Statistical Advantage
November 2008
Gary Shorter, director of biostatistics for Quintiles, talks to Envisage editor Adam Istas about the growing importance of incorporating biostatistical analysis into all stages of drug development.
Let’s start at the big picture level. At what point in a clinical development program do you involve the biostatisticians?
GS: The standard approach has biostatisticians becoming involved early in the product’s development. Based on the clinical information available, they help define what the sample size should be for a particular trial. They also decide what analysis can be done for the particular type of data that’s being put together.
As an analogy, I would compare it to an auto-racing team with the statisticians serving as the technicians. Naturally, you have different levels of technicians. You have technical advisors at the high level that would put the sample size together and help define the strategy upfront for that trial to ensure the trial has the best chance of success. Then, you have the ongoing monitoring during the trial where, similar to a race car in an auto race, you must check in on the trial and see how it is progressing. Whether it’s the beginning, middle or end of the product’s development cycle, biostatisticians play an important role in helping to keep the trial moving forward. Experience in doing this quickly, efficiently and correctly is invaluable. There are rules to follow and there’s no time for mistakes, so experience and expertise are critically important.
Here at Quintiles, our statisticians go beyond the standard approach—they don’t just look at one clinical trial, they look at the development of the whole compound. To take this back to the auto racing analogy, they take the wider view and look at the whole racing season.
How has the role of biostatistics in clinical development changed during the last 10 or 20 years?
GS: Quite simply, 10 or 20 years ago, we weren’t doing this type of statistical analysis throughout the course of a trial. In fact, it’s still somewhat of an issue in some places. Statisticians at some pharmaceutical companies are invited to be involved in as much of the development as possible. Others are siloed off where they do the sample sizing and the analysis and that’s it. With an increased emphasis on safety, the industry is now realizing that it needs to look more carefully at data, which greatly benefits from more involvement from the statisticians and the programmers. Data mining is becoming more important than it was 10 or 20 years ago as safety questions crop up and safety signal detection is needed in real time, making the need to have statisticians and programmers involved on a regular basis critical.
Has technology been the primary driver of this increasing role?
GS: Yes, electronic data capture (EDC) has definitely helped as it allows you to have data in real time. A previous, paper-based study had the problem of a two-week lag in simply retrieving the data from the investigative site, and then presumably a further delay in actually analyzing the data. With access to real-time EDC data, you can see what signals are coming through, so you can produce reports quickly and get them out to a steering committee on a much more regular basis. Instead of the data being two weeks old, it’s now only 24 hours old. We are still reliant, however, on the investigators in the field completing the necessary electronic documentation in a timely manner.
What role can biostatistics play in the post-marketing realm?
GS: Safety is the primary focus. We have all seen the news about data from multiple studies that raise questions about the validity of a drug’s safety, so there’s much more emphasis on continuous review through the life of the compound from development through approval and beyond. With standard systems in place, it’s feasible to provide regular updates throughout the lifecycle of the compound that brings multiple studies together to build on the broader safety profile. With set rules apriori, you can data mine for events of interest in lab results and events over time, bringing them together in a high level dashboard ‘readout’ that keeps the statistician aware of the status.
What are you and your group looking forward to, with regard to technology or your role in drug development as a whole?
GS: What I am looking forward to most is bringing our technical expertise to more partnerships with our customers. There are so many efficiencies to be gained and costs and time to save when you keep it consistent. We know how to get the best from a racing car, but that can only happen if you are given a seat at the design table. We have a number of tools (CDISC, SAS CDI/SDD), techniques (signal detection, site fraud detection, enrollment/event analysis, data mining) and experts bringing the latest developments (adaptive clinical trials, therapeutic, biomarker) to the industry.
When a team includes the right people at the table, it means that everyone commits to one goal, making the effort much more focused. Drug development is a true team effort that takes years of planning and development, but with the right commitment and expertise you can achieve great things.
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