Category Archives: Future-oriented technology analysis

Nano-enabled Drug Delivery in Cancer Therapy: Literature Analysis Using the MeSH System

Biomedical literature provides abundant knowledge on R&D development and emerging themes and techniques to researchers and to enhance clinical treatment. Tracing research topic activity and researcher connections, and understanding evolving research landscapes, supports identification of research domain potential and informs R&D portfolio management. Methods: We offer a systematic approach to summarize biomedical research information compiled from the MEDLINE database. Selected MeSH qualifiers are applied as properties for clustering terms. Linkages among clusters are measured based on an object–attribute–value, relative research concentration. By arraying selected technical dimensions against each other, we enable identification and evaluation of latent connections. Results: 10354 MEDLINE records from 2000 to 2013 on nano-enabled drug delivery (NEDD) for cancer treatment are retrieved and analyzed. Seven topical clusters are generated with relatively clear boundaries. Elements with high relative research concentration but low number of records show emerging trends. And the concentrations’ decline indicates the universalization of drugs and nano components in cancer treatment. Conclusions: This systematic topical analysis process helps explore particular technological trends and potentials in biomedical areas. It combines an algorithm to reveal latent connections hidden in literature text content with expert judgement. From the standpoint of technology assessment, it provides researchers and administrators the ability to capture biomedical research dynamics.

http://www.eurekaselect.com/144824/article

Author(s): Tejraj M Aminabhavi, Jing Ma and Alan L Porter
Organization(s): Shree Dhanvantary Pharmacy College
Source: Pharmaceutical Nanotechnology
Year: 2016

A methodology for technology trend monitoring: the case of semantic technologies

This paper introduces a systematic technology trend monitoring (TTM) methodology based on an analysis of bibliometric data. Among the key premises for developing a methodology are: (1) the increasing number of data sources addressing different phases of the STI development, and thus requiring a more holistic and integrated analysis; (2) the need for more customized clustering approaches particularly for the purpose of identifying trends; and (3) augmenting the policy impact of trends through gathering future-oriented intelligence on emerging developments and potential disruptive changes. Thus, the TTM methodology developed combines and jointly analyzes different datasets to gain intelligence to cover different phases of the technological evolution starting from the ‘emergence’ of a technology towards ‘supporting’ and ‘solution’ applications and more ‘practical’ business and market-oriented uses. Furthermore, the study presents a new algorithm for data clustering in order to overcome the weaknesses of readily available clusterization tools for the purpose of identifying technology trends. The present study places the TTM activities into a wider policy context to make use of the outcomes for the purpose of Science, Technology and Innovation policy formulation, and R&D strategy making processes. The methodology developed is demonstrated in the domain of “semantic technologies”.
http://link.springer.com/article/10.1007/s11192-016-2024-0

Author(s): Oleg Ena, Nadezhda Mikova, Ozcan Saritas, Anna Sokolova
Organization(s): National Research University Higher School of Economics
Source: Scientometrics
Year: 2016

S-Curve analysis and technology life cycle. Application in series of data of articles and patents

In this article, the methodology of curves in S is applied in series of data on articles in Biotechnology and Nanotechnology since 1956 obtained from the ISI Web of Science and of patents since 1962 (year of priority) and 1970 (year of publication). Belonging to controlled release, of the medical context, the data was obtained from a Tech Mining approach using the Vantage Point software tool. With the accumulated data, in time, nonlinear regression was achieved and the inflection point in the two series was calculated, taking into account the statistical parameters like Fitted R2, Value T, Value P, and Durbin Watson. The data of the articles and patents were analyzed under the following models: Weibull, Gompertz, Logistic and Sigmodial, among others, for a total of 13 models analyzed. The models with the best fit in the inflection point were selected. In the series of data from the articles, one of the models that had the best fit was the Sigmoidal model. The Sigmoidal model contained three parameters which generated a value of 33.4 for the inflection point for the year of the studied series. With the obtained values for the inflection points in the series of articles and patents, the uncertainty can be reduced in the making of decisions about the Technology Life Cycle (TLC), especially in the following aspects: the identification of the kind of technology (before and after of the inflection point), the determination of the suitable moment to apply technological rights and intellectual property, and the establishment of strategies for monitoring (when the technology is emerging) and investment.

Full-text available at http://www.revistaespacios.com/a16v37n07/16370719.html

Author(s): Jhon Wilder ZARTHA Sossa; Fernando PALOP Marro; Bibiana ARANGO Alzate; Fabián Mauricio VELEZ Salazar; and Andres Felipe AVALOS Patiño
Organization(s): Universidad Pontificia Bolivariana,  Universidad Politécnica de Valencia
Source: Espacios
Year: 2015

Subject–action–object-based morphology analysis for determining the direction of technological change

Morphology analysis, despite being a strong stimulus for the development of new alternatives, largely relies on domain experts and neglects the relationships between keywords in the construction of morphological structures. In addition, there are few systematic approaches to prioritize the morphological configurations. To address these issues, a hybrid approach is proposed, which enhances the performance of morphology analysis by combining it with subject–action–object (SAO) semantic analysis. Initially, a keyword co-occurrence patent set for subsequent SAO analysis is prepared based on keywords frequency vector analysis. Then, SAO structures are extracted and semantic analysis is performed to identify the relationships between keywords, which help to build morphological structures more objectively. In addition, a well-defined evaluation system that contains eight sub-indexes is proposed to evaluate the morphological configurations. Finally, to demonstrate and validate the proposed approach, the dye-sensitized solar cells technology is employed as the case study. Results indicate that the most promising combination we predict appears frequently in 2012–2014 and the distribution of it is also close to the fact in 2012–2014. Accordingly, the proposed method can be used to effectively determine the direction of technological change and to forecast technology innovation opportunities.

http://www.sciencedirect.com/science/article/pii/S0040162516000299

Author(s): Junfang Guo, Xuefeng Wang, Qianrui Li, Donghua Zhu
Organization(s): Beijing Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2016

Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research

Highlights

  • Data-driven clustering approach to group topics with high accuracy
  • Similarity measure approach to trace the interaction between topics in time series
  • Analyzing changes of TFIDF values of related topics to predict future trends
  • Technology Roadmapping to blend historical analysis and expert-based forecasting

The number and extent of current Science, Technology & Innovation topics are changing all the time, and their induced accumulative innovation, or even disruptive revolution, will heavily influence the whole of society in the near future. By addressing and predicting these changes, this paper proposes an analytic method to (1) cluster associated terms and phrases to constitute meaningful technological topics and their interactions, and (2) identify changing topical emphases. Our results are carried forward to present mechanisms that forecast prospective developments using Technology Roadmapping, combining qualitative and quantitative methodologies. An empirical case study of Awards data from the United States National Science Foundation, Division of Computer and Communication Foundation, is performed to demonstrate the proposed method. The resulting knowledge may hold interest for R&D management and science policy in practice.

http://www.sciencedirect.com/science/article/pii/S0040162516000160

Author(s): Yi Zhang, Guangquan Zhang, Hongshu Chen, Alan L. Porter, Donghua Zhu, Jie Lu
Organization(s): University of Technology Sydney, Georgia Institute of Technology, Beijing Institute of Technology
Source: Technological Forecasting and Social Change
Year: 2016

Semantic-Based Technology Trend Analysis

Technology trend analysis offers a flexible instrument to understand both opportunity and competition for emerging technologies. Semantic information is used in Science, Technology & Innovation (ST&I) records which makes the technology trend analysis more challenging. This paper proposes a semantic-based approach for technology trend analysis through emphasizing Subject-Action-Object (SAO) structure, It also applies the trend analysis approach to extract technology information and identify and predict the trend of technology development more effectively. An empirical study on Graphene is completed to demonstrate the proposed trend analysis approach.

http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=7383052&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D7383052

Author(s): Yang, Chao ; Zhu, Donghua ; Zhang, Guangquan
Organization(s): Beijing Institute of Technology, University of Technology Sydney
Source:  2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
Year: 2015

Navigating the innovation trajectories of technology by combining specialization score analyses for publications and patents: graphene and nano-enabled drug delivery

In this study, we combine the specialization scores for publications and patents (the latter is a new indicator of cross-disciplinary engagement) to achieve more comprehensive navigation of the innovation trajectory of a technology. The patent specialization score draws upon counterpart research publication indicator concepts to measure patent diversity. Two nano-based technologies—Nano-enabled drug delivery (NEDD) and Graphene—provide contrasting explorations of the behavior of this indicator, alongside research publication indicators. Results show distinctive patterns of the two technologies and for the respective publication and patent indicators. NEDD research, as evidenced by publication and citation patterns, engages highly diverse research fields. In contrast, NEDD development, as reflected in patent International Patent Classifications (IPCs), concentrates on relatively closely associated fields. Graphene presents the opposite picture, with closely linked disciplines contributing to research, but much more diverse fields of application for its patents. We suggest that analyzing the field diversity of research publications and patents together, employing both specialization scores, can offer fruitful insights into innovation trajectories. Such information can contribute to technology and innovation management and policy for such emerging technologies.

http://link.springer.com/article/10.1007%2Fs11192-015-1826-9

Author(s): Seokbeom Kwon, Alan Porter, Jan Youtie
Organization(s): Georgia Institute of Technology
Source: Scientometrics
Year: 2016

Identification of technology development trends based on subject-action-object analysis: The case of dye-sensitized solar cells

Identification of technology development trends is essential for supporting decision makers in forecasting and identifying related innovation activities and industrial growth. Different from the traditional technology development trends based on keyword-based quantitative methods, which usually predict trends by finding key technologies without showing how to develop them, our method allows the identification of future direction and industry goal for the technology domain and shows detailed paths for achieving them. Thus, our method has constructed technology roadmapping (TRM) with seven layers (material, technology, influencing factor, component, product, goal, and future direction) on the basis of subject–action–object analysis. The detailed paths for developing this as a trend can be shown by the interaction among these TRM elements. In addition, the method also sets three indicators as a discriminating standard to find key players that can support the trend by engaging technological innovation scenarios. The case of a dye-sensitized solar cell (DSSC) is exemplified to illustrate the detailed procedure of our method. The results reveal the development trends in the field of DSSCs, the detailed paths to achieve them, and key countries that support them.

http://www.sciencedirect.com/science/article/pii/S004016251500133X

Author(s):  Xuefeng Wang, Pengjun Qiu, Donghua Zhu, Liliana Mitkova, Ming Lei, Alan L. Porter
Organization(s): Beijing Institute of Technology, Georgia Tech
Source: Technological Forecasting and Social Change
Year: 2015

Advancing the forecasting innovation pathways approach: hybrid and electric vehicles case

The forecasting innovation pathways (FIP) approach combines empirical tech mining with expert opinion. To date, FIP has been devised for relatively immature emerging technologies. This study extends the FIP methodology to work for a more advanced and complicated technology. It does so through a case analysis of hybrid and electric vehicles (HEVs). We retain the ten-step FIP process, augmenting several steps to deal with this more complex technology and technology delivery system (TDS). In particular, it is vital to address TDS sub-systems and attendant technical and market infrastructures. The key method to explore future prospects for the technology in question is an interactive workshop. Splitting into multiple workshop sub-groups proved constructive in addressing target markets and regional variations in innovation systems and policy options. The paper derives methodological suggestions to enrich FIP to address more complex technologies regarding scoping, sub-systems analyses, and ways to systematise key operations.

http://www.inderscienceonline.com/doi/abs/10.1504/IJTM.2015.072975

Author(s): Alan L. Porter, Scott W. Cunningham, Alejandro Sanz
Organization(s): Georgia Tech, Delft University of Technology
Source: International Journal of Technology Management
Year: 2015

Evaluation of the Development of R&D into Parkinson’s Disease through Technology Monitoring Using Patent Documents and Scientific Articles

Characterized as a progressive neurodegenerative disease caused by the loss of dopaminergic neurons in the substantia nigra, Parkinson’s disease is affecting an ever greater number of people around the world as global life expectancy rises. As the disease progresses, it has physical, mental, emotional, social, and economic impacts on the patient, eroding their quality of life. Many studies have been done to understand what leads to the onset of the disease and to develop treatments or even prevention. This study uses technology foresight by identifying patents and scientific articles related to drugs for the treatment of the disease with the purpose of assessing the progress of research over time and map out the countries and companies that control the related technologies.

Full-text available at http://www.ijrpb.org/pdf/v2-i3/4.pdf

Author(s): Karinne Marieta Carvalho , Eduardo Winter , Adelaide Maria de Souza Antunes
Organization(s): Federal University of Rio de Janeiro and National Institute of Industrial Property
Source: International Journal of Research in Pharmacy and Biosciences
Year: 2015