Keeping Data Management In-House


Applied Clinical Trials

Global Head, Data Management, Bayer Schering Pharma AG, Germany, offers his perspective on recent trends in data management and why it's important to keep it in-house.

Johann Prove, PhD, Global Head of Data Management for Bayer Schering Pharma AG in Germany, will chair the Tuesday morning session: Future of Data Management/Evolving Role of Data Management. He is also a presenter, speaking on the topic: Keeping Data Management in House: How and Why?

Applied Clinical Trials spoke with Dr. Prove about the session.

Q: In terms of trends in data management, what have you seen in recent years? A: What I noticed in recent years, the past eight to 10, is that in many pharma companies data management has been off-shored. Off-shoring means really taking the entire data management operations group and moving them to mainly India, maybe China. And this is different from outsourcing, which [refers to] outsourcing certain trials but not the entire function to a CRO.

Q: These off-shoring companies in India, are they CROs? A: These are CROs; these could be start-up companies that just operate in India. But it could be subsidiaries of the major players like Covance, Quintiles or Parexel that have operations or people in India that do what I would call “leg work” in data management for them. But there are other companies. One particular one is Accenture, which is well known as a consultancy company that started an off-shore data management activity in India and then approached pharma companies and looked for business, the first one and most popular one being Wyeth.

Q: What is the allure of going the off-shore route for companies like Wyeth? A: What I know of Wyeth-and this is true for several other pharma companies-is that their data management processes were outdated. Wyeth, in particular, was a very paper driven pharma company, so their clinical trials used a lot of paper case report forms. Managing this huge amount of paper pages and case report forms, getting these pages entered into a database...and then cleaning the data was very tedious labor. And Western European or North
American resources would be really expensive.

Q: What are the disadvantages of off-shoring? A. It is very important to keep expertise in data management over the years. This is easier if you keep data management in-house compared to companies which off-shore. In-house you will have people who fully understand what happens to the data and where the issues are. As an example: As many pharma companies undergo frequent [regulatory] inspections, when I look at the types of questions that the inspectors ask us, we are always capable of answering those questions properly. I don’t know how this works in off-shoring companies.

Q: What do you feel are the advantages of keeping data management in-house? A: I think the timely availability of clinical trial data to the rest of the organization, understanding the data that we need to develop a drug, and providing interfaces to other functions within the organization is really the major benefit of keeping data management in-house. And when I talk about other functions, this is pharmacovigilance, clinical pharmacology, medical experts, project management, biostatistics. You need people within the organization that understand the data to an extent [so] you really can deliver on short notice what they are interested in or what they ask for.

Q: Why else keep data management in-house? A: I’m convinced that data management had to evolve into a direction that [it] not only deals with the pure patient data, but manages more than that. What I mean by that, for instance, is that data management helps to define the type of data that should be captured by looking into data that had been used in the past or those data that had not been used though captured.

Secondly, data management can contribute to the overall development of a drug. What I'm talking about, for instance, is identifying sites, countries, monitors that do not perform as expected. Which means we can use the electronic systems and look at the data and identify those sites where obviously there is a resource issue [and] where the sites require additional training.

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