The Danish Society for Biopharmaceutical Statistics (DSBS) was formed in March 1992 as an independent non-profit association. The aims of DSBS are to further the exchange of information between professional statisticians working for the pharmaceutical industry in Denmark and abroad, to promote professional standards, and to constitute an expert body in biopharmaceutical statistical matters. About 150 statisticians, representing 13 companies, are members of the society
Click on image to see the event plan.
To register, please send a mail to CAIO@novonordisk.com
Click on image to see the course plan.
To register, please send a mail to commres1351@Lundbeck.com
There is a limit on the number of attendees. The first come, first serve principle will be applied.
The programme for the 2016 Joint FMS/DSBS Meeting, taking place in Malmö November 1 2016, has now been announced. Click on the image above.
The theme of the meeting is Statistical analysis of risks and safety data, and the program is attached.
You can register for the meeting via the link https://viceversaeventmanagement.nemtilmeld.dk/14/at-bmafhlr8/
Last day for registration is October 17.
General Assembly for DSBS and a miniseminar will take place at Charlottehaven, Hjørringgade 12 C • 2100 København Ø
After the annual conference, DSBS will host a dinner at the same venue.
The Joint DSTS and DSBS Two-day Meeting was held on 10-11 November 2015 at Novo Nordisk, Bagsværd. The slide presentations and program can be found here.
The 6th edition of the European Statistical Forum took place in Vienna on November 16, 2015. The title of this year’s edition is: “Applications of statistical methodology in early drug development”. For further information about this edition, future and the past ones you can visit the website www.esforum.eu. DSBS members will be provided discounted participation fee.
The following article published in Nature may be of interest to you and your Industry colleagues: How scientists fool themselves—and how they can stop. There's also an accompanying commentary on blind data analysis: Blind analysis: Hide results to seek the truth, and an interesting editorial: Let’s think about cognitive bias.