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To Research in Statistics, Mathematics,  and SAS programming

We have technical expertise in Statistical Analysis Plan, Reporting and interpreting analysis results, SAS programming, and Validation of TFLs (Safety and Efficacy tables, figures, listings using SAS or S-Plus/R.) for clinical trials in phases I-IV. We have expertise in most of therapeutic areas and our specialties are Oncology, Osteoporosis, Diabetes, Alzheimer's disease and Cardiovascular, Chronic Obstructive Pulmonary Disease (COPD), devices such Elite SPY, surgical Mesh analysis. We have over 20 years of pharmaceutical experiences and clinical data manipulation. We had played great role in number of successful NDA submissions within pharmaceutical industries. We are familiar with FDA requirements and knowledgeable of drug approval process, ICH guidelines, GCP, and EMEA. We can take your clinical trial studies to a successful FDA submission using CRT (Case Report Tabulation) for electronic submissions, implementing SOPs and Working Guidelines.

We have expertise working with the following statistical and mathematical software packages:

SAS, R, WinBugs, BUGS,  East, Adaptive, Bayesian, JMP, nQuery, MATHLAB, IBM-SPSS,  NCSS/PASS. 

 To discuss more in detail how we can help you to design clinical trials and to reach to your successful FDA submissions, please get in touch with us.

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Articles to consider for Clinical Trial Design

About 10000 clinical trials are undertaken annually in all areas of medicine, from the treatment of acne to the prevention of cancer. Correct interpretation of the data from such trials depends largely on adequate design and on performing the appropriate statistical analyses. The statistical aspects of both the design and analysis of trials are important, with particular emphasis on recently developed methods of analysis.

1. Guidance for determining the number of centers in clinical trials

2. Guidelines on Data Safety and Monitoring

This guideline is to provide the oversight and necessity of interim monitoring to ensure the safety of the study participants and the validity and integrity of the trial data. Phase III clinical trials usually have a Data and Safety monitoring Board (DSMB), with broad responsibility for monitoring the conduct of the trial.

3. Guidelines for the Creation of Analysis Data Files and Documentation of Statistical Analyses for Submission

 Optimal Two-Stage Designs For Phase II Clinical TrialsThe purpose of this document is to provide guidelines for the creation of analysis data sets and associated documentation that are submitted to the FDA statistical reviewer in support of the primary and important secondary study objectives.

4. Guidance for Contents of the Clinical Study Report 

The purpose of this document is to provide guidelines on what information need to be included in statistical section of the Clinical Study Report (CSR).

5. Guidance for Non-Inferiority Clinical Trials

6. Fundamentals of Biostatistics ( 1. Clinical Trials (RCT), 2. Validity/Reliability, 3. Assessing Evidence)


Oncology: Optimal Two-Stage Designs For Phase II Clinical Trials

Richard Simon: Optimal Two-Stage Designs

Enter probability of accepting poor drug (alpha) [between 0 and 0.3 only]
Enter probability of rejecting good drug (beta) [between 0 and 0.3 only]
Enter response probability of poor drug (P0) [between 0 and 1]
Enter response probability of good drug (P1) [P1 should be greater than P0]

Example of this Calculation

Your input

Alpha --------------------------------------------> 0.10

Beta ---------------------------------------------> 0.10

Response Probability of Poor Drug (P0) ---> 0.40

Response Probability of Good Drug (P1) ---> 0.60


Your Output

Optimal Two Stage Design Optimum Design MinMax Design
First Stage Sample Size (n1)
Upper Limit For 1st Stage Rejection of Drug (r1)
Maximum Sample Size (n)
Upper Limit for 2nd Stage Rejection of Drug (r)
Expected Sample Size If Response Probability = P0
Probability of Early Termination at P0


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