Mendelian Randomization Course

The course comprises four half-days’ worth of content plus the final hackathon, and will take place over 3 weeks (plus a preliminary week 0). It consists of some on-demand pre-recorded content and some timetabled (live) content. The first day of Week 1 will be Monday 6^th November 2023. All the core content of the course is pre-recorded - live sessions are not compulsory to attend, but are supplementary to the core content. They represent a chance to engage with the course tutors. Several of the live sessions will be recorded.

Each half-day can be done whenever is convenient. A half-day of content includes three pre-recorded talks (around 20-30 minutes each) and one practical session (around 1-1.5 hour). Each of the three computer practicals should be performed individually, but there is an associated live drop-in session to come and ask questions. There is also a recorded debrief session that runs through the practical content. In terms of live content, in addition to the practical drop-in sessions, paper discussion, and hackathon, there is also a question and answer session each week to ask your questions. Questions can be asked during the week on a dedicated Slack channel, or you can ask questions live (Q+A sessions will be recorded).

The hackathon is an opportunity to perform your own Mendelian randomization investigation to use the skills you have gained during the course. This can be done individually or as part of a group.

Participants should choose one of the papers for the timetabled paper discussion (Practical 3), and one hackathon session, based on their availability and preference.

Genetics in Drug Development

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. Leveraging such genetic data thus offers an efficient and cost-effective approach for identifying drug targets and studying their effects.

This short course “Genetics in drug development” will provide theoretical and practical advice on using genetic data to:

1. Identify drug targets
2. Investigate the effects of drug target perturbation for different indications
3. Explore potential adverse effects and repurposing potential for drug targets
4. Identify biomarkers to explore drug efficacy in early stage clinical trials
5. Identify population subgroups for which drug effects may vary
6. Explore interactions between different drugs and exposures

The course will be held online over one week and will consist of a series of recorded video lectures, live interactive sessions with practical examples, and participation in an online community that allows for interaction with peers and tutors throughout the course.

While this course is entirely self-contained, it follows on naturally from the Mendelian randomization course held in March. Participants who are interested in both topics may wish to apply for both courses.

Many confirmatory clinical trials turn out to be negative and do not lead to the registration of a new drug or the introduction of a new treatment. Consequently, there is growing interest amongst clinical researchers in the use of efficient methods for conducting early and late phase trials to identify the most promising compounds, and in using interim analyses to allow trials to be stopped as soon as there is sufficient evidence to reach a convincing conclusion.

Adaptive designs allow mid-trial modifications to be made to the trial so that the accumulating data guides investigators to the most appropriate form of evaluation. While offering great flexibility during the trial, they require specialised approaches to be designed and analysed.

In this course, we are going to introduce the definition of adaptive designs and consider its several most common types that are delivered through a mixture of lectures, practical sessions, and discussions.

Specifically, we are going to explore:

1.  Group Sequential Designs

2. Multi-Arm Multi-Stage Designs

3. Sample Size Re-estimation

4. Response Adaptive Randomisation

5. Master protocols

Throughout the course, the examples of implemented in practice designs that the MRC BSU has contributed to recently will be used to demonstrate the methodology. The workshop will involve practical sessions in R on these designs implementations and discussions on the practical aspects. By the end of the course, you will design your own adaptive trial.

Course aims

This short course introduces students to Bayesian 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.

Course outline

The course runs on the Moodle online learning platform, and involves 7 sessions:

1. Quantifying uncertainty with probability
2. Bayesian inference
3. Bayesian regression models
4. Critiquing and comparing Bayesian models
5. Hierarchical models
6. Modelling with missing and censored data
7. Integrating multiple sources of data

Course delivery

The course will be delivered via the Moodle online learning platform. The course consists of 7 half-days worth of content, and will take place over 7 half-days across 3 weeks starting on Friday 17th November 2023.

It will consist of some on-demand content and some timetabled (live) sessions.

Further details can be found on More Info tab.