Software requirements: definition and specification

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Quality Assurance01:19

Quality Assurance

Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
Drug Dissolution: Requirements and Profile Comparison01:14

Drug Dissolution: Requirements and Profile Comparison

The acceptance criteria for dissolution profile data are anchored in Q values, representing the percentage of drug dissolved within a specified period. This assessment unfolds in three stages:First Stage: The test passes if all six drug dosage units are equal to or greater than Q plus 5%; otherwise, the sample proceeds to the second stage.Second Stage: The average of twelve units must be equal to or greater than Q, with no unit falling below Q - 15% to pass; if not, it progresses to the final...
Clinically Relevant Drug Product Specifications: Methods of Establishment01:29

Clinically Relevant Drug Product Specifications: Methods of Establishment

Product specifications define the acceptable quality of a pharmaceutical product by ensuring identity, purity, potency, and strength. These specifications serve as benchmarks during development, manufacturing, and post-approval quality control. Clinically relevant specifications are particularly important because they directly relate to a drug's safety and efficacy in clinical use.Dissolution studies are critical biopharmaceutic tools that link in vitro behavior to in vivo performance. They...
Response Surface Methodology01:16

Response Surface Methodology

Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
Introduction to R01:11

Introduction to R

R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's functionality,...
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...