Strategic consulting and trial design
Oxford Outcomes has extensive experience in designing and conducting Epidemiology studies; we understand the importance of effective and informed advice during the design stages of trials and provide expertise in the design of clinical trials and analysis of trial data. Our experience in Epidemiology means we are able to offer strategic advice on;
- PharmacoEpidemiology, to characterize disease etiology, occurrence, risk factor distribution and to estimate
unbiased measures of the association between determinants and health status.
- Regression modeling, to examine predictors of health outcomes and to develop prognostic models.
- Longitudinal, time-series, and time-to-event analytic strategies which form the backbone of many observational
and interventional studies.
- Meta-analysis, including pair-wise and network strategies, to allow more accurate estimation of effect sizes
across trials and inform the inputs for future economic models.
- Observational real world studies of efficacy, safety and tolerability of therapies during licensing trials, to
fill knowledge gaps after randomized trials.
Our senior team in Vancouver brings together opinion-leading scientific expertise, knowledge of marketplace and regulatory landscapes, together with consultancy skills and deep understanding of client needs. Our clinical understanding of how Epidemiology feeds into clinical development, regulatory affairs, labeling and marketing allows us to provide advice at all levels. For more about the team and their recent publications click here.
Oxford Outcomes provides a customized study design, combining tried-and-tested approaches with cutting edge methods to deliver results. We design studies to credibly and effectively answer research questions, and best meet our clients' needs. Together with the Oxford Outcomes PRO team we can review, critique and recommend measures for inclusion in clinical trials to maximize responsiveness to the target outcomes, and minimize threats to validity. Early-phase data and modeling strategies can be used to inform the inclusion and exclusion criteria in the trial development phase. We can also recommend analytic strategies to maximize the likely efficiency and success of the trial.