Applications of Chemometrics for Quality by Design in the Pharmaceutical Industry

Learn how to use chemometrics for vendor selection, raw material selection, reverse engineering, and PAT for Quality by Design in Pharmaceutical Industry.

Training on PAT application using NIR Spectroscopy

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. The following videos are related to the application of machine learning in scientific research.

Predicting unknown material properties using PLS Regression

Partial least squares regression (PLS regression) is a statistical method that bears some relation to principal components regression; instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space. Because both the X and Y data are projected to new spaces, the PLS family of methods are known as bilinear factor models. Partial least squares discriminant analysis (PLS-DA) is a variant used when the Y is categorical. This video shows Data based prediction of material properties.

Principal Component Analysis to Determine Drug-Exceipient Miscibility

The principal components of a collection of points in a real p-space are a sequence of  pdirection vectors, where the i^{{\text{th}}} vector is the direction of a line that best fits the data while being orthogonal to the first i-1 vectors. Here, a best-fitting line is defined as one that minimizes the average squared distance from the points to the line. These directions constitute an orthonormal basis in which different individual dimensions of the data are linearly uncorrelatedPrincipal component analysis (PCA) is the process of computing the principal components and using them to perform a change of basis on the data, sometimes using only the first few principal components and ignoring the rest.

Training on Failure Mode Effect Analysis

Failure Mode Effect analysis is a proven Risk Management strategy. This strategy is accepted world wide. Enterprises which are willing to improve their practices for better result often depend on this proven methodology. The technique is helpful to manage risk in any industry be the agricultural, food, pharma, FMCG, Hospital and banking!
So what are you waiting for?Understand the concept of Failure Mode Effect Analysis in natural steps: What is FMEA? Why should we perform FMEA? When should we perform FMEA? Who should perform FMEA? How to perform FMEA? Along with a case study on FMEA. To learn this fascinating technique, watch our Recorded Webinar Now!

Introduction to Six Sigma

Six Sigma is a method that provides organizations tools to improve the capability of their business processes. This increase in performance and decrease in process variation helps lead to defect reduction and improvement in profits, employee morale, and quality of products or service. Watch the training here.

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