Clinical Trial Design Platform for Trade-off Visual Analysis
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Solution Overview
Problem
Clinical trial design optimization is hindered by traditional methods' inability to evaluate and compare a large number of design options, often resulting in suboptimal choices due to limited capability in considering all possible variations, leading to increased costs and prolonged completion times.
Innovation Solution
A trial design platform that utilizes cloud and distributed computing to simulate hundreds of millions of study design variants, leveraging advanced simulations, visualizations, and methodological knowledge to identify optimal or near-optimal designs by evaluating and comparing hundreds, thousands, or even millions of design options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to evaluate clinical trial designs, then the evaluation process is simple and quick, but the number of design options that can be evaluated is limited, resulting in suboptimal choices
Solution Approach 1:
The patent segments the evaluation process into modular components including simulation modules, optimization modules, and visualization modules. Each module handles specific aspects of trial design evaluation, allowing the system to process millions of design options by dividing the complex evaluation task into manageable segments that can be executed independently and combined.
Solution Approach 2:
The patent introduces computational algorithms and simulation engines as intermediaries between the input trial design parameters and the output evaluation results. These intermediary computational systems automatically process and compare vast numbers of design variations, eliminating the need for manual evaluation while providing systematic, reproducible results.
2Measurement precision
If all possible design variations are evaluated to find the optimal design, then the quality of the selected design improves, but the time and computational resources required increase significantly
Solution Approach 1:
The patent applies preliminary filtering and pre-processing steps that eliminate obviously suboptimal design configurations before full evaluation. By pre-identifying and removing designs that cannot possibly meet optimization criteria, the system reduces the evaluation scope while maintaining the ability to find optimal designs among the remaining candidates.
Solution Approach 2:
The patent dynamically adjusts evaluation parameters and computational resources based on the complexity of the design space and progress of the optimization process. The system can modify simulation fidelity, sampling density, and computational allocation in real-time, allowing high-precision evaluation when needed while using reduced-precision methods for preliminary screening, thus balancing quality and time requirements.
Data Source
AI summary
A method for trial design analysis that includes receiving, for each trial design of a plurality of trial designs, a set of simulated performance criteria for a set of trial designs, and visualizing, on a graph, values for a first simulated performance criteria and a second simulated performance criteria from the set of simulated performance criteria for each trial design using a location of points on the graph corresponding to the set of trial designs. The method further includes identifying optimal designs based on an optimality criteria using the set of the simulated performance criteria, and determining a tradeoff metric for the first simulated performance criteria and the second simulated performance criteria. The method further includes displaying, the tradeoff metric as a set of lines on the graph, wherein a slope of the lines corresponds to a value of the tradeoff metric.