2 day course: 10th & 11th June 2019.

The importance of exploratory clinical research prior to the launch of a large-scale definitive phase III clinical trial is becoming increasingly recognised, both in the pharmaceutical industry and in public sector medical research.  Dose-escalation studies are first-in-human studies intending to determine a safe dose or range of doses which can be taken forward for further development. 

Advances in the identification of medical biomarkers of therapeutic effect and in statistical techniques based on adaptive designs and Bayesian inference now allow such studies to be designed efficiently, to take account of information from a variety of sources and to combine objectives such as establishing safety and seeking evidence of a potential benefit.

This course presents state of the art methodology for dose-escalation studies.  The course will be delivered through a mixture of lectures, practical sessions and discussion sessions.

Important please note:

We will make every attempt to accommodate Lancaster University staff and postgraduate research students on our courses. However, if a course becomes fully booked we reserve the right to give priority to students on the MSc in Statistics, MSc in Data Science, and external participants.

Details of course fees.

Payment: Once you have registered, please pay at the online shop 

https://online-payments.lancaster-university.co.uk/product-catalogue/courses/mathematics-and-statistics/short-courses-and-cpd/mps-research-unit-psc-short-courses-20182019

Accommodation Details: Can be found here.

Cancellation Policy

Registrations are transferable to another course or individual at any time. Full refunds will be given for cancellation 10 or more working days before the course start date. Otherwise the full course fee will be charged.

Programme:

Model-based dose-escalation in oncology
Dose-escalation in healthy-volunteer studies
Bayesian curve-free dose-escalation for drug combinations
Dose-escalation designs incorporating multiple endpoints.