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      Can literature analysis identify innovation drivers in drug discovery?

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      Nature Reviews. Drug Discovery
      Nature Publishing Group UK

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          Key Points

          • Drug discovery has traditionally responded to the 'pull' of unmet medical need and commercial potential. Here, we evaluate the scientific areas that are providing 'push' in terms of scientific innovation, as measured by publications and patents.

          • The amount of funding from the US National Institutes of Health, the number of doctoral degrees awarded, the number of publications and the number of approvals for new molecular entities issued by the US Food and Drug Administration show a general upward trend from the 1950s to the present. Although explanations can be suggested for some of the short-term ups and downs, these trends are also affected by numerous hidden variables, and well as time lags, feedback loops and other complications.

          • The numbers of publications in various disease areas correlate well with global disease burden.The correlation is greater in the developed world, where the impact of infectious and parasitic diseases, respiratory infections and infant mortality, is considerably lower than in the developing world.

          • A few therapeutic areas stand out when analysing trends in publications, citations, publications in high-impact journals and patents. Oncology is the clearest outlier on almost every metric. Viruses, nutrition and metabolism, and the immune system also show increases in the majority of metrics.

          • In terms of individual diseases, insulin resistance, orthomyxoviridae infections, depression, autism, macular degeneration, inflammation, obesity, cognitive disorders and ventricular dysfunction have strong publication growth in both 2- and 5-year periods. Publications related to the genes encoding forkhead box P3, leucine-rich repeat kinase 2, janus kinase 2, transcription factor 7-like 2, interleukin-17A, toll-like receptor 2 (TLR2), TLR4, FK506 binding protein 12-rapamycin associated protein 1and ADIPOQ (adiponectin, C1Q and collagen domain-containing) show the strongest publication growth in the same periods.

          • Assessing scientific innovation is a complex endeavour; however, the 'bibliome' seems to offer many approaches that could enhance decision-making in drug discovery.

          Supplementary information

          The online version of this article (doi:10.1038/nrd2973) contains supplementary material, which is available to authorized users.

          Abstract

          Here, the authors use bibliometrics and related data-mining methods to analyse PubMed abstracts, literature citation data and patent filings. The analyses are used to identify trends in disease-related scientific activity that are likely to give new therapeutic opportunities.

          Supplementary information

          The online version of this article (doi:10.1038/nrd2973) contains supplementary material, which is available to authorized users.

          Abstract

          Drug discovery must be guided not only by medical need and commercial potential, but also by the areas in which new science is creating therapeutic opportunities, such as target identification and the understanding of disease mechanisms. To systematically identify such areas of high scientific activity, we use bibliometrics and related data-mining methods to analyse over half a terabyte of data, including PubMed abstracts, literature citation data and patent filings. These analyses reveal trends in scientific activity related to disease studied at varying levels, down to individual genes and pathways, and provide methods to monitor areas in which scientific advances are likely to create new therapeutic opportunities.

          Supplementary information

          The online version of this article (doi:10.1038/nrd2973) contains supplementary material, which is available to authorized users.

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          Most cited references45

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          Drugs for bad bugs: confronting the challenges of antibacterial discovery.

          The sequencing of the first complete bacterial genome in 1995 heralded a new era of hope for antibacterial drug discoverers, who now had the tools to search entire genomes for new antibacterial targets. Several companies, including GlaxoSmithKline, moved back into the antibacterials area and embraced a genomics-derived, target-based approach to screen for new classes of drugs with novel modes of action. Here, we share our experience of evaluating more than 300 genes and 70 high-throughput screening campaigns over a period of 7 years, and look at what we learned and how that has influenced GlaxoSmithKline's antibacterials strategy going forward.
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            NETWORKS OF SCIENTIFIC PAPERS.

            D. Price (1965)
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              A well adapted regulatory contrivance: regulatory T cell development and the forkhead family transcription factor Foxp3.

              The random generation of antigen receptors in developing lymphocytes results in a considerable risk of autoimmunity. Regulatory T cells (T(reg) cells) act in a dominant, trans-acting way to actively suppress immune activation and maintain immune tolerance. Here, we discuss the principal advances in our understanding of the molecular mechanisms of T(reg) cell development and function with particular emphasis on the forkhead transcription factor Foxp3. Accumulating evidence suggests that T(reg) cells represent a dedicated T cell lineage and that Foxp3 functions as the T(reg) cell lineage specification factor. The aggressive early-onset lymphoproliferative syndrome resulting from Foxp3 deficiency identifies T(reg) cells as vital mediators of immunological tolerance to self and Foxp3 as the mediator of the genetic mechanism of dominant tolerance.
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                Author and article information

                Contributors
                Pankaj.Agarwal@gsk.com
                Journal
                Nat Rev Drug Discov
                Nat Rev Drug Discov
                Nature Reviews. Drug Discovery
                Nature Publishing Group UK (London )
                1474-1776
                1474-1784
                2009
                : 8
                : 11
                : 865-878
                Affiliations
                GRID grid.418019.5, ISNI 0000 0004 0393 4335, Computational Biology Department, , GlaxoSmithKline Pharmaceuticals, ; 709 Swedeland Road, PO BOX 1539, King of Prussia, 19406 Pennsylvania USA
                Article
                BFnrd2973
                10.1038/nrd2973
                7097144
                19876041
                7c75ec91-0a50-4e19-9e19-6924921f12ad
                © Nature Publishing Group 2009

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

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                © Springer Nature Limited 2009

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