Tuesday 24 Oct

Using analytical methods are more and more replacing database searching in a knowledge manager's daily activities. In this presentation various facets of publication analysis will be presented and discussed. These new methods were applied for the analysis of publications in scientific journals and visuals were created to deduct publications strategies. On the technical side, the overall analysis process requires diverse tools for reference managing, text analysis and visualization. The impact on skills of the knowledge manager who moves from the expert for query languages to the expert for creation and maintaining of thesauri is also shown. Main benefit of the analytical methods compared to traditional database searching is the manifold use of results, which are easily adaptable to new requirements.

The growth in computing power has made it possible to gain insights into very large quantities of text by both statistical and neural methodologies and linguistics, the way languages work for humans, is not a major part of that process.  However, decisions on FTO, Invalidity and competition are still made by humans, which means reading the patents identified by the machines. Because humans are endlessly creative even in an apparently constrained world of patent writing, and different human languages have different ways of expressing similar concepts, identifying ranges in alloys, compounds, formulations etc. is a complex challenge for computer programs.  This paper explores how the same computer hardware advances which have enabled machine learning can be exploited to produce overall solutions to the problems that natural languages present to humans and computers alike.  It will identify those areas in  which computer programs can outmatch human capability in identifying and assessing complex interactions of molecules, elements and the like and comparing them with potential or actual specifications, a capability which allows humans much more time to focus on the interpretation rather than the finding. And it will illustrate the application of such programs to both the main European languages and Chinese, Japanese and Korean.

Patent data is a critical source of information to stimulate innovation and for competitive intelligence. Patents are often the first and only source of disclosure of a new invention and hence, ignoring them will only delay innovation and give an incomplete competitive intelligence picture. 

Delivered from the perspective of a patent analyst, we will use case studies to describe the use of patent data to compile a competitive landscape, to stimulate innovation by learning from others and to help identify valuable IP in a portfolio. We will discuss the challenges in using patents for competitive intelligence and the recent innovative features and functionality in PatBase which can help, including: 

• Using thesauri, semantic and non-patent literature searching to compile a comprehensive competitive landscape.
• The use of Analytics for customised, multidimensional analysis and to visually compare multiple datasets. 
• Text-mining to automatically identify and highlight concepts within any full text patent.
• Citation analysis to identify key competitors, collaborators or potential infringers. 

This presentation will demonstrate how any user can benefit from the innovative features and functionality in PatBase to interrogate and visualize the competitive landscape for any technical area.

Open chemistry platforms such as PubChem offer depositor-provided cross-references to scientific abstracts in PubMed for many compounds. However, only a few cases have direct links to associated primary literature on the publisher’s site.  

In our talk we will show how chemical data gathered through Chemical Named Entity Recognition will enhance discoverability and accessibility of scientific information in an easy and intuitive way. By depositing these chemicals in public databases, literature information can be searched by chemical structure beyond typical text search. Additionally, the use of a smart algorithm ensures that only relevant compounds found in an article will be displayed. 

We will present publisher-internal projects dealing with the comprehensive chemical annotation of relevant content and the deposition of the results in PubChem. Additionally we will discuss further opportunities with regards to other platforms like ChemSpider, ZINC or OpenPHACTS.

During the recent years like other segments, cheminformatics also entered the field of big data. As we see quick transition from the traditional methods towards the direction of need for handling significantly large sets of data often in unstructured or semistructured forms. Words and phrases like, terabytes, scalability, NoSQL, cloud solutions are integrated in our everyday language. I would like to present a few case studies to highlight key features of this transition. Such as sowing techniques and technologies for handling different aspects of this new area.

 Trying to keep up to date with developments, trends and opportunities even in narrow domains involves digesting and considering large amounts of textual information and often is beyond the reading capabilities of human experts. Large organisations may be able to cope with this challenge with dedicated analysis teams, but SMEs are overcharge with this information load. 

Under the label „Technology Scouting“ we present an approach to employ modern semantic technologies and artificial intelligence to (semi) automate the collection, analysis and reporting of large document collections in a way that allows to derive important insights for technology-driven companies: Which technologies and markets are emerging or moving, how do my clients, partners and competitors operate?   

After an introduction to the technological and methodological basis, we present experiences from past industry engagements where this aproach has be applied in production.

Neglecting key scientific developments can translate to missed opportunities and increased risks in the legal and business industries. The scientific and medical literature provides a significant source of information for stakeholders in these industries, but the ever-increasing pace and sophistication of emerging science can be daunting to track and review. In our years of experience working closely with regulated product manufacturers and their counsel, we continually encounter teams that struggle to keep up with new science in a systematic and organized fashion. However, when firms integrate systematic literature monitoring in their processes, these firms are up-to-date on the science and rather than playing catch-up, these teams are hard at work analyzing and developing new strategies based on the emerging science. This latter group is exemplary of the advantages offered to those firms and companies closely tracking key scientific developments. Technological developments are making literature monitoring and evaluation more effective and relevant to the intended audience. To enhance our work, we have recently initiated various collaborations to integrate new human-assisted big data and machine learning approaches to the identification and review of the literature. In this presentation, we will present our experiences working closely with attorneys handling complex scientific cases and how we support them in maintaining an awareness of the science, including some of the technologies we are integrating with our existing processes.

Since it launched in 2011, the Digital Science Catalyst Grant has awarded 13 groups with grants of up to £15,000  each to fund exciting innovations, and to take them from concept to prototype. The grant also comes with the opportunity to work with the Digital Science team to help refine, develop and promote the innovation. In this way we hope to lower barriers and foster greater creativity in research solutions for science. This presentation will outline the increasing need for grants such as Catalyst, and describe how we support founders with their early-stage ideas.

While the raison d'être of patents is Intellectual Property (IP) there is a growing awareness of the scientific value of their data content.  This is particularly so in medicinal chemistry and associated bioactivity domains where disclosed compounds and associated data not only exceeds that published in papers by several-fold and surfaces years earlier, but is also, paradoxically; completely open (i.e. no paywalls). Scientists have traditionally extracted their own relationships or used commercial sources but the last few years have seen a “big bang” in patent extractions submitted to open databases, including nearly 20 million structures now in PubChem.   

This tutorial will:

• Outline the statistics of patent chemistry in various open sources
• Introduce a spectrum of open resources and tools
• Enable an understanding of target identification, bioactivity and SAR extraction from patents and connecting these relationships to papers
• Cover aspects of medicinal chemistry patent mining
• Include hands on exercises using  open source antimalarial research as examples 

The focus will be on public databases and patent office portals, since these can be transparently demonstrated.  However, the essential complementarity with commercial resources will be touched on. Those engaged in Competitive Intelligence will also find the material relevant.