MODDE® — Design of Experiments Software
Design, analyze, and optimize experiments with guided DOE workflows
MODDE® design of experiments (DOE) software provides guided workflows for planning, analyzing, and optimizing experiments. Part of the Umetrics® Data Analytics Ecosystem, it helps scientists identify critical factors, understand cause-and-effect relationships, optimize multiple outcomes, and establish robust operating conditions.
By generating more information from fewer experiments, MODDE® provides structured evidence for biopharma development decisions and Quality by Design (QbD).
The business impact of design of experiments software
Repeated experimental iterations can extend development timelines and tie up manufacturing capacity. MODDE® software helps users plan efficient experimental designs, understand the impact of interdependent parameters, and identify optimal conditions sooner, reducing repeated rounds of testing.
Efficient DOE studies can generate more useful information from fewer experiments. By helping users select experiments that provide maximum value, MODDE® software can reduce unnecessary use of samples, materials, equipment time, and labor resources.
Guided workflows in MODDE® software support a structured approach to experimental design, analysis, and optimization. This makes it easier to apply DOE consistently across development teams and compare results using shared evidence.
MODDE® software helps teams use DOE to understand how expected variations can affect process outcomes before conditions are finalized or scaled up. This supports more robust development by reducing the risk of late changes, failed conditions, or rework as processes move toward larger scale.
MODDE® software helps teams get more value from every experiment by showing how different inputs and conditions work together. This supports more effective optimization, helping teams identify combinations that improve quality, yield, productivity, and other key outcomes.
Answer complex bioprocessing questions with design of experiments
Which factors influence process outcomes?
Systematically vary multiple factors to investigate causality, understand their effects on key process outcomes, and identify where interactions matter.
Which experiments will provide the most useful information?
Use efficient experimental designs to reduce unnecessary runs and maximize what you learn from the resources available.
Which conditions give the best overall result?
Model several measured outcomes together to identify the combination of conditions that best balances quality, yield, productivity, stability, or other study objectives.
Will the selected conditions remain robust?
Evaluate how process variation and measurement uncertainty could affect the selected conditions before they are finalized or scaled up.
Which operating range can be justified?
Explore the design space and acceptable operating ranges to support Quality by Design, process characterization, and control strategy development.
MODDE® software at a glance
Applications across biopharma process development
Explore how MODDE® software can support systematic experimentation across upstream and downstream process development, helping teams optimize conditions and reduce experimental iterations.
DOE capabilities
Define study objectives, factors, responses, and constraints, then select an experimental design that captures the information needed with as few experiments as possible.
Use guided analysis to evaluate experimental results, create models, and review the diagnostics needed to assess and interpret model performance.
Identify critical factors affecting process performance and establish cause-and-effect relationships between experimental conditions and responses.
Use multi-objective optimization to identify conditions that best balance several responses, such as quality, yield, productivity, and stability.
Simulate process performance across the design space to assess whether selected conditions remain acceptable when expected variation is considered.
MODDE® software in practice
Accelerate process intensification
Process intensification is becoming critical to keeping up with the global demand for mAbs, but transitioning to a perfusion process can be challenging and expensive. MODDE® software can be used to rapidly optimize parameters such as seeding concentration and media exchange rates, helping keep perfusion costs low.
Optimize media formulations
MODDE® software can be used to design experiments that determine which media components have the greatest impact on responses such as viable cell density, doubling time, and titer. Sweet spot plots can then be used to identify the optimal media composition across the tested attributes.
Improve process robustness for advanced therapies
MODDE® software can be used to simultaneously investigate the effects of multiple cell therapy process parameters, including number of activations, seeding density, seed train time, and cytokine concentration. The DOE approach enables the systematic examination of growth parameters and their interactions, while visual outputs provide clear decision support for selecting conditions that improve titer and process scalability.
Characterize chromatography performance
Chromatography performance can depend on many interdependent process factors, making it difficult to optimize. Response contour plots in MODDE® software can be used to show the influence of parameters such as sample load, pH, and conductivity on yield and impurity clearance, and to identify the conditions needed to reach target outcomes.
See how MODDE® software fits into the Umetrics® Data Analytics Ecosystem
MODDE® software supports the Build area of the Umetrics® Data Analytics Ecosystem, where teams develop process understanding and create trusted models. Explore how Build connects with Innovate, Deploy, and Elevate to enable better decision making across development and manufacturing.
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Frequently asked questions
MODDE® software is used to execute design of experiments (DOE) strategies, including planning efficient experiments, analyzing results, optimizing processes, and defining a design space with far fewer runs than trial-and-error approaches.
Design of experiments is a structured method for planning experiments that vary multiple factors systematically, so their effects and interactions can be understood efficiently from a minimal number of runs.
MODDE® software defines and explores the design space through DOE, identifying which factors drive quality and where the process should operate — directly supporting a QbD approach.
MODDE® software is used by scientists and engineers in biopharma, chemical, food, and academic research who need to optimize processes and products efficiently through structured experimentation.
