Software for the Pharmaceutical and Bio-Technology Industry

The Unscrambler®

In the Pharmaceutical and Biotechnology industry, The Unscrambler® software is used for a variety of data analysis needs and the design of experiments.

In the Pharmaceutical and Bio-Technology Industry, The Unscrambler® helps:

• Identify differences between HPLC Mass Spec data sets, and also of combinations of several data sets of one type versus several data sets of another type
• Create models (PLS .cal file) that could be used with AIRS 3.0 for discriminate analysis purposes (raw material identification)
• Find methods for raw material identification

The Unscrambler® Features | Download a 30-Day Trial

Some instances of how The Unscrambler® has been used in the Pharmaceutical and Biotechnology field segments follow.

HPLC-MS study of Normal/Tumor lung tissues: Lung tissue masses were observed and recorded at specified difference times over an HLPC run. The masses have a particular accuracy value and at times a “window” – indicating that two mass measurements are the same, if their masses are within 0.5 of each other and their times are within 1 of each other. A single data set could have different elements such as mass and time that could be absent in another data set, or sometimes 3-10 times more intense than in another data set.

The client needed to examine differences between two HPLC Mass Spec data sets or combinations of several data sets of one type versus several data sets of another.

The Uncrambler® was used to calculate correlation coefficients (CR) in conjunction with Matlab’s channel line-up capability. The Unscrambler® helped compare the CR among normal samples and tumor samples as well as between two mixed types. It identified the difference between two types if any existed.

Qualitative and quantitative analysis for lactose classification with NIR measurements: The client needed to create a PLS model that could be used with AIRS 3.0 for discriminate analysis. This would in turn identify suitable raw materials for different products.

A set of NIR spectra were measured for both lactose anhydrate and monohydrate forms. The spectra had a large variation in intensity though derived from same chemicals. The client needed to classify the two forms based on their spectra.

The Unscrambler® was used for data pre-processing spectra normalized by mean using SIMCA and PLS DA. These methods were proven to yield useful results and classification.

Experimental Design for Optimization of fermentation media, innoculum size and time, fermentation parameters, and others: The client was restricted to standard Design of Experiments such as full factorial design or fractional factorial design. With The Unscrambler® they could develop Plackett-Burman, Box-Behnken and Mixture Designs. This lowered the number of experiments that needed to be carried out and also improved the interpretation of the results.

NIR measurements of mutants: The client is developing a new application for the rapid identification of good mutants for antibiotic production. For this application, the client uses spectrometric application of Near-infrared spectrometry that yields a large amount of data that has to be interpreted using multivariate data software. The Unscrambler® is used for analyzing this data.