Driven by the need to reduce risk and cost of clinical trials

Working closely with our long term big pharma clients, we have developed nQuery Bayes. nQuery Bayes provides researchers access to a suite of tables that allows them to formalize the use of Bayesian methodology into their clinical trial framework, most notably Bayesian Assurance, Bayesian Posterior Credibility Intervals & Mixed Bayesian Likelihood.

What is Assurance (Bayesian Power)?

The short answer is, using Assurance allows you to discover how likely it is to see the “True probability of success" from a trial, before you start it.

How does Bayesian Assurance work?
Expert opinions, together with information from previous experiments or work in similar fields holds many benefits. These can be elicited and then integrated with each other plus prior data using the Sheffield Elicitation Framework (SHELF).

nQuery Bayes allows you to easily combine all this information to receive some valuable decision making information in the form of an Assurance (A) calculation.

The benefits of Bayesian Assurance formalizing Sensitivity Analysis
Bayesian Assurance provides key contextual information on what is likely to happen over the total range possible values rather than the small number of fixed points used in a sensitivity analysis.

  • In a sensitivity analysis, a number of scenarios are chosen by the researcher and assessed individually for power or N. This gives clear indication of the merits of the individual cases highlighted but no information on other scenarios.
  • With assurance, we average the power over all plausible values by assigning prior to one or more parameters. This provides a summary statistic for the effect of parameter uncertainty but less information on specific scenarios.

Assurance is vital contextual tool in the planning toolbox. It places uncertainty at the heart of sample size determination.

Whitepaper
Bayesian Assurance: Formalizing Sensitivity
Analysis in Sample Size

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Whitepaper
Bayesian Solutions To Help Reduce
Risk & Cost in Clinical Trials

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Further Bayesian Solutions to Clinical Trial Challenges

What other industry challenges can nQuery Bayes Address?
The cost of failed clinical trials is high and the industry needs to focus on ways to reduce the continuously high failure rate. Companies need to make better decisions - back the best trials and put resources in the right place

Solution
nQuery Bayes (an nQuery add-on module) allows Bayesian calculations to address these issues. Currently in nQuery Bayes, the following methods are available to researchers:

  • Bayesian Posterior Credible Intervals
  • Mixed Bayesian Likelihood
  • Assurance 

What are the benefits to researchers?
Researchers are now able to:
● Use prior information from pilot studies and other sources to make quicker and better decisions
● Discover the likelihood of a “positive” trial outcome and then make better decisions on what trials to back

See nQuery Bayes in action with our on demand webinar

Bayesian Approaches To Improve Sample Size

  • In this 60 minute webinar hosted by Ronan Fitzpatrick, Head of Statistics at Statsols you'll learn about:

  • Bayesian Sample Size Determination: See how the growth of Bayesian analysis has helped transform our ideas about statistical inference and methodologies in clinical trials

  • Bayesian Assurance: Get an informative answer on how likely it is to see a “positive” outcome from the trial and then make better decisions on what trials to back

  • Posterior Credible Intervals and Mixed Bayesian Likelihood: Enable researchers to use prior information from pilot studies and other sources to make quicker and better decisions
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Interested in a trial
of nQuery Bayes?

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