Clinical Biostatistics · Drug Development
Statistics for the people who actually develop medicines.
Clinical Biostats teaches the methods used in real clinical trials and regulatory submissions — and builds the interactive tools that put them to work.
Primary & Key Secondary Endpoints
HR / OR, 95% CIHow the site works
Go beyond textbook statistics.
Practical explanations built around clinical trials, regulatory submissions and real pharmaceutical development — not abstract theory.
Clinical Methods
Regression, survival analysis, MMRM, Bayesian methods, multiplicity and missing data — explained the way they're actually applied in trials.
Interactive Tools
Sample size, power, dose-finding and adaptive design calculators you can run against your own trial parameters.
Applied Expertise
SAPs, TLFs, estimands, CDISC programming and the regulatory context that connects statistics to submissions.
Statistical Tools
Tools built for real trial design.
Every calculator on Clinical Biostats runs the same methods you'd defend in a protocol or SAP. This preview shows what the Sample Size & Power calculator looks like — open it to run it against your own assumptions.
Open Sample Size CalculatorSample Size & Power — Two-Sample Proportions
Tutorials
Six methods every trial statistician needs.
Each tutorial works through the method's assumptions, its regulatory context and a worked clinical example.
MMRM
Model specification, covariance structures and interpretation for repeated-measures trial data.
Read tutorial →Missing Data
Estimand-aligned strategies for handling dropout, from MI to reference-based imputation.
Read tutorial →Survival Analysis
Kaplan–Meier, Cox regression and proportional hazards in the context of oncology trials.
Read tutorial →Multiplicity
Gatekeeping procedures and alpha-spending for trials with multiple endpoints or comparisons.
Read tutorial →Sample Size
Power calculations for common trial designs, from simple superiority to non-inferiority margins.
Read tutorial →Trial Design
Adaptive designs, dose-finding and the operational statistics behind modern protocols.
Read tutorial →Tools
Interactive statistical tools.
Turn methodology into something you can actually run. Every calculator links out to its own dedicated page.
Sample Size & Power
Superiority, non-inferiority and equivalence designs across common endpoint types.
Simon's Two-Stage
Optimal and minimax designs for single-arm Phase II oncology trials.
TITE–BOIN
Time-to-event Bayesian optimal interval design for late-onset toxicities.
Group Sequential Design
Interim analysis boundaries and alpha-spending functions for adaptive monitoring.
Insights
Timely regulatory & methodological commentary.
Short, practical takes on guidance changes and methods debates that affect how trials get designed and analyzed.
ICH E9(R1) Estimands: What Actually Changed in Practice
A practical look at how estimand thinking has changed SAP language and sensitivity analyses since adoption.
When MMRM and Multiple Imputation Disagree
Reconciling primary and sensitivity analyses when the two standard approaches to missing data diverge.
Reading FDA's Latest Adaptive Design Guidance
What the updated guidance means for interim analyses and pre-specification in confirmatory trials.
Built by an industry biostatistician
“The goal isn't to teach statistics in isolation. It's to teach statistics the way they're actually used to develop medicines.”PhD in Statistics · Pharmaceutical clinical development · BLA / MAA / IND experience
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Expert Discussions
Original commentary and practical takeaways from leading statisticians, researchers and quantitative scientists working in drug development.
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Explore tutorials, calculators and professional training built around real clinical trial statistics.