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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.
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.
Reference information
Find reference information on the document types of the Dose-Response Analysis Package add-on.
Equivalence margin development documents
Find details on the document structure of Equivalence margin development documents and access reference information on particular document elements.

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.
- 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.
  - Installation
    Find details on the system requirements for the Dose-Response Analysis Package add-on and the steps to install the add-on in your environment.
  - Dose-response analysis
    Use Dose-response analysis documents to perform curve comparisons and create calibration curves.
  - Equivalence margin development
    Use Equivalence margin development documents to utilize data of earlier assays to develop and verify test systems and export these systems to apply them in new assay development.
  - Test system definition
    Use the Test system definition document type to define a collection of suitability tests and corresponding margins for Dose-response analysis documents.
  - Use case: Determine total human thyroxine (T4)
    Thyroxine (T4) is a commonly measured thyroid hormone for diagnosis of the thyroid function. Determining the total quantity of human thyroxine in serum is a standard use case for interpolation on a calibration curve.
  - Reference information
    Find reference information on the document types of the Dose-Response Analysis Package add-on.
    - Dose-response analysis documents
      Find details on the document structure of Dose-response analysis documents and access reference information on particular document elements.
    - Equivalence margin development documents
      Find details on the document structure of Equivalence margin development documents and access reference information on particular document elements.
    - Test system definition documents
      Find details on the document structure of Test system definition documents and access reference information on particular document elements.
    - Document elements
      Find reference information on the document elements in the document types of the Dose-Response Analysis Package add-on.
- 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.

Equivalence margin development documents

Find details on the document structure of Equivalence margin development documents and access reference information on particular document elements.

Select a link to display reference information about the respective element.

Equivalence margin development for dose-response analysis assays
.... Name
.... Identification
.... Date
.... Settings
........ Margin development
........ Test strategy verification
........ Test strategy visualization
........ Confidence level
........ Tolerance level
.... Data table
........ Observation source
........ Row order
........ Document reference
........ Section
............ Name
............ Column key
............ Property filter
................ Property key
................ Term
........ Development assay
............ Name
........ Verification assay
............ Name
........ Scientifically acceptable
............ Name
........ Exclude assay
.... Margin development
........ Equivalence test (parameter estimate)
............ Upper asymptote (A) (nonlinear models)
............ B parameter (nonlinear models)
............ C parameter (nonlinear models)
............ Lower asymptote (D) (nonlinear models)
............ Asymmetry parameter (G) (nonlinear models)
............ Slope (linear models)
............ Intercept (linear models)
............ Difference of asymptotes (A - D) (nonlinear models)
............ Ratio of asymptotes (A / D) (nonlinear models)
........ Test: Parameter/property point estimate
............ Upper asymptote (A) (nonlinear models)
............ B parameter (nonlinear models)
............ C parameter (nonlinear models)
............ Lower asymptote (D) (nonlinear models)
............ Asymmetry parameter (G) (nonlinear models)
............ Slope (linear models)
............ Intercept (linear models)
............ Difference of asymptotes (A - D) (nonlinear models)
............ Ratio of asymptotes (A / D) (nonlinear models)
........ Anova terms
............ Test: Sum-of-squares model
............ Test: Sum-of-squares residual error
............ Test: Sum-of-squares lack of fit
............ Test: Sum-of-squares pure error
............ Test: Sum-of-squares total
............ Test: Mean-squared model
............ Test: Mean-squared residual error
............ Test: Mean-squared lack of fit
............ Test: Mean-squared pure error
............ Test: Mean-squared total
.... Test strategies
........ Strategy
............ Name
............ Equivalence test (parameter estimate)
................ Upper asymptote (A) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ B parameter (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ C parameter (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Lower asymptote (D) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Asymmetry parameter (G) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Slope (linear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Intercept (linear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Difference of asymptotes (A - D) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Ratio of asymptotes (A / D) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
............ Test: Parameter/property point estimate
................ Upper asymptote (A) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ B parameter (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ C parameter (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Lower asymptote (D) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Asymmetry parameter (G) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Slope (linear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Intercept (linear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Difference of asymptotes (A - D) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Ratio of asymptotes (A / D) (nonlinear models)
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
............ Anova terms
................ Test: Sum-of-squares model
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Sum-of-squares residual error
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Sum-of-squares lack of fit
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Sum-of-squares pure error
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Sum-of-squares total
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Mean-squared model
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Mean-squared residual error
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Mean-squared lack of fit
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Mean-squared pure error
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
................ Test: Mean-squared total
.................... Alternatives
........................ Upper margin (calculated value)
........................ Upper margin (manual input)
.................... Alternatives
........................ Lower margin (calculated value)
........................ Lower margin (manual input)
.... Visualization
........ Max simulations
........ Max configurations
........ Model
........ Alternatives
............ Logarithmic dose transformation
................ Logarithm base
............ No dose transformation
........ Degrees of freedom
........ Transformed dose range
............ Transformed dose minimum
............ Transformed dose maximum
........ Response range
............ Response minimum
............ Response maximum
........ Simulation space
............ Standard error: A upper asymptote (nonlinear models)
............ Standard error: B parameter (nonlinear models)
............ Standard error: C parameter (nonlinear models)
............ Standard error: D lower asymptote (nonlinear models)
............ Standard error: G asymmetry parameter (nonlinear models)
............ Standard error: Intercept (linear models)
............ Standard error: Slope (linear models)
............ Covariance of A upper asymptote and D lower asymptote
............ Variance
.... Comment
........ Subject
........ Text
........ Linked document
........ Date
........ Author