As the Global VP of Data Sciences and managing Site Head at Quotient Sciences’ Edinburgh location, Greg Johnson oversees the Data Science services that we provide to our clients. This involves working closely with the functional Directors for each of the six different Data Science departments (Database Programming, Data Management, Statistical Programming, Pharmacokinetics, Statistics, and Medical Writing) and alongside our clinical units in Nottingham and Miami.
Looking back to when you were first starting your career, was your goal to be where you are now?
I grew up in Cambridge UK, studied for a BSc in Pure Mathematics and Statistics at Cardiff University, and then trained to be a teacher in Wales. In 1990 I moved to Edinburgh and I have lived here ever since. Initially, I had no real career plan in mind other than to try something different first before I became a full-time teacher. I was lucky enough to be offered a job as a clinical programmer which I enjoyed and became more involved in Phase I-IV clinical trials, performing different roles over the years at a variety of Phase I-IV CROs. I used to occasionally think I would go back to teaching “in a couple of years”, however after 30 years in the clinical trial industry that seems less and less likely!
You mentioned that you started in Data Management and Programming, how has your career progressed since then?
Just after I started work in clinical trials, networked PCs were rolled out and the early ones were about the size of a fridge, however at the time, this seemed quite cutting edge. The early Phase clinical trials we conducted were more simplistic in design, much less adaptive, and usually single-part. Paper CRFs were used to collect study data and ‘remote access to data’ consisted of faxing copies to sponsors to allow them to review study data. Although the methods of data collection and technologies have improved immeasurably, requirements for GCP and scientific rigor in study set-up, data management, statistical analysis, and reporting have all remained unchanged.
How does Data Sciences help our customers?
We help our clients by providing an integrated Data Science service in support of clinical trials conducted in the Nottingham and Miami units. We work flexibly depending on the different sponsor needs, for example, Biotech generally relies on us as their in-house experts, whereas the work is more collaborative with Pharma staff for data management, statistics, etc.
In summary, the Data Science departments perform key tasks including protocol writing, randomization, and database building to allow study set-up. During the study we manage data and aid interim decision-making; after the clinical phase ends, we lock the study database, program datasets, and summary listings/tables, and perform statistical and pharmacokinetic analysis/interpretation, all of which are then included in the Clinical Study Report (CSR). Essentially, the CSR and datasets are the reason that the sponsor is ultimately conducting the study.
What types of programs does the Edinburgh facility support?
Most Data Science staff are based in Edinburgh, however, we also have staff in Nottingham and Miami. We provide Data Science services for the wide variety of clinical studies/programs conducted at our Nottingham or Miami sites.
For each study, a functional Lead is assigned from each of the six Data Science departments (e.g. Lead Medical Writer, Lead Statistical Programmer, etc) and we support all our clinical trials in one way or another. For most studies we provide “full service” i.e. we perform all Data Science tasks. A few sponsors prefer to perform some, or all of the Data Science services themselves, although we always build the study eSource database because that is required for data collection in our clinical units.
How does the Edinburgh facility support Quotient Sciences’ Translational Pharmaceutics programs?
Data Sciences are a key component of our Translational Pharmaceutics offering. In addition to the Data Science study services described above, we provide interim PK reports and interim database listings. These enable crucial dosing decisions to be made during Translational Pharmaceutics studies e.g. after a cohort or study period. We have provided hundreds of such interim outputs over the past few years, usually within only a few working days.
How much has changed in terms of the team since you started up until now?
I joined six years ago and in this time Data Sciences has grown from just over 30 staff to almost 85. As a result, three years ago we outgrew our Edinburgh office and moved to the current office in the West of Edinburgh.
Due to our specialist early Phase services and procedures, we have tended to recruit new graduates and train them. However, we have also hired some experienced staff who we think they will bring some valuable experience. With support from others like HR and Recruitment, I believe we have been very successful in both approaches and the excellent Data Science staff project work over the years would seem to demonstrate this. In addition to technical skills, we put high emphasis on teamwork; one related comment made to me by a new member of staff about a year ago was “How do you manage to only recruit good people?” which I particularly enjoyed hearing.
What do you think is one of your teams biggest successes?
I was fortunate that when I took over the Data Science department it was in excellent shape with a stable Data Science management team and strong support staff. I am delighted to have been able to help continue the expansion of Data Sciences and services alongside the growth of the clinical studies conducted in Nottingham. Since the Miami clinical unit was acquired and integrated into the Quotient Sciences family, I have also been pleased to see how we have jointly delivered growth in the number of “full service” studies conducted there and how well we work with the clinical and project management staff there too.
I am also proud that we see so many Data Science staff start and progress their careers here, and they in turn have contributed massively to the business's success.
When conducting a study, what do clients need to make crucial dosing and program decisions?
To drive the next stage of their overall clinical development program or raise additional funding, sponsors need to include one or more of the following deliverables from Data Sciences: interim or end-of-study pharmacokinetic/statistical results and interpretation, a published CSR and/or datasets (e.g. CDISC SDTM, ADaM and define-xml packages) for regulatory submission.
We typically lock a database within 3-4 weeks of the end of the clinical phase and can issue a draft CSR 5-7 weeks later, depending on the study size and complexity. These metrics compare very well with industry standards and we have many examples of sponsors taking much longer when they perform Data Science services in-house or elsewhere.
Our strong record for timeline adherence reflects the close working relationships between the different Data Science departments and with project management, clinical, and others across our sites.