Umetrics MODDE


MODDE@ – Explore. Improve. Advance!

MODDE introduces the dynamic Design Space estimations with the new Design Space Explorer which interactively allows you to slide through the multidimensional design space.
MODDE also facilitates creating beautiful reports using the new report generator or the predefined formats when exporting to Other documentation and presentation tools.
MODDE is the perfect DOE software for research, process development, pilot and manufacturing in industries such as pharma, biotech, chemical, pulp and paper, food and beverage. Designed to meet requirements from new users all the way to power users and statisticians, MODDE supports the user with wizards and advisors at all levels of DOE; from planning and setting up new investigations to analyzing results with cutting edge technology. MODDE is available for development and integration in customer specific applications (OEM) as MODDE-Q.

The release is in line with Umetrics’ vision for a complete offering in PAT and QbD underpinned by Umetrics MVDA technology for on and off-line solutions using the SIMCA software family.

For Pharma and other critical application areas
As anyone in product development knows, getting things right from the start is a challenge. Especially with so many parameters to take into account. For industries like Pharma where outcomes are critical and the competition is fierce, you need tools that you can be sure will get you to the market on time.

Faster, easier optimization
MODDE is the most effective method you can find for achieving product and process efficiency and optimization. Created specifically to help scientists, engineers and statisticians understand complex processes and products, MODDE is the only guide you need to reach a safe interpretation and evaluation when designing experiments. lts intuitive graphical interfaces and detailed data visualization combine to enable effective and accurate decisions.

Beyond classical DOE
With MODDE we don’t stop at DOE, but empower you to simultaneously perform valuable quality analysis without having to rely on Other software. By integrating risk analysis visualization we go much further than the classical DOE Contour and Sweet Spot plots. Our unique Probability Contour Plot introduces Monte Carlo simulation to show you where risks for failure exist, as well as the probability of achieving the results you need according to the desired criteria. Leading the way in Design Space estimation. Because classical overlay contour methods provide no assessment of risk, many solutions fall short in their contributions to QbD and Design Space estimation. With MODDE, Umetrics leads the way in developing real QbD and estimation of Design Space by taking into account uncertainties and variations in parameters, measurement systems and processes. And it works with up to 32 factors and multiple responses.

Unique risk analysis visualization
The Probability Contour Plot is a unique tool created for MODDE that significantly enhances your ability to perform quality analysis together with DOE — a new dimension in your efforts to achieve Quality by Design.
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New version of MODDE 13 released!
Check the MODDE 13@ release letter .pdf for more details.
Do you want to be at the absolute forefront of Design of Experiments and Quality by Design? Download/purchase the latest version of MODDE@ Design of Experiments Solution.

The release includes new functionalities such as one-click analysis, which makes it possible for you to run the analysis wizard in one-click, and help you determine if the model is correct.

Two new designs:
Do your analysis in fewer experiments. With the generalized subset designs, GSD, you have the possibility to accomplish reduced designs even when handling multiple multilevel factors. This is an excellent DOE strategy for a stepwise investigation approach, stability testing or multivariate calibration.

Umetricsrv Suite of Data Analytics Solutions integration: With the connection to SIMCA@ Multivariate Data Analysis Solution it is possible for you to continue to do your analysis in SIMCA, and merge the DOE setup with big tables of data such as for example raw data and process data.

Download your free trial today and test out all the new functionalities.

New Features

MODDE Pro 13 includes state-of-the-art functionality for creating designs and analyzing the results with confidence, supporting the Quality by Design initiative through a set of useful tools.

New features in MODDE Pro 13:

  • One-Click feature, including automatic outlier detection, transformation and model tuning.
  • Generalized subset designs — A unique design setup that generates a sequence of reduced design sets.
  • Improved advisor in the Analysis wizard.
  • Definitive screening designs for 4 to 30 factors.
  • Export function to SIMCA.
  • Response correlation effect optionally included in Design Space calculations.
  • Qualitative factors with missing level supported.

MODDE Pro specific functionality:

  • Robust optimization • Probability estimates for a robust solution
  • Design Space documentation
  • Advanced and interactive setpoint analysis with capability estimation
  • Proven acceptable range documentation
  • Generalized subset designs for optimal complementary design sets
  • Special application designs for example RED-MUP, Stability testing and reduced combinatorial
  • Advanced constraints of design region
  • Mixture designs

There are a number of reasons why we think MODDE
V 13 is superior:

1. It has now one-click analysis. Using One-Click in the Analysis Wizard aims at making the analysis process as simple for you as possible. Auto transform and Auto tune are performed without your involvement while there are other warnings that need your attention. This section explains a One-Click scenario where no interaction is necessary.

See also : Webinars available

2. MODDE V 13 is very easy in usage.
MODDE is known for its graphical interface and interactive graphics. MODDE 13 has further made it easy to set up designs, enter data, and analyse the results.

3. New designs:
When quantitative and qualitative factors are specified to have two levels, the design generation is straightforward. There are then several classical design families tochoose from, for instance full factorial designs, fractional factorial designs, and Plackett- Burman designs. However, when quantitative and qualitative factors at three, four, or even more levels are involved in a DOE investigation, a challenge arises in the sense that the number of factor combinations grows substantially, far beyond What is required by e.g. a two-level fractional factorial design. For practical reasons, there may then be a need to limit the number experiments required. The generalized subset designs, GSD, is a new entry in MODDE providing a possibility to accomplish reduced designs even when handling multiple
multilevel factors. This design setup generates a series of reduced designs, subsets, that are logically linked, such that, when combined, all subsets will add up to a full multilevel multifactorial design where all factor combinations are encoded by the global design. Conceptually, the output of GSD is similar to how two-level fractional factorial designs represent complementary reductions of two-level full factorial designs.

There is a much more detailed treatment of the statistics in this publication (submitted to Analytical Chemistry): Generalized fractional factorial designs — an approach to balanced subset selections in multi-choice analytical chemistry applications, written by Izabella Surowiec, Ludvig Vikstrôm, Gustaf Hector, Erik Johansson, Conny Vikstrôm, and Johan Trygg

4. New, design from scores:
This is a typical QSAR application where a subset of molecules is selected by design. Molecules described by many variables are compressed to score vectors in SIMCA. These score vectors can then be imported directly from the SIMCA usp file.

5. MODDE 13
has excellent features in selecting less experiments with enough information for RMS, finding an optimum using quadratic terms.

6. Fit Models:
The data collected by the experimental design are used to estimate the coefficients of the model. The model represents the relationship between the response Y and the factors XI , X2, etc. MODDE uses multiple linear regression (MLR) or Partial Least Squares (PLS) to estimate the coefficients of the terms in the model. MODDE recommends
PLS when the investigation has a high condition number.

Do you wish to try MODDE Pro 13 please visit : MODDE FREE TRIAL

If you wish to have training, please visit : Sartorius Education training/courses

Do you have any questions please contact Jan Smit at


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