Change of Data-Driven Drug Design Trends Through Patent Analysis

被引:5
作者
Kim, Jong-Hyun [1 ]
Lee, Yong-Gil [1 ]
机构
[1] Inha Univ, Dept Energy Resources Engn, Incheon 22212, South Korea
关键词
data science; fourth industrial revolution; pharmaceutical; R&D; patent; innovation; technology; BIG-DATA; TECHNOLOGY; MODEL;
D O I
10.3390/pr7080492
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The pharmaceutical industry is one of the most research and development (R&D)-intensive industries. This industry has tried many strategies to overcome the limitations of a business model that had a high return and high risk. In recent years, the fourth industrial revolution has affected many industries, causing them to update their traditional production and business strategies to a "data science-based" approach. This data science methodology, based on the largely increased size of the data environment, has actively changed the pharmaceutical industry. Therefore, this study aimed to identify specific characteristics of data science innovation in the pharmaceutical industry through the analysis of patent data from the triadic patent databases from the United States, Japan, and Europe.
引用
收藏
页数:18
相关论文
共 35 条
[21]  
Kim J, 2018, SEOUL J ECON, V31, P1
[22]   Model-based clinical drug development in the past, present and future: a commentary [J].
Kimko, Holly ;
Pinheiro, Jose .
BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 2015, 79 (01) :108-116
[23]   An Optimization-Based Framework to Define the Probabilistic Design Space of Pharmaceutical Processes with Model Uncertainty [J].
Laky, Daniel ;
Xu, Shu ;
Rodriguez, Jose S. ;
Vaidyaraman, Shankar ;
Munoz, Salvador Garcia ;
Laird, Carl .
PROCESSES, 2019, 7 (02)
[24]   Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents [J].
Lee, Won Sang ;
Han, Eun Jin ;
Sohn, So Young .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2015, 100 :317-329
[25]  
LIEBOWITZ SJ, 1995, J LAW ECON ORGAN, V11, P205
[26]   Navigating the fourth industrial revolution [J].
Maynard, Andrew D. .
NATURE NANOTECHNOLOGY, 2015, 10 (12) :1005-1006
[27]   Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route [J].
Metta, Nirupaplava ;
Ghijs, Michael ;
Schafer, Elisabeth ;
Kumar, Ashish ;
Cappuyns, Philippe ;
Van Assche, Ivo ;
Singh, Ravendra ;
Ramachandran, Rohit ;
De Beer, Thomas ;
Ierapetritou, Marianthi ;
Nopens, Ingmar .
PROCESSES, 2019, 7 (04)
[28]   Lessons from 60 years of pharmaceutical innovation [J].
Munos, Bernard .
NATURE REVIEWS DRUG DISCOVERY, 2009, 8 (12) :959-968
[29]   A new chapter in pharmaceutical manufacturing: 3D-printed drug products [J].
Norman, James ;
Madurawe, Rapti D. ;
Moore, Christine M. V. ;
Khan, Mansoor A. ;
Khairuzzaman, Akm .
ADVANCED DRUG DELIVERY REVIEWS, 2017, 108 :39-50
[30]   Path dependence [J].
Page, Scott E. .
QUARTERLY JOURNAL OF POLITICAL SCIENCE, 2006, 1 (01) :87-115