Richard Houghton (Roche)
6 years
I completed my BSc Mathematics at Sheffield Hallam University, MSc Applied Statistics at Birkbeck, University of London and am currently studying part-time for a PhD in pharmacoepidemiology at Maastricht UMC+ in the Netherlands. Roche supported me as I pursued my Master’s degree and currently ongoing PhD alongside working. While working for Roche I have had the opportunity to work in 3 different roles and even move countries (UK to Switzerland).
I have been working in the Personalized Health Care Data Science department in Basel, Switzerland for almost 4 years. During this time, I’ve been able to work in multiple disease areas, so I’ve learnt a lot since joining.
A mix of meetings and research, I guess around 50-50 overall. Generally, we try to keep meetings to a minimum, but meeting your colleagues and stakeholders regularly is the best way to make sure that everyone stays aligned on the objectives.
IT systems, access to data, and analytic environments are all set up very nicely to ensure that the time we get to devote to deriving insights from data can be most productive. The role of data and analytics in personalised healthcare is constantly expanding and being redefined, with many new and exciting projects available to people in the department.
Generally, I enjoy learning and understanding everything related to epidemiology – such as natural history of disease, predictors of safety and effectiveness of treatments in the real world setting, and supporting our clinical trials.
I like collaborating with scientists to help the setting and prioritising of research questions in alignment with stakeholder needs. Then, once these questions and objectives are set, as an analyst I deal with large and complex databases that contain the keys to unlocking these questions.
This course is aimed at clinical trial statisticians who are new to or with limited experience of machine learning. Attendees will learn about a range of topics in machine learning, including practical sessions in R.
This webinar will explore two different approaches to Correlates of Protection in vaccine development.
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
The event will open with an overview on drug development in women’s health from a clinician perspective. This talk is followed by talks about statistical challenges when planning IVF studies and analysing the menstrual cycles.
This webinar will provide an overview of surrogacy for licensing and reimbursement. In turn, the need of extensions of the SPIRIT and CONSORT statement will be defined and outlined, with case studies to support.
Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.
We will share a brief overview of what Mobilise D is and why it is an important step stone in the development of digital biomarkers, and how Mobilise D outputs can be relevant for you.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
We have exciting new opportunities available for Study Statisticians, Support Statisticians and Exploratory Statisticians at various levels.
