Decimaker

Software for adaptive design and Bayesian decision analysis

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.

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.

With Decimaker, you can 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 analyse dose-ranging studies using a comprehensive set of Bayesian analysis, allocation and decision procedures.

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.

Dec #1: 0.58
Pr[70mg is a clinically relevant dose]

Dec #2: 1
Pr[140mg is a clinically relevant dose]

Trial Analysis Stage

Phase II dose-ranging efficacy trial: Placebo, 14, 28, 42, 70, 98 and 140mg (N=10 each). Bayesian NDLM dose-response model.

Why is Decimaker 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 the most promising agents. They 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.