Description: Bayesian statistics is an approach to data analysis, wherein prior beliefs about a certain quantity of interest can be formally incorporated and updated when new data become available. There is a big role for Bayesian statistics to play in making clinical trials more efficient. This two-day short course is designed to provide an introduction to both basic aspects and advanced features of Bayesian methods with applications to clinical trials. Day 1 will be a primer in Bayesian design and analysis of clinical trials, including fundamentals of Bayesian statistics, resemblance between Bayesian and classical trial designs, prior elicitation, and practical implementation of Bayesian designs in statistical software. Day 2 will focus on Bayesian adaptive methods for clinical trials, where modifications during the trial are enabled. The course will be a mix of lectures and practical session during which the attendees will apply learned methods in problems motivated by real clinical trials.

Location: In Person –

MRC Biostatistics Unit
East Forvie Building
Forvie Site
Robinson Way
Cambridge Biomedical Campus
Cambridge
CB2 0SR

Duration: 2 days

Course Tutors:

Dr Haiyan Zheng
Dr Pavel Mozgunov
Prof Thomas Jaki

Course fees: £300 (student registration), £460 (public sector registration), £600 (private sector registration)

Registration: Bayesian Methods for Clinical Trials, May 2023 | University of Cambridge

Description: The majority of biologic and small molecule drugs perturb protein targets to exert their effects. With the recent explosion in the availability of large-scale genetic association data, it is increasingly feasible to identify genetic variants that proxy the effect of perturbing a protein drug target. Such leverage of genetic data thus offers an efficient and cost-effective approach for identifying drug targets and studying their effects. While this course is entirely self-contained, it follows on naturally from the Mendelian Randomization course. Participants who are interested in both topics may wish to apply for both courses.

Location: Online

Duration: 1 week, 5 live sessions (x2 courses per year)

Course Tutors: Dr Dipender Gill, (St. George’s, University of London), Dr Ville Karhunen (University of Oulu), Dr David Ryan (University College London), Dr Stephen Burgess (MRC Biostatistics Unit, University of Cambridge)

Upcoming course dates: 27th March – 31st March 2023

Course fee: £300 for all participants

Registration: Genetics in Drug Development, March 2023 | University of Cambridge

More information: Genetics in Drug Development course (mendelianrandomization.com)

Description: Studies based on Mendelian randomization are increasingly being used to distinguish causal relationships from observational associations in epidemiology and to prioritize potential targets for pharmaceutical intervention. This course intends to explain both simple and more complex statistical methods for causal inference in Mendelian randomization studies, and the instrumental variable assumptions on which they are based. The course includes several computing practicals in R.

Location: Online

Duration: 3 weeks, 4 live sessions per week (x2 courses per year)

Course Tutors: Dr Stephen Burgess (MRC Biostatistics Unit, University of Cambridge), Dr Verena Zuber, (Imperial College London), Dr Apostolos Gkatzionis (MRC Unit, University of Bristol), Dr Andrew Grant (University of Sydney), Dr Amy Mason (Cardiovascular Epidemiology Unit, University of Cambridge), Dr Dipender Gill (St George’s, University of London)

Upcoming course dates: 6th March – 24th March 2023

Course fees: £200 (student registration), £380 (public sector registration), £500 (private sector registration)

Registration: Mendelian Randomization Course, February 2023 | University of Cambridge

More information: Mendelian Randomization course (mendelianrandomization.com)

Description: In statistical methods in biomedical settings, and provides skills for designing, assessing and interpreting Bayesian analyses using the R and JAGS statistical software. The emphasis throughout will be on practical, applied modelling: code to carry out analyses will be provided. It will consist of some on-demand content and some timetabled (live) sessions, covering topics from Bayesian inference to intergrating multiple sources of data. The target audience of the course is statisticians and people doing statistical analysis in any subject area. No experience of Bayesian methods is assumed, but we do we assume familiarity with key statistical concepts and R.

Location: Online

Duration: 2 weeks, 7 half-days of content (5 in week 1, 2 in week 2)

Course tutors: Dr Anne Presanis (MRC Biostatistics Unit, University of Cambridge), Dr Robert Goudie (MRC Biostatistics Unit, University of Cambridge), Dr Christopher Jackson (MRC Biostatistics Unit, University of Cambridge)

Course dates: 28th November – 6th December 2022

Course fees:

Registration: Registration Bayesian Statistics Online Short Course, November 2022

More information: Bayesian Statistics