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  5. Lisa LaVange, Ph.D. - Transcript
  1. Regulatory Science in Action

Lisa LaVange, Ph.D. - Transcript

Examining evidence in pre- and post-market settings to help provide safe and effective medicines

Dr. LaVange: The statistics here, they’re very challenging. The data packages are complex. The protocol designs are complex. The analyses we run are complex. So, you are challenged. What you get here that you can’t get anywhere else is the public health impact.

Text Slide:

Lisa LaVange, Ph.D.


Office of Biostatistics

Office of Translational Sciences

Dr. LaVange: The Office of Biostatistics is the resource for statistical expertise and knowledge in CDER. We work in the pre-market setting to examine evidence of whether drugs work and whether they’re safe. We work in a post-market setting to continue to monitor the safety of drugs once they’re on the market and being taken by a much larger and more heterogeneous population of patients, and we also support the non-clinical side of drug development with animal studies and other types of non-clinical studies, and we support the Office of Generic Drugs.

The statistics that we do helps to provide safe and effective medicines to people who need them. We have a direct impact to the public health, both the US and globally. That’s our strength and that’s our expertise.

With the advent of more powerful computing platforms, trial designs have gotten more sophisticated. Our statisticians need to be up on these trial designs. We need to be experienced in them. We need to understand them. We need to have state of the art statistical and computing skills.

One particular place in post-market, the post-marketing setting we’re working right now is the opioid epidemic and trying to determine if when we approve one of the newly formulated opioids, formulated to not be so easy to abuse, whether that’s actually making a difference in the epidemiological data, the data of overdose reports for example. And the data sources are complex and the statistical issues are complex.

Master protocols are an innovation that we’re particularly excited about right now. These are coordinated efforts to answer more than one question at a time regarding whether drugs work. They involve multiple drugs coming from different pharmaceutical sponsors who have to coordinate. So, you get a better use of patients, much more quick recruitment, and you end up with a powerful infrastructure, lots of trials being run at the same time; answers about drugs are available more efficiently and sooner.

I think biostatisticians play a very important role in CDER. We’re trained to find the truth in the data, or the evidence that the data can bring, and to assess that evidence and to make sure it’s sturdy.

We have an important role to play in determining whether drugs are safe and effective. We also try to impact the speed of development and the efficiency of development. We then are responsible for getting drugs into the hands of the patients that need them, and this is a real reason to get up and come to work in the morning.

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