Clinical Statistics for Non-Statisticians - Everything you need to know - in a day - 9 May 2019
In modern global pharmaceutical companies it is becoming increasingly important for non-statisticians to understand the value and application of statistics in order to maximise the value of the data.
This course is designed for professionals working in the pharmaceutical industry with no or little previous knowledge of statistics as we start right at the beginning with the basics.
It will be non-software focused, but rather understanding the basic statistical concepts, interpreting output and discussing how the knowledge can be applied and integrated efficiently into the job role.
Who should attend?
This course is aimed to introduce statistics to people who work on Clinical Trials, but who are not Statisticians or Professionals working in the Pharmaceutical Industry who wish to gain basic knowledge of the subject.
This basic but wide-ranging course will cover techniques for performing basic statistical techniques on data sets typical to pharma industry settings. There are many basic concepts that need to be understood before statistics can be used to its full potential to give useful and informative answers. The course ensures that these concepts are understood in a non-technical way and then demonstrated using data examples.
Mathematical details are kept to a necessary minimum and the focus is on interpretation of statistical output and illustrate applications with data from dummy clinical trials or published data. The objective of the course is not ot teach how to become a statistician, but to help to work with statisticians, ask them the right questions and get the maximum value when reviewing statistical output.
The basics of statistics are presented to give background and a common base to start from and the applications and use of statistics in drug development is then discussed. The role of the statistician and their ability to help with decision making is also explained.
Part 1: The Basics
• Descriptive Statistics (Summary Measures of Location and Spread)
• Describing Variation (Standard Deviation & Standard Error)
• Presenting Results (p-values & Confidence Intervals)
• Visualisations for presentation and explanation
• Power and Sample Size (incl. Type I and Type II Error)
Part 2: Design Issues
• Choice of Endpoints
• Avoiding Bias
• Crossovers vs Parallel Gp
• Equivalence & Non-Inferiority
• Missing Data
Gemma Hodgson, MSc, CStat. has worked in the Pharmaceutical Industry for over 20 years. Gemma began her career at Pfizer working in global teams on major phase III projects. After 13 years at Pfizer working in phase I through to phase IV, Gemma moved to Takeda R&D in London, focusing on close liaison with other departments within the organisation. Since 2012 Gemma has worked for and now runs Qi Statistics Ltd. Gemma has considerable experience in rolling out statistical training programmes to non-statisticians in a variety of industries.
Many practical examples are given and the emphasis is on application and understanding rather than the equations and the technical background. The training is interactive as far as possible and will include informal exercises (with answers!) and discussions.
9 May 2019
09.00 – 17.00 hrs
tram stop «Grosspeterstrasse»
Early Bird Fee: CHF 990.00 + 7.7% VAT (valid until: 28.03.2019)*
Regular Fee: CHF 1'110.00 + 7.7% VAT (valid after: 28.03.2019)*
*10 % reduction for CTC employees, SwAPP and SBA members
Registration fees include: Course documentation, refreshments, lunch and a course participation certificate.
Payment: After registration you will receive confirmation and an invoice with instructions on how to complete the bank transfer. Full prepayment is needed prior to the course.
• Cancellations received more than 14 days before course: 100% refund less bank charges & cancellation fee of CHF 50.00
• Cancellations received 7-14 days before the course: 50% refund
• Cancellations received 7 days before the course: no refund
In case of no show, no refund will be made
Training Terms & Conditions