QTech Web-Analytics Software solution is being developed, in order to be deployed quickly and maintain easily at the client site. This software solution is a web based Business Intelligence applications for unlimited users of different skill level.  These applications can enable users to dice, merge and analyze the data in variety of ways with no knowledge of IT and very little training. Dashboards, Scorecards, Trends, Trial Repeat and other tools can be developed, which can provide fast and flexible analytical reports to users with nobody’s help. Major benefits of these Internet based BI applications are as follows.

• Timely and accurate information.
• Customized reports with real time/near real time data from various data sources.
• Applications can be delivered to unlimited number of users irrespective of their location and IT expertise.
• Consistently fast response and predictable query time.
• Instinctive interface and Interactive multidimensional reports. Data can be analyzed on different dimensions like categories, time and measures (metrics).
• Trends,comparative and time based analysis can be performed.
• Smaller learning curve and faster decision making process.
• Minimal knowledge of programming and databases required.
• Data can be explored at summary level then can be drilled down through data hierarchy to examine micro level details.
• Complex calculations and flexible analysis can be done in no time.

Qtech Solutions Inc (Qtech-Sol) SAS-Application PETT Tool is designed to perform the following functional. As a SAS Solution Provider Company, this tool is design to meet the company standards pertaining to its Data Design & Quality Execution process needs towards Clinical Data Execution, Data Validation and Reporting Needs for its FDA/EMEA submissions in compliance with CFR Part 11 standards and clinical practices.

PETT- Protocol Execution and Transformation Tool, includes processes to validation date being feed from various clinical data resources and allows the user to apply regulatory and therapeutic business transformation into practice by linking the data to SAS Resources.

Key Benefit using PETT:

• Perform process analysis.
• Document system requirements and process flows (use cases).
• Matching the derived requirements to existing test cases,where none exist, develop new test cases
• Development of Requirements Specification and
• Development of System Design Specification.
• Save in approx 50% reduction in process execution times.

(a) Pre-Execution Process with PETT:

Fresh current data is available and feed to repository from live data feed interface per schedule.

(b) At Execution Process with PETT:

• Protocol review is preformed and the data elements required is determined.
• The data variables required for assessment and analysis is identified per inclusion and exclusion criterion per test carried prior to creating samples, randomization schemas.
• The PETT tool allows the design of standard templates to select, manipulate and create standard reports.
• It contains options to select data based on criteria required, by writing sql codes.
• The inclusion/exclusion criterion are applied per regulatory policies and therapeutic areas and tests performed.
• Selection of samples, randomization under normal, logistic and binomial distribution is performed for test sampling using SAS in PETT.
• Stratified random samples and segment-based selection of subjects can be created within the tool, depending upon data needed for analysis.
• Created new derived and persistent derived variables based on functional to retain for analysis.
• Creates standard output files as required and SAS datasets per protocol tests needs and made available for analysis.
• Queried Data from the host using the SAS PROC SQL/pass through facility.

Data Validation and Statistical Analysis - Involved in certification of standards, clinical release studies of Patients Extracted data from Flat files, Oracle SQL Tables and SAS Datasets. Performed Cleaning Techniques on Clinical Data provided. Performed data validation of existing data and identified bad data and listed them as reports using Proc Reports, Proc Tabulate and Print facilities of SAS. Used Proc Freq, Proc Means and Proc Univariate to select random observations to identify invalid, missing data and created files to be used for correction later.

(c) Post Execution Process with PETT:

• Track Responders based on Data Inputs from responder system.
• Phase wise Standardization of reports pertaining to various tests per guidelines for submission.
• The Flat files, SAS datasets and Tables are created per standard metadata layouts are used directly for reporting and statistical analysis.
• Environment: SAS 9.1.3 (Base, Macros, SQL, ODS, Graph and STAT Modules)