In recent years, tools for the development of new drugs have been dramatically improved. These include genomic and proteomic research, numerous biophysical methods, combinatorial chemistry and screening technologies. In addition, early ADMET studies are employed in order to significantly reduce the failure rate in the development of drug candidates. As a consequence, the lead finding, lead optimization and development process has gained marked enhancement in speed and efficiency. In parallel to this development, major pharma companies are increasingly outsourcing many components of drug discovery research to biotech companies. All these measures are designed to address the need for a faster time to market. New screening methodologies have contributed significantly to the efficiency of the drug discovery process. The conventional screening of single compounds or compound libraries has been dramatically accelerated by high throughput screening methods. In addition, in silico screening methods allow the evaluation of virtual compounds. A wide range of new lead finding and lead optimization opportunities result from novel screening methods by NMR, which are the topic of this review article.

Drug Discovery Today

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the const...

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Information retrieval and text mining technologies for chemistry

We present OSIRIS, an entirely in-house developed drug discovery informatics system. Its components cover all information handling aspects from compound synthesis via biological testing to preclinical development. Its design principles are platform and vendor independence, a consistent look and feel, and complete coverage of the drug discovery process by custom tailored applications. These include electronic laboratory notebook applications for biology and chemistry, tools for high-throughput and secondary screening evaluation, chemistry-aware data visualization, physicochemical property prediction, 3D-pharmacophore comparisons, interactive modeling, computing grid based ligand-protein docking, and more. Most applications are developed in Java and are built on top of a Java library layer that provides reusable cheminformatics functionality and GUI components such as chemical editors, structure canonicalization, substructure search, combinatorial enumeration, enhanced stereo perception, force field minimization, and conformation generation.

OSIRIS, an entirely in-house developed drug discovery informatics system.

Integrating Biological Databases.

https://www.elsevier.com/__data/assets/pdf_file/0008/97064/Data_driven_medicinal_chemistry.pdf

Data-driven medicinal chemistry in the era of big data

We present ABCD, an integrated drug discovery informatics platform developed at Johnson & Johnson Pharmaceutical Research & Development, L.L.C. ABCD is an attempt to bridge multiple continents, dat...

Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

Electronic health databases have become extremely valuable resources for pharmacoepidemiological and translational research, as noted in the recent Perspective article, Beyond debacle and debate: developing solutions in drug safety (Nature Rev. Drug Discov. 8, 775–779; 2009)1. Through these databases, researchers can gain a better understanding of the shortand long-term impact of exposure to drugs and devices, identify populations at risk for adverse effects, estimate the prevalence and natural history of medical conditions, and assess drug utilization across different demographic groups2–4. However, the daunting size and complexity of these databases have made them inaccessible to all but a few experts with advanced data-management and statistical programming skills. Although simpler interfaces have begun to emerge5,6, a truly integrative approach that combines convenient access with advanced analytics is still lacking. Our Advanced Biological and Chemical Discovery (ABCD) system has demonstrated the potential of such an approach in drug discovery7,8. Recently, we extended our toolset and the underlying design principles to the field of outcomes research. The solution consists of four major components. The first is a high-performance relational database with a specialized data organization and indexing strategy, which decreases the data processing time by orders of magnitude compared with traditional, file-based approaches. To facilitate cohort selection by distinct criteria such as exposure to medications or clinical diagnoses, it creates separate copies of the same data tables with different clustered indices (Box 1), thus greatly improving performance. The second is a graphical interface that allows the user to define complex queries with multiple inclusion or exclusion criteria through a series of dialogue boxes, employing language and identifiers that are familiar to epidemiologists (FIG. 1). This interface, which was implemented as a plug-in to Third Dimension Explorer (3DX)7, eliminates the need for programming expertise by hiding complex Structured Query Language (SQL) query generation, execution and post-processing. The third is 3DX itself, an intuitive data analysis and visualization environment for interactive plotting, analysis, filtering and manipulation of the query results7 (FIG. 2). Follow-up queries and more elaborate statistical assessments can be invoked through specialized routines or services available from within 3DX, or by exporting the data into an external statistical package. The final component is a rigorous evaluation of the tool’s performance, usability and versatility for different users and study types, and a strict validation of the results by comparing them with the current gold standard: customized SAS routines that are specific to the issue at hand. We found that queries requiring many hours Broadening access to electronic healthcare databases

/pdf/broadening-access-to-electronic-healthcare-databases-1i3mtgz6jc.pdf

Broadening access to electronic healthcare databases.

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Advanced biological and chemical discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world.

Broadening access to electronic healthcare databases.