Home
Data analysis
Data analysis add-ons offer a wide range of capabilities, ranging from analytical methods over comprehensive analysis to statistical process control. PLA 3.0 also provides a set of add-ons that support and supplement data analysis add-ons.
bioMérieux Endotoxin Detection Assay Package
Use the bioMérieux Endotoxin Detection Assay Package add-on to perform endotoxin testing based on recombinant factor C (rFC), a synthetic alternative to naturally sourced reagents derived from horseshoe crabs, as offered by the bioMérieux company.
bioMérieux endotoxin detection assays
Use bioMérieux endotoxin detection assay documents to detect or extrapolate endotoxin concentrations in potentially contaminated test substances by comparison with a defined endotoxin dilution series.
Analytical settings
To support you in defining your analytical settings, bioMérieux endotoxin detection assay documents provide a set of concepts you should be familiar with when working with this document type.
Regression model
Select a regression model to accurately quantify endotoxin levels by fitting a curve or a straight line to the assay data of your bioMérieux endotoxin detection assay.

Get started
Explore PLA 3.0, its key features and ongoing enhancements. Learn how it fits into your environment, and how to log in and register.
User interface
PLA 3.0 supports you in your daily work by providing a set of graphical and textual user interface elements. Learn about the different elements and how to use them efficiently.
Key concepts
Details on documents and templates, the data editors and the Content editor of PLA 3.0.
Data analysis
Data analysis add-ons offer a wide range of capabilities, ranging from analytical methods over comprehensive analysis to statistical process control. PLA 3.0 also provides a set of add-ons that support and supplement data analysis add-ons.
- Biological Assay Package
  Use the Biological Assay Package for potency analysis of biological assays. The add-on comes equipped with a highly flexible test system to qualify your assay. You can perform combination calculations to obtain a reportable value from independent assay runs and use historic assay data to develop equivalence margins.
- Biological Assays Simulation Package
  Use the Biological Assays Simulation Package to create simulations of quantitative response assays (QRAs) and use the Quantitative response assay document type of PLA 3.0 to store the simulated data.
- bioMérieux Endotoxin Detection Assay Package
  Use the bioMérieux Endotoxin Detection Assay Package add-on to perform endotoxin testing based on recombinant factor C (rFC), a synthetic alternative to naturally sourced reagents derived from horseshoe crabs, as offered by the bioMérieux company.
  - Installation
    Find details on the system requirements for the bioMérieux Endotoxin Detection Assay Package add-on and the steps to install the add-on in your environment.
  - bioMérieux endotoxin detection assays
    Use bioMérieux endotoxin detection assay documents to detect or extrapolate endotoxin concentrations in potentially contaminated test substances by comparison with a defined endotoxin dilution series.
    - Assay setup
      To support you in setting up your assay, bioMérieux endotoxin detection assay documents provide a set of concepts you should be familiar with when working with this document type.
    - Analytical settings
      To support you in defining your analytical settings, bioMérieux endotoxin detection assay documents provide a set of concepts you should be familiar with when working with this document type.
      - Regression model
        Select a regression model to accurately quantify endotoxin levels by fitting a curve or a straight line to the assay data of your bioMérieux endotoxin detection assay.
      - Coefficient of variation
        The coefficient of variation (CV) assesses the precision of the assay, indicating how much variation exists between replicate measurements. A lower CV indicates more consistent, precise results, while a higher CV suggests greater variability and less reliability in the measurements.
      - Final activity rounding
        Final activity rounding lets you round the calculated final activity of a sample during an endotoxin detection assay, thus influencing the interpretation of the final values and ensuring consistency and compliance with predefined limits.
      - Gain optimization
        The gain of a plate reader reflects its dynamic range, indicating the level at which reasonable measurements can still be carried out. bioMérieux endotoxin detection assay documents let you define a gain optimization routine, therefore providing the data you need to adjust the signal amplification to maximize dynamic range and ensure the results remain within the instrument's detection limits.
    - Test system
      Set up a test system to prove the validity of your calculation. The bioMérieux endotoxin detection assay document type provides a set of tests that cover, for example, regression model parameters, recovery rate of the positive product control, coefficient of variation, and behavior of the blank control.
  - Templates
    The bioMérieux Endotoxin Detection Assay Package comes equipped with endotoxin detection assay templates, preconfigured with the analytical settings, test system, and assay layout required for the respective assay kit.
  - Use case: Validate a cleaning process for pharmaceutical water
    In the pharmaceutical industry, water is an important resource both in synthesizing and developing products and in cleaning vessels and other types of equipment. Validating the cleaning processes for pharmaceutical water to prevent product contamination is therefore crucial.
  - Reference information
    Find reference information on the bioMérieux endotoxin detection assay document type provided by the bioMérieux Endotoxin Detection Assay Package.
- Control Chart Package
  The Control Chart Package allows sophisticated statistical process control (for example, by plotting Shewhart I-Charts as recommended in the USP <1010>). It provides visualization options for intervals, subcharts and sidecharts, and allows you to define colors by a secondary characteristic. You can also define rules based on events and time frames.
- Dichotomous Assay Package
  Use the Dichotomous Assay Package to analyze biological assays based on quantal (binary) responses by fitting probit or logit models to estimate the potency of your samples.
- Dose-Response Analysis Package
  The Dose-Response Analysis Package provides various biostatistical methods for immunoassays, ELISA, and more. It supports you in investigating equivalence for calibration curves, provides enhanced data processing, and options for subgroup analysis.
- Generic Document Types Package
  Use the Generic Document Types Package add-on to document general information.
- Integration Report Package
  Use the Integration Report Package for creating reports in additional file formats that are not covered by the standard PLA 3.0 reporting functionality. These reports can be used for example for automated processing in third-party software.
- Measurement Documentation Package
  The Measurement Documentation Package add-on is a universal add-on for documenting different aspects of a measurement. Its documents can be referenced by other document types, for example, Quantitative response assays.
- Microbial Assays for Antibiotics Package
  The Microbial Assays for Antibiotics Package for PLA 3.0 is your software for assessing the potency of antibiotics. This add-on supports various methods, that is, cylinder-plate, turbidimetric, and combination of microbial assays. It enables you to closely follow the guidelines laid out in the United States Pharmacopeia (USP <81>) and the Japanese Pharmacopoeia (JP 4.02).
- Split Assay Package
  Use the Split Assay Package to split a Quantitative response assay with several Test and Control samples into individual assays, each with the Standard and one Test or Control sample.
- Toolkit for Biological Assay Package
  Use the Toolkit for Biological Assay Package to modify the analytical settings of larger sets of Quantitative response assays or split Quantitative response assays with more than one test or control sample into individual assays.
Data import
Use data acquisition and data import add-ons to import external response values and observation data into PLA 3.0 for further processing and evaluation.
Installation
Details on the deployment and installation of licensed PLA 3.0 versions.
Licensing
Details on the licensing solution of PLA 3.0, the available licensing options, and the activation and management of licenses.
Administration
Details on system administration tasks such as setup and maintenance of databases and add-ons, user accounts, access rights, and migration and update procedures.
Regulatory compliance
PLA 3.0 supports you in achieving compliance with regulations such as ISPE GAMP^® 5 and 21 CFR Part 11. It also provides options to validate PLA 3.0 in your environment.
PDF downloads
Download PDF guides of current and previous framework and add-on versions.
Sample lab
Meet the team of Stegmann Labs Inc. and use our sample laboratory to explore core features and functions of PLA 3.0.
Glossary
Find definitions of terms.

Regression model

Select a regression model to accurately quantify endotoxin levels by fitting a curve or a straight line to the assay data of your bioMérieux endotoxin detection assay.

Created from scratch, bioMérieux endotoxin detection assay documents use the 4-parameter logistic regression model. You can switch to the linear model if you require.

Figure 1. Regression models of a bioMérieux endotoxin detection assay document

4-parameter logistic model

Use the 4-parameter logistic model to let PLA 3.0 determine the regression curve using the measured RFU values at the nominal concentration of the Standard sample.

The model is defined by the following equation:

dRFU = \frac{(A - D)}{1 + {(\frac{Dose}{C})}^{B}} + D

This regression model is weighted with method 1/y or 1/y².

Linear model

Use the linear model to let PLA 3.0 determine the regression curve using the measured RFU values at the nominal concentration of the Standard sample.

When using this regression model, a Blank control sample for calculating the net dRFU is required.

The model is defined by the following equation:

log(net dRFU) = m \cdot log (Dose) + n