Quantify the probability of success in Clinical research Make better Decisions on Drugs

Software for adaptive design and Bayesian decision analysis

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What is Decimaker?

Decimaker is an innovative statistical software for the adaptive design and the Bayesian decision analysis of clinical trials. Pharmaceutical and biotechnology companies use Decimaker to design and simulate adaptive trials. With Decimaker, they estimate in real-time the probability of success in the study, and adjust its course accordingly. A user-friendly graphical interface enables to simulate, compare and analyze dose-ranging studies using a comprehensive set of Bayesian analysis, allocation and decision procedures.

Why is it important?

Pharmaceutical companies want to accelerate the development of novel therapies, making better go/no go decisions and selecting doses faster. They want to terminate failed compounds sooner to allocate resources to most promising agents. The want to avoid failed studies by making sure that each dollar invested in a trial will generate decision-enabling information. Adaptive designs and Bayesian methods permit a dynamic monitoring of clinical research, controlling the information collected towards decision making. Decimaker helps pharmaceutical decision makers to get the best return on investment by maximizing the quality of clinical data and minimizing information gathering costs.

Who should use it?

Decimaker is designed for analysts, technical experts and deciders involved in pharmaceutical clinical trials. In a single interface, it integrates a complete trial design and simulation platform, Bayesian analysis capabilities and a decision-enabling toolbox. Adopting new software across a large organization can be challenging. That is why Decimaker offers all capabilities in the same package, making it easy for you to work as a team on a trial project and to move it along from the design to the implementation stage.

Under the FDA critical path initiative, pharmaceutical companies are adopting new strategies to bring innovative medicines to the market.

Using adaptive design and Bayesian decision analyses, the return on clinical research investments may be much improved, leading to better go/no go decisions, faster dose selections and avoiding failed studies.

Decimaker software from ClinBAY brings powerful Bayesian adaptive design and decision analysis methods to the pharmaceutical professional desktops.

Designed to assist clinical development teams during protocol design, study implementation and analysis, Decimaker handles innovative adaptive designs, complex Bayesian analysis and decision-making solutions with a user-friendly graphical interface. Decimaker is an optimized and comprehensive solution to drug development .

With Decimaker, you enjoy the full power of R and OpenBUGS statistical analysis programs enhanced with a tailored process flow and graphical interface that simplifies your work.

Decimaker simulation and analysis results are visualized graphically to assist decision makers to quantify probability of success and take the best decision for their drugs.

  

Trial analysis stage: Bayesian modeling of interim dose-response data leading to optimized adaptive allocation of next doses and estimation of probability of success.

Features & Screenshots of DeciMaker

User-friendly graphical interface in Microsoft .NET

The graphical power of Microsoft .NET Framework used to build pretty-looked interface and visual effects.

Customized R and Winbugs analytics running behind the Decimaker user interface:

• Allow all users to get started quickly
• Require no previous programming knowledge
• Present point-and-click option: selection boxes, menus, formula and radio buttons
• Offer quality-proven R processing for data import, matrix manipulation, calculus and optimisation, plus many standard features of Winbugs for baysian estimation using MCMC.

Efficient study workflow to build and share clinical trial projects in teams.

• Instant sharing of project files (*.dcm) including design plans, data and analysis results using import/export facilities
• Import and visualize standard data files (text, Excel and comma-separated formats)
• Modular integration of data, modeling, adaptive allocation, decision and trial simulation components
• One-click transition of a project from the “design” stage to the “implementation” stage.
• Ability to lock data and analysis plan modules, upon approval of a study protocol.

Modern statistical methods implemented:

Bayesian dose-response models for binary and continuous endpoints.

 

Select and parameterize an analysis model among a large set of bayesian models, available for:
• Binary and continuous normal responses
• ANOVA, linear regression, logistic regression, non-linear models (e.g, Emax) and semi-parametric models (e.g., Normal Dynamic Linear Model)
• Vast choice of prior distributions, including normal, gamma, log-normal, beta, and many more…
Preview the model fit on data and doses prediction with your model

 

Response-adaptive allocation methods

• Choose among several criteria the most relevant allocation method for your project: CRM, D-optimal, C-Optimal, variance of target responses.
• Customize the allocation technique to benchmark your drug to a negative, positive control, an historical reference or a fixed one.
• Define flexibly the size and content of each cohort, being enrolled chronoligically into the study.
• Choose your Allocation algorithm: play-the-winner, biased-coin, urn, or highest.
• Display the allocation rule objective function across all doses (red line)
• View results of the allocation of subjects across doses of the selected next cohort proposition
• Generate adaptive randomisation tables and simulate next cohort of data, as you wish

Easy reporting using interactive graphics and summary tables.

• Link points in a graph to data in the corresponding table for easy viewing
• Produces esay-to-understand summaries for trial simulations and analyses
• Change plot settings to customize your graphes
• Export options to easily insert results in your reports

Generates R & OpenBUGS scripts for data analysis & post-hoc processing.

The results menu offers possibility to export results in many formats, including R and OpenBUGS.

 

Use simulations to learn and compare the operational characteristics of various trials proposals

• Many trial scenarios may be constructed, including data simulation plans, analysis methos, allocation and decision rules
• Multiple-art studies are possible, considering custom decision-trees to go from one to the next part
• Simple to interpret tabular and graphical display of power curves, sample size, allocation summaru,model adjustment and relative efficiency to a standard design
• Simulate-at-interim capability to quantify predictive power of various options and make the best decisions.