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Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs
Lijie Feng1, Weiyu Zhao2, Jinfeng Wang3
1Logistics Engineering College, Shanghai Maritime University, 1550 Haigang Avenue, Pudong District, Shanghai 201306, China.
Pharmaceuticals (Basel, Switzerland)
|November 10, 2022
Summary
This study introduces a data-driven technology roadmap (TRM) approach to uncover new drug innovation opportunities for hyperuricemia. Key findings suggest reviving uric acid oxidase and reducing small molecule drug toxicity as promising avenues for hyperuricemia treatment.
Area of Science:
- Biotechnology and Bioinformatics
- Drug Discovery and Development
- Metabolic Diseases
Background:
- Hyperuricemia is a metabolic disease with rising incidence, necessitating novel drug innovation.
- Identifying emerging technology opportunities is crucial for advancing hyperuricemia therapeutics.
- A structured approach is needed to analyze complex data for drug development.
Purpose of the Study:
- To propose a systematic, data-driven technology roadmap (TRM) approach for identifying novel technology opportunities in hyperuricemia drug discovery.
- To leverage advanced data analysis tools for tracking technological trends and market dynamics.
- To provide actionable insights for future hyperuricemia drug development.
Main Methods:
- Utilized BERT and SAO models for mapping literature, patents, and drug data into technology and market layers.
- Employed the BTM model to identify core semantic topics within the technology and market dimensions.
- Applied a link prediction model to identify and prioritize potential technological opportunities.
Main Results:
- The data-driven TRM effectively identified potential technology opportunities for hyperuricemia drugs.
- Key opportunities include resurrecting the pseudogene of human uric acid oxidase and reducing the toxicity of small molecule drugs.
- Specific pathways for realizing these opportunities involve DNA sequence comparison and identifying critical amino acid sites.
Conclusions:
- The proposed data-driven TRM approach offers a valuable method for analyzing technology opportunities in drug discovery.
- Reviving uric acid oxidase and mitigating drug toxicity represent significant potential avenues for hyperuricemia treatment.
- Further research into genetic sequences and enzyme activity is recommended to realize these therapeutic opportunities.
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