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

University of Cambridge Students and Staff, whose department will be covering the participation cost, please raise a Purchase Order (or contact a member of your department who can assist with this) and send a PDF of the Purchase Order to burgess-group-admin@mrc-bsu.cam.ac.uk . You will then be sent the passcode which you will need to use along with the Purchase Order number to complete registration below, selecting the 'UoC Student/Staff Registration' option.

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 2nd November 2026. 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).

University of Cambridge Students and Staff, whose department will be covering the participation cost, please raise a Purchase Order (or contact a member of your department who can assist with this) and send a PDF of the Purchase Order to burgess-group-admin@mrc-bsu.cam.ac.uk .  You will then be sent the passcode which you will need to use along with the Purchase Order number to complete registration below, selecting the 'UoC Student/Staff Registration' option.

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, prior elicitation, and practical implementation of Bayesian designs in statistical software. Day 2 will focus on Bayesian adaptive methods for clinical trials, historical information borrowing, and basket trial designs. 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.

University of Cambridge Students and Staff, whose department will be covering the participation cost, please raise a Purchase Order (or contact a member of your department who can assist with this) and send a PDF of the Purchase Order to courseadmin@mrc-bsu.cam.ac.uk .  You will then be sent the passcode which you will need to use along with the Purchase Order number to complete registration below, selecting the 'UoC Student/Staff Registration' option.