In Vitro Toxicity Evaluation Using Metabolic Compatibility Rules
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Solution Overview
Problem
Conventional in silico methods for predicting metabolism or toxicity have insufficient accuracy in in vitro toxicity evaluation tests, as they do not adequately consider the relevance to the in vitro toxicity evaluation test results.
Innovation Solution
A toxicity evaluation device and method that includes a processor configured to perform data acquisition, prediction, and evaluation processing, utilizing rule data with compatibility rules suitable for in vitro toxicity evaluation tests, including reaction preconditions, stop conditions, and priorities for metabolic reactions, to enhance prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional in silico models are used for predicting metabolism or toxicity, then the prediction process can be performed, but the prediction accuracy for in vitro toxicity evaluation tests is insufficient
Solution Approach 1:
The patent changes the parameters of the prediction model by incorporating specific parameters related to in vitro toxicity evaluation tests, such as reaction preconditions, stop conditions, and priorities that reflect the actual test conditions. This allows the model to better predict metabolic reactions and toxicity outcomes that are relevant to in vitro tests, thereby improving both prediction accuracy and reliability simultaneously.
2Productivity
If metabolic reaction prediction is performed without considering in vitro test relevance, then the prediction can be completed, but the prediction accuracy for in vitro toxicity evaluation is low
Solution Approach 1:
The patent applies preliminary action by pre-defining compatibility rules that capture the essential characteristics of in vitro toxicity evaluation tests before the actual prediction process. These rules include preconditions, stop conditions, and priorities that are established in advance based on knowledge of in vitro test systems. When performing predictions, the model directly applies these pre-established rules, maintaining high prediction efficiency while ensuring the results are relevant to in vitro tests.
3Speed
If the metabolic reaction model is simplified to improve processing speed, then the prediction is faster, but the prediction accuracy for in vitro toxicity evaluation deteriorates
Solution Approach 1:
The patent segments the metabolic reaction prediction process into distinct stages with specific rules for each stage. The model divides complex metabolic pathways into manageable segments, applying appropriate preconditions, stop conditions, and priorities to each segment. This segmentation allows the model to process predictions efficiently by focusing computational resources on critical reaction steps while maintaining accuracy for in vitro toxicity evaluation through targeted application of compatibility rules.
Data Source
AI summary
A toxicity evaluation device including a processor, in which the processor is configured to perform data acquisition processing of acquiring test substance data specifying a test substance, prediction processing of predicting a metabolic reaction process of the test substance and a metabolite generated in the metabolic reaction process based on the test substance data, evaluation processing of acquiring an evaluation result by evaluating toxicity of at least one compound selected from the group consisting of the test substance and the metabolite, and output processing of outputting a processing result including the evaluation result, in the prediction processing, the processor is configured to predict the metabolic reaction process based on the test substance data and rule data specifying a rule in which a metabolic reaction proceeds, and the rule data includes a compatibility rule suitable for an in vitro toxicity evaluation test; an operation method of a toxicity evaluation device; and an operation program of a toxicity evaluation device.