Discovery informatics: its evolving role in drug discovery

被引:38
作者
Claus, BL [1 ]
Underwood, DJ [1 ]
机构
[1] BMS Pharmaceut Res Inst, Wilmington, DE 19880 USA
关键词
D O I
10.1016/S1359-6446(02)02433-9
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Drug discovery and development is a highly complex process requiring the generation of very large amounts of data and information. Currently this is a largely unmet informatics challenge. The current approaches to building information and knowledge from large amounts of data has been addressed in cases where the types of data are largely homogeneous or at the very least well-defined. However, we are on the verge of an exciting new era of drug discovery informatics in which methods and approaches dealing with creating knowledge from information and information from data are undergoing a paradigm shift. The needs of this industry are clear: Large amounts of data are generated using a variety of innovative technologies and the limiting step is accessing, searching and integrating this data. Moreover, the tendency is to move crucial development decisions earlier in the discovery process. It is crucial to address these issues with all of the data at hand, not only from current projects but also from previous attempts at drug development. What is the future of drug discovery informatics? Inevitably, the integration of heterogeneous, distributed data are required. Mining and integration of domain specific information such as chemical and genomic data will continue to develop. Management and searching of textual, graphical and undefined data that are currently difficult, will become an integral part of data searching and an essential component of building information- and knowledge-bases.
引用
收藏
页码:957 / 966
页数:10
相关论文
共 29 条
[1]  
ARGENTAR DR, 2000, 8 INT C INT SYST MOL
[2]   CLUSTERING OF CHEMICAL STRUCTURES ON THE BASIS OF 2-DIMENSIONAL SIMILARITY MEASURES [J].
BARNARD, JM ;
DOWNS, GM .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1992, 32 (06) :644-649
[3]   Computational approaches for combinatorial library design and molecular diversity analysis [J].
Blaney, JM ;
Martin, EJ .
CURRENT OPINION IN CHEMICAL BIOLOGY, 1997, 1 (01) :54-59
[4]   A rapid computational method for lead evolution:: Description and application to α1-adrenergic antagonists [J].
Bradley, EK ;
Beroza, P ;
Penzotti, JE ;
Grootenhuis, PDJ ;
Spellmeyer, DC ;
Miller, JL .
JOURNAL OF MEDICINAL CHEMISTRY, 2000, 43 (14) :2770-2774
[5]  
Brown RD, 1997, PERSPECT DRUG DISCOV, V7-8, P31
[6]  
GROVER II, 2000, PHARM SCI TECHNOL TO, V3, P50
[7]  
Grover Manish, 2000, Pharmaceutical Science and Technology Today, V3, P28, DOI 10.1016/S1461-5347(99)00214-X
[8]   DiscoveryLink: A system for integrated access to life sciences data sources [J].
Haas, LM ;
Schwarz, PM ;
Kodali, P ;
Kotlar, E ;
Rice, JE ;
Swope, WC .
IBM SYSTEMS JOURNAL, 2001, 40 (02) :489-511
[9]   Latent semantic structure indexing (LaSSI) for defining chemical similarity [J].
Hull, RD ;
Singh, SB ;
Nachbar, RB ;
Sheridan, RP ;
Kearsley, SK ;
Fluder, EM .
JOURNAL OF MEDICINAL CHEMISTRY, 2001, 44 (08) :1177-1184
[10]   Chemical similarity searches using latent semantic structural indexing (LaSSI) and comparison to TOPOSIM [J].
Hull, RD ;
Fluder, EM ;
Singh, SB ;
Nachbar, RB ;
Kearsley, SK ;
Sheridan, RP .
JOURNAL OF MEDICINAL CHEMISTRY, 2001, 44 (08) :1185-1191