Clinical Data Comparison for Real-World Therapy Analysis
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Solution Overview
Problem
The efficient use of real-world data (RWD) in medical drug development is hindered by the enormous volume and unstructured nature of the data, requiring significant temporal and human resources for analysis, making it difficult to grasp therapy situations and drug efficacy across all patients.
Innovation Solution
A computer system that aggregates and analyzes clinical and non-clinical data using a processor, storage device, and communication interface to generate comparative data, facilitating efficient statistical analysis and extraction of relevant clinical data for therapy situation and drug efficacy investigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all real-world data from clinical sites is analyzed to grasp therapy situations and drug efficacy, then analysis coverage is improved, but temporal and human costs increase enormously
Solution Approach 1:
The patent segments the enormous real-world data into manageable units by selecting only necessary data elements (item A) related to therapy situations and drug efficacy, rather than processing all available data. This segmentation enables comprehensive analysis coverage while reducing temporal and human costs by focusing only on relevant data portions.
Solution Approach 2:
The patent extracts and selects only the essential data elements (item A) from the vast real-world data database, separating useful information from unnecessary data. This extraction process maintains analysis coverage for therapy situations and drug efficacy while dramatically reducing the volume of data requiring temporal and human resources for processing.
2Measurement precision
If all real-world data from clinical sites is analyzed to grasp therapy situations and drug efficacy, then analysis coverage is improved, but human resources required increase enormously
Solution Approach 1:
The patent segments the analysis task by identifying and processing only necessary data elements (item A) related to therapy situations and drug efficacy, rather than manually processing all real-world data. This segmentation reduces the quantity of human resources needed while maintaining comprehensive analysis coverage.
Solution Approach 2:
The patent extracts and processes only the essential data elements (item A) from the vast real-world data, separating critical information from redundant data. This extraction significantly reduces the human resources required for analysis while preserving complete coverage of therapy situations and drug efficacy.
3Ease of operation
If real-world data is structured and processed for analysis, then data usability is improved, but data processing complexity increases
Solution Approach 1:
The patent extracts and structures only the necessary data elements (item A) from unstructured real-world data, transforming them into usable structured format. This approach improves data usability for therapy situation and drug efficacy analysis while limiting processing complexity to only the essential data transformation tasks rather than processing entire datasets.
Data Source
AI summary
A computer system is coupled for access to a first database that stores clinical data including, as an item, information acquired on a clinical site and relating to a patient provided with a therapy and a second database that stores non-clinical data including, as an item, information acquired for an investigation purpose and relating to a patient group provided with a therapy. The computer system selects a predetermined number of pieces of the clinical data from the first database, and aggregate the selected predetermined number of pieces of the clinical data, to thereby generate comparative data; and executes, through use of the non-clinical data and the comparative data which are the same in therapy content, statistical analysis for analyzing a difference in the item.