S. Yin Ho, founder and CEO of New York-based pharmaceutical data provider Context Matters, isn’t impressed with all the entrepreneurial excitement around “big data”—the effort to lasso all the information being collected about consumer buying patterns and the like and use it to improve business strategies. As far as Ho is concerned, it’s not the volume of the data that matters. “A lot of people focus on the big part of it, instead of the impact,” Ho says. “I think it’s more about the ability to glean some kind of insight from the data.”
Ho, a former physician, started Context Matters in 2010 with a plan to amass data about drug development around the world, and then parse it in a way that would be useful to pharmaceutical executives making decisions about whether or not to develop certain products. The company’s platform, which is Web-based, draws on several hundred sources of data to track trends in drug approvals, clinical trials, patent grants, and reimbursement decisions by private and public insurers. Customers can filter the data based on several parameters, including disease and geographic territory.
Much of Context Matter’s initial focus was on reimbursement patterns—an increasingly important issue in drug development. If, for example, a pharma company develops a long-acting version of an existing drug but can’t get any insurance companies to pay for it, the drug becomes worthless. Context Matter’s technology allows R&D decision-makers to predict whether or not their newfangled drugs will pass muster with insurers by looking at the previous experiences of other companies that have developed similar products.
Hence the name, Ho explains. “Part of the reason for calling the company Context Matters is that context determines what the value of a product is,” she says. “You can’t determine your relative value unless you can ask, ‘Am I going to get reimbursed in this market, and if I don’t have a shot, is it worth me putting extra money into this drug?’”
One recent Context Matters client, for example, was trying to decide whether or not to license an experimental molecule from another company, says Ho, who declines to reveal the company’s name. “They wanted to know if the formulation was different enough that
