I am an MRC Investigator in the clinical   trials methodology group, part of the   Design and Analysis of Randomised   Trials (DART) theme.

 My research aims to improve clinical trial design through the development of innovative methods that lie in the intersection between optimisation, machine learning and statistics. These methods may result in efficiency gains (i.e. smaller or faster trials) but face several practical barriers (e.g. a high computational cost) to be widely adopted. These innovations include patient-centric trials - i.e. those having an explicit goal of assigning more trial participants to superior treatments (e.g. an efficacious vaccine). My proposed programme includes four main objectives: 1) developing computationally easy to implement innovative trial designs, 2) improving analysis methods of optimal, patient-centric adaptive trials (estimation and testing); 3) designing innovative trial designs in response of specific emerging challenges (including using adaptive experiments to enhance and personalise m-health apps) and 4) promoting update and appropriate application of these novel designs in practice. For this last point 4) my collaboration with Papworth is fundamental and a main goal if my involvement in PTUC is to identify opportunities for the appropriate application of innovative designs and develop them into successful trials.

I am involved in two national trials that include an adaptive or innovative element. These are NIHR funded: The PIPAH trial (Positioning Imatinib for Pulmonary Arterial Hypertension) and The NOTACS trial (Nasal High-Flow Oxygen Therapy After Cardiac Surgery).

Other selected studies: MRC grant with Mark Toshner (Stratified adaptive therapeutic studies in pulmonary arterial hypertension caused by mutations in BMPR2), Rfpb study with Tim Quinell, Intelligent Stethtoscope, Prodose, HOPE.

Other responsibilities: training sessions, general managing of the team, PTUC meetings, open surgeries, link with BSU, UK network of CTUs meetings.

MRC Biostatistics Unit

I am a Research Associate in the MRC Biostatistics Unit, in the Design and Analysis of Randomised Trials group with the statisticians in the PTUC.

 My research aims are to improve   designs for clinical trials and to apply these improved designs in real-life trials. For me, “improvement” could mean a number of things, including reducing the number of participants required or creating a design that caters to an unmet need of investigators. I also have experience of clinical trials that evaluate multiple treatments in a single trial, known as multi-arm trials.

While I’m interested in all types of adaptive design, my particular expertise is in adaptive designs that use a binary (response/no response) primary outcome. For this type of design, I have developed an approach that greatly reduces the average number of participants required. There are multiple benefits of this: if a treatment doesn’t seem to work, ending early means fewer participants receiving a non-working treatment and allows investigators to move on to another possible treatment; if a treatment does seem to work, we can move on to the next phase of testing and get the treatment to more participants sooner. There are also benefits to ending a trial early in terms of financial and time commitments.

In the PTUC, I am involved in the PIPAH trial (Positioning Imatinib for Pulmonary Arterial Hypertension), a phase I/II trial that uses adaptive designs in both phase I and phase II.

Other selected studies: PROTECT-CH (NIHR), a UK-wide clinical trial to identify treatments that can protect care home residents from developing COVID-19.

Other responsibilities: Providing support in all statistical aspects of clinical trial design; Beginner course in R at the MRC Biostatistics Unit.

I am a Statistician based at the MRC Biostatistics Unit within the Design and Analysis of Randomised Trials (DART) theme, and I also work in partnership with the Papworth Trials Unit Collaboration. My main interests lie within applied clinical trial design and analysis.

I am the trial statistician for the NOTACS (Nasal High-Flow Oxygen Therapy After Cardiac Surgery) trial, which is an NIHR funded trial that uses an adaptive trial design. This trial includes an interim sample size re-estimation, which allows us to optimise the sample size and ensure that we are not recruiting too few or too many participants.

Other selected studies: NOMAB, NOTACS aerosol generation sub-study, Rfpb study with Tim Quinell

MRC Biostatistics Unit 

I am a Research Associate working in the Efficient Study Design theme of the MRC Biostatistics Unit (BSU) at the University of Cambridge. My research involves methodological developments for the design and analysis of Bayesian adaptive clinical trials, with a specific emphasis on early phase dose-finding trials. Before joining the BSU, I completed a PhD at McGill University, where I focused on improving the performance of Bayesian adaptive designs through utilization of covariate information. Prior to this, I worked as a biostatistician at Wake Forest School of Medicine where I was involved in several randomized controlled trials. Previously, I received a bachelor’s (Molecular Genetics) and master’s (Applied Statistics) degree from Ohio State University.