Quantitative Strategies and Data Science

The Core of Your Clinical Development Decision-making Process

Ultimately, any biopharma or medical device company’s success depends on its ability to make the right decisions at the right time.  Cytel’s Quantitative Strategies and Data Science group helps customers transform data into robust decisions, minimizing development risks and increasing the chances of bringing new, effective therapies to patients, faster.


Our Quantitative Strategies & Data Science team comprises Statisticians, Data Scientists, Computer Scientists, Geneticists, Operations Research Scientists, Health Economists, Biomedical Engineers, Epidemiologists, and Pharmacometricians with an ability to achieve objectives in creative and effective ways. Our Strategic Consultants keep abreast of emerging trends in the industry and across regulators, adapting precedent and developing innovative solutions to meet the specific needs of each project. The team impartially selects and combines traditional and novel approaches enabling smart, efficient clinical development and reimbursement for biopharma and device companies of all sizes. The team interacts across six practice lines:

Adaptive Strategies

Complex Innovative Designs

Navigate the path to safer, more productive, successful trials

Custom Tools

Custom Tools

Increase Efficiency and Productivity with custom software developments

Discovery & Diagnostics

Discovery & Diagnostics

Cutting edge data analytics for today’s advanced big data technologies

Operations Research

Operations Research

Advanced analytics for better decisions 

Quantitative Pharmacology & Pharmacometrics

Quantitative Pharmacology & Pharmacometrics

Right drug, right dose, right time, right patient

Real World Analytics

Real World Analytics and Health Economics & Outcomes Research

Supporting smarter clinical development

Quantitative Strategies & Data Science underpin the advice we provide to our clients, ensuring data driven approaches are used at each stage of development to optimize the product lifecycle. Our multi-disciplinary team of highly trained PhD/MS consultants and analysts ensure that non-clinical, clinical and real-world data are used appropriately, applying leading-edge statistical and computational methods to support clinical trial and experimental designs, analysis, and interpretation of data to expedite patient access to the best health technologies.


Core services across the 6 practice lines include:

Advanced Statistics 

Bayesian Methods, Functional Data Analysis, Hierarchical Modeling, Longitudinal Models, Meta-Analysis, Missing Data, Multiple Comparisons, Multivariate Regression, Survival, Wavelets…

Data Curation & Visualization

Predictive Analytics

Data Mining, Statistical Modeling & Simulation, Artificial Intelligence: Machine Learning and Deep Learning Techniques

Statistical Planning for Clinical Development Programs

Strategic Alignment with Clinicians and Pharmacologists, Estimand Specification, Trial Design, Modeling & Simulation, Analysis & Inference Planning


Programming [R, Python, CDMs for RWD], Bayesian methods, AI, ML, CID for non-statisticians, MIDD, Estimands etc.