharmaceutical company is currently developing several new molecules many of which have promise. In particular, the company has developed a new compound that treats a major neurological disease. The company knows that its competitors have other products that are further along in the clinical development process. But the company does not think the competing products are as effective as its molecule. To further complicate the picture, recently a new device was approved by the FDA which treats the disease in a completely different manner. However, before most insurance companies will pay for the device, it needs to be approved for reimbursement by Medicare.

Based on the competitive environment, the company faces a key question: Does it spend its resources on the molecule for the neurological disease or, would it be better positioned if it developed one of its other drugs where it may face less competition but also a smaller potential market?

Using Inkling, the company asks several questions which try to better assess the competitive situation: Will a competitor's product be approved by the FDA before the end of the year? Will Medicare agree to cover the costs associated with the new device? If Medicare agrees to cover the device, what will the total out-of-pocket costs to patients be? Before the end of the year, will an international drug company license its product to a U.S. competitor to ultimately gain entry to U.S. market?

Questions that were largely answered by hunches and guesses can now have probability scenarios assigned to each of them.

As these markets are run, senior management now has much more context from which to make the decision regarding the future of their own molecule.