Experimental and study design
Study design, endpoint strategy, sample size and power, randomisation and sample allocation, and decision criteria before data are generated.
Quantitative support across biomedical research and R&D
EigenQuant Solutions
Led by Min Sun, Founder and Principal Consultant, EigenQuant Solutions helps research and R&D teams turn complex biomedical questions into quantitative evidence, from study design and data analysis to modelling, review, and the next scientific move.
Min Sun
Founder and Principal Consultant
Chartered Statistician (CStat), awarded by the Royal Statistical Society, UK
Almost a decade of experience at Roche (Switzerland) and GSK (UK) R&D headquarters
Research lifecycle
Use quantitative evidence to decide what to study, trust, and advance.
Biomedical research teams often have more data than clarity. EigenQuant Solutions supports the full quantitative path: designing studies, analysing complex data, building fit-for-purpose models, stress-testing assumptions, and turning results into focused recommendations for the next experiment, analysis, or programme decision.
How EigenQuant helps
Consulting services across the biomedical research lifecycle.
Statistical analysis and modelling
Frequentist and Bayesian analysis, regression, mixed models, longitudinal analysis, survival analysis, hypothesis testing, uncertainty, and sensitivity analysis.
Translational and PK/PD evidence
Quantitative support and modeling for exposure-response, dose rationale, biomarker-response relationships, and proof-of-mechanism questions.
Complex biomedical data analytics
Analysis of high-dimensional biomarkers, omics such as RNA-seq and proteomics, imaging, flow cytometry, cytokines, and HLA types.
Fit-for-purpose ML/AI and optimisation
Prediction, classification, feature selection, pattern recognition including subgroup and responder identification, computer vision, optimisation, validation, and overfitting checks.
Research review and communication
Independent review, publication-ready analysis, reproducible workflows, reviewer responses, second opinions, and decision summaries.
Why EigenQuant
Integrated quantitative judgment across complex scientific questions.
EigenQuant Solutions starts from the scientific decision, then formulates the problem mathematically before choosing the quantitative approach that fits the question, the data, and the evidence required. The goal is not to default to the most complex method, but to select the method that matches the scientific question and the strength of the data.
Right approach, right question
That may mean statistical modelling, machine learning, optimisation, computer vision methods for image analysis, graph-theoretic reasoning, or mechanistic reasoning using dynamical systems, including differential-equation models and stochastic processes where appropriate.
Integrated research lifecycle view
Across Roche Pharma Research and Early Development (pRED) and GSK R&D headquarters, Min worked across connected scientific questions where target biology, biomarkers, exposure, imaging, endpoints, and uncertainty all influence what comes next.
Accredition by the Royal Statistical Society
Min Sun is a Chartered Statistician (CStat), awarded by the Royal Statistical Society, UK, combining professional statistical standing with models and summaries that scientific teams can understand, scrutinise, and use.
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