Biostatistics for Non-Statisticians

This course is designed as an introduction to the statistical principles that form the basis for the design and analysis of research investigations. The focus of topics will benefit individuals within the pharmaceutical and biotech industries including medical investigators, basic and clinical research scientists, clinical research associates those involved in regulatory affairs. It will concentrate on the philosophy and understanding of the statistical principles required in conducting sound scientific investigations. It will not simply present statistical formulae. Thus, the lectures are oriented toward professionals having little or no formal training in statistics or mathematics.

Learning Objectives

Those completing this course will have an understanding of the concepts and statistical methods required in biological and health science research. They will be able to interpret results related to design and analysis issues as routinely presented in the scientific literature and clinical trials.

Course Description

Introductory Methods (2 Days). This part of the course will introduce and detail the basic and intermediate statistical concepts that are essential for professionals in a biological, public health or medical environment. The first day will emphasize the principles of descriptive and inferential statistical applications while the second day will focus on actual study examples, problem solving and interpretation of results. Through out the course the participants are encouraged to ask questions and discuss examples relevant to their own work. The following include but are not limited to topic areas to be discussed.

- Basic statistical terminology needed to effectively communicate with and understand your statistical colleagues
- The statistical essentials required to initiate a research investigation
- Research questions in statistical terms
- Sample size considerations to insure accuracy of conclusions in clinical trials to determine treatment efficacy
- Discussion of statistical techniques to compare experimental approaches or treatment efficacy.

Advanced Topics (3rd Day - Optional). This section of the course will go cover more complex issues in research investigations and clinical trials. Topics will include:

- Association studies including correlation and regression analysis with clinical applications
- Examination of Phase I, II and III clinical trials analysis
- Survival analysis and discussion of techniques in bioequivalence and biotherapeutic studies
- Gaining information from multiple studies by meta-analysis.

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COURSE AGENDA

FIRST DAY

Statistical Concepts and Terminology: Population, sample, nominal, ordinal, continuous data

Statistical Measures and Descriptive Statistics: Central tendency (average or mean, median, mode), dispersion measures such as range, variance, standard deviation, coefficient of variation, unbiased estimates

Graphical Techniques: Histograms, bar charts, box plots.

Distributions: Normal, t-distribution, skewed distributions

Inferential Statistics: Point and interval estimates of the mean and variance of a population. Hypothesis testing for the mean and variance of a population.

Risk Assessment: Relative risk, odds ratio, Bayes risk.

SECOND DAY

Defining a Sound Scientific Study: Selection criteria to statistical considerations

Single Therapy Protocols: Phase I and Phase II clinical trials, sample size and analyses, simple regression techniques

Comparative Studies: Defining appropriate study hypotheses, study objectives, defining efficacy measures and endpoints (response), sample size considerations, quantitative measures, analyses (continuous and discrete data), case control studies

Data Presentation: Interpretation and discussion of results from actual clinical data computer output for categorical and continuous endpoints, p-values, statistical significance, risk measures.

THIRD DAY

Multiple Treatment Studies: Analysis of Variance (ANOVA), multiple regression

Multiple Treatment Clinical Protocols: Phase III protocol sample size and comparative analyses (response and survival techniques)

Bioequivalence and Biotherapeutic Studies: Point and interval testing for equivalence,
Non-inferiority and superiority graphical techniques

Meta-Analytic Techniques: Presentation of individual patient vs. literature based meta-analyses, statistical tests of homogeneity and pooled effect size.