Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs
Abstract
:1. Introduction
2. Theoretical Background
2.1. Technology Opportunity Analysis
2.2. Technology Roadmap and Data-Driven Technology Roadmap
2.3. Data Analysis Techniques and Data-Driven Technology Roadmap
2.3.1. Bidirectional Encoder Representations for Transformers with the Data-Driven Technology Roadmap
2.3.2. Subject-Action-Object Analysis with the Data-Driven Technology Roadmap
2.3.3. Biterm Topic Model with the Data-Driven Technology Roadmap
2.3.4. Link Prediction with Data-Driven Technology Roadmap
3. Methodology
3.1. Collecting and Pre-Processing Data for Technology and Market
3.1.1. Data Collection
3.1.2. Setting the Timeframe of Data-Driven TRM
3.2. Layer Mapping
3.2.1. Classifying the Data into Layers Based on BERT
3.2.2. Semantic Analysis for the Technology Layer and Market Layer Based on SAO
3.3. Contents Mapping
3.3.1. Pre-Processing the SAO Components
3.3.2. Identify Topics of SAO Components for Technology and Market Layers Based on BTM
3.4. Opportunity Finding
3.4.1. Identify Potential Connections Based on Link Prediction
3.4.2. Integrating TRM and Analyzing Technology Opportunities
4. Illustrative Example
4.1. Collecting and Pre-Processing Data for Technology and Market
4.1.1. Data Collection
4.1.2. Setting the Timeframe of Data-Driven TRM
4.2. Layer Mapping
4.2.1. Classifying the Data into Layers Based on BERT
4.2.2. Semantic Analysis for the Technology Layer and Market Layer Based on SAO
4.3. Contents Mapping
4.3.1. Pre-Processing the SAO Components
4.3.2. Identify Topics of SAO Components for Technology and Market Layers Based on BTM
4.4. Opportunity Finding
4.4.1. Identify Potential Connections Based on Link Prediction
4.4.2. Integrating TRM and Analyzing Opportunities
5. Discussion
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Type | Data Source | Retrieval Strategy | Count |
---|---|---|---|
Paper | Medline | MH = (gout OR hyperuricemia) | 6124 |
Patent | Derwent | IP = (A61P-019/06) | 5158 |
Market | ABI | hyperuricemia | 4582 |
Time Series | Sentences | SAO Components | |||
---|---|---|---|---|---|
Original | Duplicate | Incomplete | Reserved | ||
2010–2013 | 12,161 | 9912 | 202 | 8263 | 1447 |
2014–2018 | 24,441 | 19,902 | 596 | 16,408 | 2898 |
2019–2021 | 17,424 | 13,034 | 224 | 10,812 | 1998 |
In total | 54,026 | 42,848 | 1022 | 35,483 | 6343 |
Time Series | Sentences | SAO Components | |||
---|---|---|---|---|---|
Original | Duplicate | Incomplete | Reserved | ||
2010–2013 | 4371 | 2439 | 219 | 1960 | 260 |
2014–2018 | 17,799 | 6315 | 1035 | 4767 | 513 |
2019–2021 | 9460 | 3548 | 427 | 2818 | 303 |
In total | 31,630 | 12,302 | 1681 | 9545 | 1076 |
Layer | SAO Components | Time Series | Group |
---|---|---|---|
Technology | S | 2010–2013 | T-S-TS1 |
2014–2018 | T-S-TS2 | ||
2019–2021 | T-S-TS3 | ||
A | 2010–2013 | T-A-TS1 | |
2014–2018 | T-A-TS2 | ||
2019–2021 | T-A-TS3 | ||
O | 2010–2013 | T-O-TS1 | |
2014–2018 | T-O-TS2 | ||
2019–2021 | T-O-TS3 | ||
Market | S | 2010–2013 | M-S-TS1 |
2014–2018 | M-S-TS2 | ||
2019–2021 | M-S-TS3 | ||
A | 2010–2013 | M-A-TS1 | |
2014–2018 | M-A-TS2 | ||
2019–2021 | M-A-TS3 | ||
O | 2010–2013 | M-O-TS1 | |
2014–2018 | M-O-TS2 | ||
2019–2021 | M-O-TS3 |
Technology | Market | ||||
---|---|---|---|---|---|
Group | Number of Topics | Coherence | Group | Number of Topics | Coherence |
T-S-TS1 | 9 | −45.59 | M-S-TS1 | 9 | −16.61 |
T-A-TS1 | 1 | 12.03 | M-A-TS1 | 1 | −8.79 |
T-O-TS1 | 10 | −61.45 | M-O-TS1 | 7 | −2.38 |
T-S-TS2 | 10 | −78.55 | M-S-TS2 | 9 | −35.95 |
T-A-TS2 | 2 | −30.04 | M-A-TS2 | 1 | −8.27 |
T-O-TS2 | 10 | −87.32 | M-O-TS2 | 2 | 2.24 |
T-S-TS3 | 9 | −64.03 | M-S-TS3 | 10 | −24.46 |
T-A-TS3 | 1 | −16.53 | M-A-TS3 | 1 | −26.92 |
T-O-TS3 | 9 | −70.89 | M-O-TS3 | 2 | 15.48 |
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Feng, L.; Zhao, W.; Wang, J.; Lin, K.-Y.; Guo, Y.; Zhang, L. Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs. Pharmaceuticals 2022, 15, 1357. https://doi.org/10.3390/ph15111357
Feng L, Zhao W, Wang J, Lin K-Y, Guo Y, Zhang L. Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs. Pharmaceuticals. 2022; 15(11):1357. https://doi.org/10.3390/ph15111357
Chicago/Turabian StyleFeng, Lijie, Weiyu Zhao, Jinfeng Wang, Kuo-Yi Lin, Yanan Guo, and Luyao Zhang. 2022. "Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs" Pharmaceuticals 15, no. 11: 1357. https://doi.org/10.3390/ph15111357