Cargando…
Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs
Hyperuricemia is a metabolic disease with an increasing incidence in recent years. It is critical to identify potential technology opportunities for hyperuricemia drugs to assist drug innovation. A technology roadmap (TRM) can efficiently integrate data analysis tools to track recent technology tren...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694917/ https://www.ncbi.nlm.nih.gov/pubmed/36355529 http://dx.doi.org/10.3390/ph15111357 |
_version_ | 1784837925987418112 |
---|---|
author | Feng, Lijie Zhao, Weiyu Wang, Jinfeng Lin, Kuo-Yi Guo, Yanan Zhang, Luyao |
author_facet | Feng, Lijie Zhao, Weiyu Wang, Jinfeng Lin, Kuo-Yi Guo, Yanan Zhang, Luyao |
author_sort | Feng, Lijie |
collection | PubMed |
description | Hyperuricemia is a metabolic disease with an increasing incidence in recent years. It is critical to identify potential technology opportunities for hyperuricemia drugs to assist drug innovation. A technology roadmap (TRM) can efficiently integrate data analysis tools to track recent technology trends and identify potential technology opportunities. Therefore, this paper proposes a systematic data-driven TRM approach to identify potential technology opportunities for hyperuricemia drugs. This data-driven TRM includes the following three aspects: layer mapping, content mapping and opportunity finding. First we deal with layer mapping. The BERT model is used to map the collected literature, patents and commercial hyperuricemia drugs data into the technology layer and market layer in TRM. The SAO model is then used to analyze the semantics of technology and market layer for hyperuricemia drugs. We then deal with content mapping. The BTM model is used to identify the core SAO component topics of hyperuricemia in technology and market dimensions. Finally, we consider opportunity finding. The link prediction model is used to identify potential technological opportunities for hyperuricemia drugs. This data-driven TRM effectively identifies potential technology opportunities for hyperuricemia drugs and suggests pathways to realize these opportunities. The results indicate that resurrecting the pseudogene of human uric acid oxidase and reducing the toxicity of small molecule drugs will be potential opportunities for hyperuricemia drugs. Based on the identified potential opportunities, comparing the DNA sequences from different sources and discovering the critical amino acid site that affects enzyme activity will be helpful in realizing these opportunities. Therefore, this research provides an attractive option analysis technology opportunity for hyperuricemia drugs. |
format | Online Article Text |
id | pubmed-9694917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96949172022-11-26 Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs Feng, Lijie Zhao, Weiyu Wang, Jinfeng Lin, Kuo-Yi Guo, Yanan Zhang, Luyao Pharmaceuticals (Basel) Article Hyperuricemia is a metabolic disease with an increasing incidence in recent years. It is critical to identify potential technology opportunities for hyperuricemia drugs to assist drug innovation. A technology roadmap (TRM) can efficiently integrate data analysis tools to track recent technology trends and identify potential technology opportunities. Therefore, this paper proposes a systematic data-driven TRM approach to identify potential technology opportunities for hyperuricemia drugs. This data-driven TRM includes the following three aspects: layer mapping, content mapping and opportunity finding. First we deal with layer mapping. The BERT model is used to map the collected literature, patents and commercial hyperuricemia drugs data into the technology layer and market layer in TRM. The SAO model is then used to analyze the semantics of technology and market layer for hyperuricemia drugs. We then deal with content mapping. The BTM model is used to identify the core SAO component topics of hyperuricemia in technology and market dimensions. Finally, we consider opportunity finding. The link prediction model is used to identify potential technological opportunities for hyperuricemia drugs. This data-driven TRM effectively identifies potential technology opportunities for hyperuricemia drugs and suggests pathways to realize these opportunities. The results indicate that resurrecting the pseudogene of human uric acid oxidase and reducing the toxicity of small molecule drugs will be potential opportunities for hyperuricemia drugs. Based on the identified potential opportunities, comparing the DNA sequences from different sources and discovering the critical amino acid site that affects enzyme activity will be helpful in realizing these opportunities. Therefore, this research provides an attractive option analysis technology opportunity for hyperuricemia drugs. MDPI 2022-11-03 /pmc/articles/PMC9694917/ /pubmed/36355529 http://dx.doi.org/10.3390/ph15111357 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Feng, Lijie Zhao, Weiyu Wang, Jinfeng Lin, Kuo-Yi Guo, Yanan Zhang, Luyao Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs |
title | Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs |
title_full | Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs |
title_fullStr | Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs |
title_full_unstemmed | Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs |
title_short | Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs |
title_sort | data-driven technology roadmaps to identify potential technology opportunities for hyperuricemia drugs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694917/ https://www.ncbi.nlm.nih.gov/pubmed/36355529 http://dx.doi.org/10.3390/ph15111357 |
work_keys_str_mv | AT fenglijie datadriventechnologyroadmapstoidentifypotentialtechnologyopportunitiesforhyperuricemiadrugs AT zhaoweiyu datadriventechnologyroadmapstoidentifypotentialtechnologyopportunitiesforhyperuricemiadrugs AT wangjinfeng datadriventechnologyroadmapstoidentifypotentialtechnologyopportunitiesforhyperuricemiadrugs AT linkuoyi datadriventechnologyroadmapstoidentifypotentialtechnologyopportunitiesforhyperuricemiadrugs AT guoyanan datadriventechnologyroadmapstoidentifypotentialtechnologyopportunitiesforhyperuricemiadrugs AT zhangluyao datadriventechnologyroadmapstoidentifypotentialtechnologyopportunitiesforhyperuricemiadrugs |