On behalf of PSI (Statisticians in the Pharmaceutical Industry) I am pleased to announce the following training course :
Introductory workshop on Optimum Design Theory and its application to Pharmaceutical Drug Development, presented by Patrick Johnson (JPharma Solutions), Gordon Graham (Novartis) , and Barbara Bogacka (Queen Mary, University of London). The course will run on 6-7th November 2013 at the Park Inn Hotel, Bath Road, Heathrow UB7 0DU. Course outline: Pre-clinical and clinical studies are performed in drug development with one of the main objectives being the description of observed data through the use of regression models. When designing these studies it is desirable that the collected data will be informative for these model fitting purposes. This course will look at the application of experimental design optimality criteria for selecting design variables in the context of fitting a range of regression models. Example models include: · Linear regression models · Nonlinear models: sampling time selection for pharmacokinetic models and dose selection for dose-response models · Nonlinear mixed effect models: blood sampling time selection for population pharmacokinetic models This two day course provides an introduction to optimum design theory and its application for the efficient design of studies for the purposes of regression modelling. The emphasis will be to deliver a course that mixes theory and practical examples explored in hands-on workshops. Theory Provide an overview of optimum design theory for the purpose of regression modelling, including linear and nonlinear models and mixed effects models. Application Discuss application of optimum design theory in drug development, in particular dose-response and pharmacokinetic models, illustrated with simulated examples and real examples taken from the literature. Software Tools The course will use R and PFIM, a program written for R that evaluates and optimises designs for nonlinear mixed effects models Workshops To reinforce the optimum design theory, hands-on examples will be explored in workshops. The workshops will introduce a range of modelling and design problems, which the delegates will explore through hands-on tasks. Examples will start with simple models such as linear models, building to complex models such as nonlinear mixed effect models. The workshop is targeted at statisticians and pharmacometricians who are involved in selecting the key design variables such as doses, sampling times and sample size in pre-clinical and clinical studies for the purposes of regression modelling. To book a place, go to the PSI website. Please register online at <http://www.psiweb.org/> www.psiweb.org (click on Events); payment is now available online. Registration costs (includes lunch and refreshments): Early-Bird Registration on or before 01 October 2013 PSI Members: £495 plus vat Non-members: £530 plus vat Registration after 01 October 2013 PSI Members: £595 plus vat Non-members: £630 plus vat PSI reserves the right to cancel the course if an insufficient number of delegates is registered by the early-bird deadline, in which case the course fees and any hotel booking costs made through PSI will be refunded. For further information please contact: Emma Lovett, Tel: +44 (0)845 180 349, Fax: +44 (0)1730 715291, Email: [email protected] Gemma Hodgson Qi Statistics Ltd http://www.qistatistics.co.uk <http://www.qistatistics.co.uk/> Direct Dial: +44 (0)1732 848606 Mobile: +44 (0)7708 700503 Trading Address: Penhales House, Ruscombe Lane, Ruscombe, Reading RG10 9JN VAT Registration: 527 2571 45 Company registration: 4203486 Registered Address: Overdene House, 49 Church Street, Theale, Berkshire RG7 5BX <http://www.linkedin.com/company/qi-statistics?trk=hb_tab_compy_id_2987134> linkedin logo IMPORTANT: This communication is to be treated as confidential and the information in it may not be used or disclosed except for the purpose for which it has been sent. If you have reason to believe that you are not the intended recipient of this communication, please contact the sender immediately.
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