design of experiment program

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Design of Experiments Training

Targeted topics provide faster insights, leading to immediate results! Our interactive learning experience promotes real understanding of DOE methods and tools.

Stat-Ease 360 Software

SE360 augments Design-Expert software with integration with Python scripting for data analysis, new Custom Graphs, and Gaussian process models for zero-error and noisy responses.

Hosted Network Licensing Available

Our Hosted Network License allows you to run the software on multiple devices without requiring an on-premises license server. Ask us for a quote!

Design-Expert Software

Best in class design of experiments software makes R&D easy with an intuitive interface and amazing graphics. Whether you are new to DOE or a seasoned pro, you'll make breakthrough improvements with Design‑Expert software.

New-User Intro to Stat-Ease® 360 Software

A complete introduction to Stat-Ease DOE software, this free webinar provides new users with the tools needed to start planning your DOE.

A better product. An improved process. Stat-Ease, armed with an expertise in design of experiments, has been helping people make breakthroughs since 1985. Find out how our industry-leading software and multi-modal training can help you improve your bottom line.

Make the most from every experiment sm

Stat-Ease Software

Powerful tools for experimenters.

Make breakthrough improvements with Stat-Ease 360 or Design-Expert® software. Our software makes it incredibly simple to apply powerful multifactor testing tools.

Whether you are new to design of experiments or a pro, our straightforward, easy-to-use interface sits on top of a powerful statistical engine. You will not only screen for vital factors, but also locate ideal process settings for top performance & discover optimal product formulations.

The latest releases provide new Custom Graphs, a multi-response Analysis Summary view, and the ability to Import/Export data to Excel. View the software brochure here .

For information on the latest version, view our change log .

Hands-on DOE Training

Learning at your convenience.

Learn design of experiments (DOE) your way! Stat-Ease offers premium training options for Design-Expert and Stat-Ease 360 alongside general DOE education.

Take advantage of our online eLearning modules designed for self-directed DOE learning, then work through our step-by-step software tutorials . Learn more by registering for a free one-hour webinar .

For comprehensive DOE education, enroll in our highly interactive instructor-led workshops for either process DOE or mixture formulations. Experienced experts lead our hands-on, case-study based courses. Whatever your educational style, we offer training that meets your needs.

Version 23.1.8 Now Available

All subscribers of Stat-Ease software or users with an active Annual Support & Maintenance plan are eligible to install and run the latest versions of Stat-Ease 360 or Design-Expert as they are released. Check our changelog for the details on what's new, and download the latest version from the Licenses tab in your account .

The Design and Analysis of Launching Cats

Even though she hasn't taken a math class since high school, our Market Development Manager designed and ran a DOE in our booth at this year's Advanced Manufacturing Minneapolis Expo using Stat-Ease 360 software. Check out her writeup on the design and analysis of launching toy cats, and how Stat-Ease software made it easy!

2025 Public Workshop Dates Announced

We've added dates in early 2025 to our public training calendar, including a first-ever public session of our Modern DOE for Medical Devices workshop. Register now for any of our 2024-25 sessions! If you can't make the scheduled time, or if you have more than 5 people to train, contact us for options . We look forward to helping you save time and money with design of experiments!

How it works

• DOE for assay development
• DOE for media optimization
• DOE for purification process development
• Purification process development
• DNA assembly
• Case studies
• DOE training course
• DOE Masterclass
• Automation Masterclass
• Synthesis newsletter
• Dilution calculator

• Applications overview
• DOE overview
• DOE for miniaturized purification
• Assays overview
• Bioprocess development overview

Miniaturized purification

• Molecular biology overview
• Other resources
• Life at Synthace

DOE software anyone can use .

Introducing Synthace DOE, an adaptive Design of Experiments software that makes sophisticated, multifactor experiments available to anyone–all defined, executed, and analyzed in one place.

Run your first DOE.

This guided product tour will show you exactly what it’s like to use Synthace for DOE. Simply follow the prompts.

Why Synthace DOE?

Generic software for statistics

DOE without Synthace

• Lots to consider, track and calculate manually. Designs are difficult to adjust and adapt for iterative changes.
• Designs are only validated when running in the lab, so any errors could prove costly and time-consuming.
• Programming is complex and requires time and expertise. Plus tracking every step is prone to error.
• Losing track of the data needed for analysis, and wrangling multiple spreadsheets prone to human error.
• Being unable to decide which models to use for analysis. Plus, statistics tools can be hard to understand and use.

Specialized software for biologists

DOE with Synthace

• A curated list of designs for life sciences that adapt as you iterate if the intent or context changes.
• No roadblocks in the lab - in-silico simulations of your design catch and fix errors before the run.
• Accurate automation instructions generated from your design, automatically. Simply click-to-run in the lab.
• Structure and analyze DOE data and metadata without spreadsheets, and get a complete digital record of every run.
• Build models directly from results and get a summary analysis of the preferred model without statistics skills.

Run DOEs in 5 simple steps

Define, tweak, and validate your experimental design

Design, adapt and iterate your DOE designs as the intent and context change, enabled by fully adaptable, drag-and-drop DOE workflow designs and elements, including JMP imports.

Synthace's software helps you focus only on the most useful and relevant DOE designs for life sciences experiments, so you can get started more quickly and easily.

Know it will run as planned, however sophisticated it is

Preview how your designs will be executed in the lab and catch & fix any errors that could derail your experiment–from anywhere.

Synthace gives you an in-silico, step-by-step simulation of any workflow design, including error handling, so you can avoid hitting those annoying roadblocks in the lab.

Automate your DOE, even without scripting or coding experience

Synthace simulates your DOE digitally–giving time estimates, click-to-run lab automation instructions and a full digital record of your design, execution hardware, labware, data and metadata.

We integrate with multiple liquid handlers and dispensers, so you can finally use DOE software without the automation headaches.

Track and align all the data and metadata in one place, automatically

Synthace automatically structures and analyzes DOE data and metadata, so you can ditch the spreadsheets and the hours processing data.

Plus, you also get a complete digital record of every run involved in your DOE, with complete control over which datasets form part of your response analysis.

Visualize results faster with built-in response analysis

Synthace lets you build models directly from your results in a matter of clicks, with instantly generated models focused on common bioscience experiments.

That means you can run a summary analysis on your chosen model without having to use complicated statistical software.

Design of Experiments—for everyone

Synthace transforms what's possible at every stage and gives you the edge, no matter what you do. Unlock new potential with an experiment platform that's been built with R&D in mind.

Given up on DOE in the past? Not this time. Make it a reality with an experiment platform that matches your ambition for discovery.

Finally—a tool to make DOE a reliable reality

Synthace makes automation-enabled DOE possible in labs like yours. It transforms your DOE designs into the liquid handling steps your equipment needs, then gathers all of the resulting data and metadata for you. No more headaches. Just better results.

It's not just about discovery. DOE is a powerful tool for understanding and optimizing processes.

Powerful process optimization

See deeper into your processes to uncover new routes for optimization that may have been hidden from view beforehand. Make your changes, then distribute those updates across your team or wider organization via the Synthace platform.

Can you afford to carry on without DOE? Synthace can help give you the edge.

A robust tool for faster insight

Many want to use DOE, but most lack the software and automation tools to help them get there. With Synthace, you can give everyone access to this powerful methodology and give your team the edge in uncovering insight they might otherwise have been unable to see.

How biologists use Synthace DOE

'One factor at a time' won’t cut it anymore. Take advantage of the power of Design of Experiments in your specific area of bioscience.

Assay development

Run complex assay development workflows and structure your data automatically. Give yourself confidence in knowing the complexities of the assay you’ve just optimized: ideal for method transfer into screening.

Media optimization

Optimize cell growth and differentiation by understanding the full range of factors at play with far fewer experimental runs. Save time and money, and move with confidence towards better results.

Optimize your downstream process development by enabling automated analytical workflows, then letting Synthace handle the DOE designs and data structuring at the end of each run.

DOE Masterclass: Anyone can run DOEs

Nuno Leitão, PhD, Principal Scientist shares how Synthace’s own lab team manages critical jobs like DOE workflow designs, stock concentration calculations, data structuring, and analysis on a digital experiment platform.

A biologist’s guide to DOE

This guidebook demystifies Design of Experiments methodology, outlines its fundamentals and gives step by step instructions how to run DOE. You'll learn: • The top five reasons why scientists aren’t using DOE… yet • The biggest difference between DOE and “one factor at a time” (OFAT) experimentation • The three deciding factors if you should run a DOE • The six step method for planning and running a DOE • A detailed, practical example of how we’d go about creating a DOE design from scratch

Intel from DOE experts

How ai is (so close to) transforming drug discovery.

A sample-oriented approach to experiment automation

The horror of climate change is here, and labs must do their part

Design of experiments for everyone

The experimentation platform for non-statisticians, desice is a digital platform for researchers and engineers to plan, visualize and analyze experiments..

Time-Consuming Experimentation

Researchers and engineers face complex processes, requiring specialized expertise and long experimentation cycles, slowing down progress.

Limited Process Understanding

Outdated methods like one-factor-at-a-time prevent full insight into interactions between variables, leading to incomplete data and suboptimal results.

Lack of Collaboration and Integration

Current solutions often lack collaboration features and require multiple tools, complicating workflows and limiting the efficiency of team-based research.

Desice is a tool for planning and analyzing your experiments. Designed to assist researchers and engineers get experimentation done right. In providing powerful tools we help you design the optimal experiment.

Starting with an efficient and optimized experimental approach, you can significantly reduce costs and shorten the time to market. It gives you the tools, models, and confidence to analyze and present data in a precise, repeatable, and verifiable method.

What our customers are saying!

We use Desice to accelerate the learning from our R&D testing. It is simple and efficient and costs fractions of the traditional equivalent software packages. Being a web app, we also benefit from new features immediately. Fully recommend it!

Very helpful tool for a fast and easy design of experiments.

Desice offers us ideal support in the creation, evaluation and interpretation of test series. This allows us to reach our goal more quickly and draw the right conclusions from our experiments.

Jeremy Lambert

Dr. hannes kitzler, dr. michael holzwarth.

Design of Experiments Software

Free trial download. for mac and windows..

JMP ® software from SAS offers world-class capabilities for optimal design of experiments (DOE) on the desktop. Design of experiments offers a practical approach for exploring the multifactor opportunity spaces that exist in almost all real-world situations. JMP combines robust statistical analysis and dynamic visualization so you can tease out the effect of an individual factor and learn more quickly at minimum cost. JMP also includes a rich set of modeling methods.

JMP design of experiments capabilities allow you to create, analyze and understand such designs as:

• I-optimal split-plot, split-split and strip-strip.
• Full and fractional factorial.
• Response surface.
• Nonlinear and mixture designs.
• Advanced designs such as space-filling, accelerated life tests and choice.

Download Free Trial Now

Use Design of experiments capabilities in JMP to understand your opportunity space.

• Learn more about JMP.
• Discover white papers, customer stories and more when you explore the JMP website.

Contact JMP Sales

• Request Information
• [email protected]
• International Sales via Worldwide SAS Offices

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Design of Experiments (DOE) Software -  Enabling Quality by Design (QbD) 

• Cell Insights
• SIMCA®-online
• Process Analytical Technology (PAT) & Data Analytics
• Data Analytics Software
• QbD and DOE Software

DOE Software for Quality by Design (QbD) and Process Optimization

Ensure Product Robustness with Fewer Trials

When you need to ensure product robustness, define an optimal process or formula, or determine the best way to make changes or substitutions, you need a data analytics method and software tool that gives you confidence and simplifies your work. MODDE ® Design of Experiments (DOE) Software is that tool.  

Design of Experiments (DOE) is a data analytics method that helps you plan, conduct, analyze and interpret controlled tests to determine which factors exert influence over your product quality, stability or other key process attributes.  Rather than experimenting with one parameter at a time, DOE speeds up the process and helps you identify important interactions by manipulating multiple factors at the same time. 

DOE supports a quality by design (QbD) approach to product development that is favored by regulatory agencies. By building experiment certainty and reproducibility into your process, you can be confident in the robustness of your formulation and quality of your final product.

Design of Experiments Applications Across Industries  

Doe in pharma/biopharma.

DOE supports a Quality by Design (QbD) approach that helps demonstrate product robustness and determine acceptable ranges for formula composition to m...

DOE in Food & Beverage 

Doe in process industries .

DOE helps develop processes to reduce waste, improve environmental footprint and identify the best substitutions for ingredients affected by market sc...

MODDE ® Design of Experiments Software Speeds Time to Market 

Reducing the number of experiments needed to determine the right process or formula means a faster time to market.  MODDE ® DOE software helps you verify the statistical accuracy of your results, cull the data, and ensure your models are viable.  

With MODDE ® you can: 

Quickly determine the outer ranges of your experimental requirements 

Create a more accurate design space (with wizards and design templates) 

Identify the robust optimum for quality by design 

Set up subset designs and complimentary designs 

Ensure your models are viable 

Investigate all possible combinations (full factorial design)  

Clarify which portion of combinations (fractional factorial) will suffice  

MODDE ® -Q Embedded Design of Experiments

Find out how you can embed Design of Experiments into your solution and reduce the risk of human error by automating the data transfer. 

MODDE ® -Q saves you time in development, offering all the capability of MODDE ® Pro. The easy-to-use Software Development Kit (SDK) speeds up development of your own AI or ML solution and provides a user-friendly interface.

DOE EduPack 

EduPack is an educational package for academia with all you need to learn data analytics. With hands-on practical skills to solve problems and explore data, you can become the master of your data.

In Design of Experiments (DOE) you can build knowledge by setting up well planned experiments and get detailed information of how the process works. This will save you time and improve the quality of your results.

DOE Supports Quality by Design (QbD)

DOE is an essential tool to ensure products and processes satisfy Quality by Design requirements imposed by regulatory agencies.  Using a QbD approach to develop your testing process can help you reduce waste, meet compliance criteria and get to market faster.  

DOE helps you create a reliable QbD process for assessing formula robustness, determining critical quality attributes and predicting shelf life by using a few months of historical data.

Why Use a Quality By Design Approach? 

Using a Quality by Design (QbD) approach to develop the testing process and to choose the critical quality attributes for a pharmaceutical product can help to:  

Ensure products meet defined critical quality attributes 

Meet regulatory compliance criteria 

Predict formula robustness 

Reduce waste in production 

Get to market faster 

Using DOE to Optimize Processes

When it comes to creating an optimal manufacturing process that limits variation and conserves energy or resources, or a developing a new formula that is most likely to meet customer expectations, design of experiments (DOE) is an indispensable tool. 

DOE helps you to: 

Minimize the number of experiments you have to do to find the ideal formula or recipe 

Create a robust process (one that holds up to changes in environment, humidity, ingredient variation, etc.) 

Adapt a recipe for changes in ingredients or packaging needs (availability, eco-compliance, regulations, consumer trends, etc.) 

What’s the Alternative? DOE vs. Alternative Approaches 

The typical alternative to using DOE to determine which processes or formulas are contenders is the classic “COST” approach.  The COST approach, which stands for “ C hange O ne S eparate factor at a T ime” is a logical way to approach an experimentation, but it requires a lot of time and effort, and may lead to the wrong conclusions.  

COST doesn’t let you consider the interaction between investigated factors and may give you different results depending on your starting point. DOE helps shorten that process and uses advanced data analytics to help inform your decisions about which factors need to be tested.  

Another weakness of the COST approach is that it can’t define the number of runs that will be needed to find the maximum. You can only test two factors at a time and can’t define how many runs you’ll need to be sure you’ve covered all the options. 

Why using DOE is better than using a COST approach: 

• DOE suggests the correct number of runs needed (often fewer than used by the COST approach) 
• DOE provides an unbiased model for the direction to follow that is independent of start settings 
• Many factors can be used (not just two) and their interactions taken into account 

Using DOE to Predict Formula Robustness

Being able to demonstrate product robustness and deliver the intended quality of the product within allowable ranges for the claimed shelf-life period is critical for pharmaceutical manufacturers. Both international and country specific regulatory agencies, such as the FDA, pay close attention to shelf-life claims. 

Predicting formulation robustness requires a careful design of experiments that holds up under statistical analysis. Using DOE for formulation robustness studies can help you select a commercial formulation that is sufficiently robust within the acceptable ranges around the label claim to meet the shelf life stability requirements. 

Download a case study about predicting formula robustness featuring an example from Hoffmann-Roche. 

Get the Case Study

Steps to Predict Formula Robustness

Step 1: Choose the Right Measurement Factors  

Ensure that the factors selected to study can be used to predict an acceptable formulation parameter range where all the values for the assessed quality attributes will be inside the specified limits. 

Step 2: Design a Statistically Valid Study 

Consider how the factors being investigated fit into a full factorial design. For pharma companies, for example, robustness studies must be able to prove that specific critical quality attributes stay within the acceptable ranges for the entire shelf-life period. In addition: 

The study must result in a regression model that is statistically significant 

The study must provide output parameters (quality attributes) that are within predefined limits 

Step 3. Analyze the Data Using Multiple Linear Regression 

One important way to produce a valid testing model is to use a tool that makes Design of Experiments easier. For example, MODDE ® Design of Experiments Software, can help you set up multivariate formulation robustness studies that demonstrate the acceptable ranges of quality for a target composition, define the allowable edges of the composition range, and predict the stability requirements needed to reach the end of shelf life. 

Learn More About Using Design of Experiments

Past Webinars & Videos 

Find out more about using MODDE ® for Design of Experiments in one of our recorded webinars. 

Design of Experiments (DOE) for the Beginner

Lean and Clean Using One Click Analysis

Finding the Optimal Design Space

Scientific investigations involve changing a number of controlled variables to direct the response in question towards a desired level. Design of Experiments (DOE) is a rational and cost-effective approach to practical experimentation that allows the effect of variables to be assessed using only the minimum of resources. DOE is the backbone for efficient QbD implementation strategies. The final specifications for a region where all specifications are fulfilled to a defined risk level is called Design Space. Determining the optimal Design Space is a key advantage of using MODDE ® DOE Software. 

Find a Course

EduPack Design of Experiments (DOE)

The education package will take students on a journey to discover, how DOE and QbD can be applied to solve problems and bring new insights to their field of application. With EduPack students get the best education in DOE for generating good results.

EduPack Design of Experiments

Doe edupack is designed to give students hands-on skills to solve problems and learn:.

• How to create efficient experimental designs to match the objectives
• How to analyze data based on sound statistical principals to evaluate results of the experiments
• How to interpret results by using graphical and statistical tools
• How to convert modeling results into concrete action with MODDE ® optimizer & verifying experiments
• How to define a design space and find robust setpoints  

Download Brochure

Related Topics

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How Is DOE Used In Process Industries?

When it comes to creating an optimal manufacturing process that limits variation and conserves energy or resources, or a developing a new formula that...

Why DOE Is Essential in the (Bio)Pharma Industry

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