The document discusses the significance of statistical analysis in the development and evaluation of pharmaceuticals, particularly in clinical trials where participants are allocated treatments based on predefined protocols. It highlights various statistical methods, such as sequential analysis, hierarchical models, and meta-analysis, which are essential for accurate data interpretation and reducing biases. Additionally, it addresses risk-based allocation and decision analysis as approaches to optimize the evaluation process.

1. STATISTICAL ANALYSIS OF CLINICAL DATA
DARSHIL K. SHAH
M.PHARM –I
ROLL NO. 15
REGULATORY REUIRMENTS FOR PHARMACEUTICALS (RRP)

2.  Statistics: are a mathematical methods of
describing and drawing conclusions from data.
Statistics are an essential part of the medicines
development process at multiple stages.
 Clinical trial: is a clinical study in which
participants are assigned according to a pre-
defined therapeutic strategy or plan (protocol) to
receive a health-related intervention, such as a
medicine, in order to investigate its effects on
health outcomes, usually compared to another (or
sometimes no) treatment.

3. THE ROLE OF STATISTICS
Statistics play a very important role in any clinical trial
from:
 design,
 conduct,
 analysis, and
 reporting in terms of controlling for and minimising
biases, confounding factors, and measuring
random errors.
A grasp of statistical methods is fundamental to
understanding randomised trial methods and results.

4. STATISTICAL METHODS
 Statistical methods provide formal accounting for
sources of variability in patients’ responses to
treatment.
 The use of statistics in clinical trials allows the
clinical researcher to form reasonable and accurate
inferences from collected information, and sound
decisions in the presence of uncertainty.
 Statistics are key in preventing errors and biases in
medical research

5. SOME STATISTICAL APPROACHES TO ANALYSIS OF
SMALL CLINICAL TRIALS
 Sequential analysis
 Hierarchical models
 Bayesian analysis
 Decision analysis
 Statistical prediction
 Meta-analysis and other alternatives
 Risk-based allocation

6.  sequential analysis: sequential hypothesis testing
is statistical analysis where the sample size is not
fixed in advance. Instead data are evaluated as
they are collected, and further sampling is stopped
in accordance with a pre-defined stopping rule as
soon as significant results are observed.
 Hierarchical Model: are a type of linear regression
models in which the observations fall into
hierarchical, or completely nested levels.
Hierarchical Models are a type of Multilevel
Models.

7.  Bayesian inference: It derives the posterios
probability as a consequence of two antecedents:
a prior probability and a "likelihood function" derived
from a statistical model for the observed data
 Decision analysis: is the discipline comprising the
philosophy, methodology, and professional practice
necessary to address important decisions in a
formal manner

8.  Statistical prediction: is the use of the data from
an informative experiment E to make. some
statement about the outcome of a future experiment
F. The prediction statements. commonly treated in
the literature are of inference type, in which the
purpose is to give.
 A meta-analysis: is a statistical analysis that
combines the results of multiple scientific studies.
Meta-analysis can be performed when there are
multiple scientific studies addressing the same
question, with each individual study reporting
measurements that are expected to have some
degree of error.

9.  Risk-based allocation: It is done for two reasons.
First, the natural heterogeneity from subject to
subject requires some accounting for random
effects; and second, the differential selection of
groups due to the risk-based allocation is handled
perfectly by the “u-v” method introduced by Herbert
E. Robbins. The u-v method of estimation
capitalizes on certain general properties of
distributions such as the Poisson or normal
distribution.

10. REFERENCES:
 European Patients' Academy
https://www.eupati.eu/
 Sciences engineering medicines
https://www.nap.edu/read/10078/chapter/5