Dr. Stephan Ogenstad is President and founder of Statogen Consulting (http://www.statogen-consulting.com), Wake Forest, North Carolina. He is Adjunct Faculty Member and professor of biostatistics at Georgia Southern University. He has 20 years of experience with major pharmaceutical companies and distinguished university hospitals from around the world. Dr. Ogenstad earned a PhD in Statistics from the University of Stockholm, and worked as a professor of statistics at the Dept. of Statistics. He is on the International Advisory Committee of the University of North Carolina at Greensboro, and is elected President of the North Carolina Chapter of the American Statistical Association, and elected program chair for the section on Statistical Consulting for ASA for 2009.
Dr. Ogenstad lectured in experimental design, drug development and various other areas of biostatistics at the Karolinska Institute and the Swedish Academy of Pharmaceutical Sciences in Stockholm, Sweden. He served as senior statistical advisor to members of the Nobel Prize Committee of Medicine and Physiology. He is also a frequent presenter at international conferences.
Dr. Ogenstad has had numerous professional affiliations as well as society memberships. He has been the president of the Swedish Society for Medical Statistics, council member of the Swedish Statistical Association, council member and cofounder of the European Federation of Statisticians in the Pharmaceutical Industry, and chair of the Massachusetts Biotechnology Council, Biometrics.
During the past 20 years, he has held executive managerial positions in nonclinical and clinical biostatistics and clinical data management with AstraZeneca, Parexel International Corporation, Amgen, and Vertex Pharmaceuticals.
Dr. Ogenstad has contributed to the filing of 13 NDA/BLA submissions in Europe, USA and Japan. He has more than 80 publications, book chapters, and presentations in the areas of biostatistics and medicine.
Statistical representation at FDA EMEA; process innovation; Expert clinical statistics; statistics for medical devices; coaching; alliances; networks; internet; regulatory; negotiation; IT; methodology review; Analysis interpretation; Report review; Statistical reports; SAP; Exploratory analysis; Modeling simulation; Non- & preclinical consulting; Training (Clinical Trials Methodology, Biostatistics, Adaptive designs, GCP); Programming; CDM; wireless; Off-shoring and cost rationalization
It's my proud to join such a great group and meet professional ones.
Recently I have finished "The Role of Statistics in business and science" book, from Gerald J. Hahn and Necip Doganaksoy from Wiley series in probability and statistics.
This book gives me a lot of ideas for working with statistics. And as a student of statistics, it is really enjoyable and interesting.So I think it can be a good source for those who want know more about statistics roles in other science.
No, I haven't written anything that has been published on the subject. But I just have a way of explaining things to people that they seem to understand. I'll give an example. Power. It confuses people to no end. Many people think power = type II error. But we know it is 1-beta. When I tell people about power I tell them to think of power as a flashlight, and that significance is hiding in the corner, but he is there. Power can be likened to how bright the flashlight is to see the significance that is truly in the room. Then when they get that idea going I can get a bit more technical...
Another thing is repeated testing and increased Type I error. I tell clients that if they do lots of tests on the same sample they inflate the family wise error rate...and their eyes glaze over, lol. So I can tell them something like, "If you look for a needle in the haystack long enough and hard enough you'll find it, but it is still just a tiny needle.
So, things like this. I keep attempting to start a newsletter for my clients...just so busy!! Maybe it will slow down this summer and I can put more things together.
On your question about adaptive designs and the FDA, I've found in general the FDA is cautiously accepting of adaptive designs. (CDRH more warmly than CDER/CBER.) Trials using these designs need to have a lot of detail spelled out up front (e.g. alpha spending functions, expected sample size) as well as some assurance that the safety database will be large enough to accurately assess risk-benefit (a hard problem). In addition, some divisions (oncology, neurology) are more accepting than others. Bob O'Neill and Sue Jane Wang are quite familiar with the work and tend to show up to meetings with the less conventional approaches. On one occasion, I've seen the review team recommend an adaptive design over a more conventional design, but that's rare since that usually requires the medical reviewer or team leader to be familiar and comfortable with the methodology.