Pharmaceutical Technology Evaluation Scoring System
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Solution Overview
Problem
The pharmaceutical industry faces challenges in evaluating opportunities and making transaction decisions due to the overwhelming complexity and scarcity of accurate market data during drug development, particularly in pre-clinical and clinical stages.
Innovation Solution
A method and system for assembling, aggregating, and interpreting multiple complex data sources to generate strategic intelligence by transforming raw data into structured schemas, drawing associations, and generating scores based on these associations, which includes assigning weights and measuring confidence in associations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple complex data sources are assembled and aggregated to evaluate pharmaceutical opportunities, then the accuracy and completeness of market data improves, but the complexity of the evaluation system increases
Solution Approach 1:
The patent segments the evaluation system into distinct modules: data import module, transformation module, ingestion module, and scoring module. Each module handles specific data processing tasks independently, allowing the system to manage complex multi-source data aggregation while maintaining organizational clarity and reducing overall system complexity.
Solution Approach 2:
The patent introduces structured schemas as intermediary data structures between raw data sources and the evaluation engine. These schemas act as mediators that standardize and organize data from multiple complex sources, enabling accurate evaluation without requiring the entire system to handle the full complexity of raw data integration.
2Reliability
If comprehensive data analysis is performed to assess drug asset value, then the quality of investment decisions improves, but the time required for evaluation increases
Solution Approach 1:
The patent performs preliminary data transformation and structuring before the actual evaluation process. By pre-processing data into standardized schemas and pre-computing associations during data ingestion, the system prepares information in advance, enabling faster and more reliable investment decisions when evaluation is needed.
Solution Approach 2:
The patent implements a scoring system that provides quantitative feedback on data quality and association strength. This feedback mechanism allows the system to efficiently identify high-value opportunities without requiring exhaustive analysis of all data, thereby reducing evaluation time while maintaining decision quality.
3Loss of information
If detailed associations are drawn between data and profiles to generate scores, then the strategic intelligence quality improves, but the computational complexity increases
Solution Approach 1:
The patent applies local quality by drawing associations specifically between data elements and relevant profiles based on contextual relevance. Rather than computing all possible associations uniformly, the system focuses computational resources on locally relevant connections, maintaining high strategic intelligence quality while reducing overall computational complexity.
Data Source
AI summary
A method for evaluating and/or scoring pharmaceutical/life science technology is provided. The method includes importing data of a publication; transforming the data into a structured schema; ingesting the structured schema to determine a context of the data and draw associations between the data and a plurality of profiles; and generating a score based on the associations between the raw data and the profiles. The method may also include generating meta-data based on the determined context of the data and/or one or more quantitative metrics having a temporal component based on the ingested data. Related apparatus, systems, techniques and articles are also described.