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LABORATORY INFORMATICS GUIDE 2016 | DOCUMENT MANAGEMENT ➤


the success of this project and the utility of the Quosa platform for pharmacovigiliance applications, Elsevier plans to launch a dedicated pharmacovigilance system in early 2016.


MAXIMISING USE OF THE ELN In scientific R&D, the main repository for newly generated data – both structured and unstructured – is an ELN, to which contextual information can be added and from which information can be relatively easily managed and shared, commented Paul Denny-Gouldson, vice president of strategic solutions at IDBS. ‘Move further down the development pathway into more formal, process driven preclinical and clinical studies, and data is still often recorded in Word and Excel documents, from which searching for and retrieving information, and its context, is far more problematic.’ In an ideal world all information will be


logged in mineable electronic format, with accompanying context. Downstream data can be layered on top of data from earlier R&D, and sit alongside other relevant information from related projects, including successes and failures, along with regulatory and patent documentation, and project management decisions, he continues. ‘We should think in terms of building networks of information, and the ELN is a useful central repository for that information. ELNs are becoming far more contextually rich, and the IDBS E-WorkBook ELN solution, for example, captures many different components of data from different areas of an R&D project or study.’ While there is little doubt that recording all


data electronically will make information more searchable, increasing that access to knowledge and data must be associated with safeguards, Denny-Gouldson continued. ‘People want to retain ownership of their documentation, data, and knowledge, and to be able to track exactly to who or where each piece of information is released, in what format, and how it is utilised. The increasing trend towards collaborative and outsourcing models of research and development does mean that sharing data is inevitable. Scientists and companies will have to deal effectively with outside organisations, and information will have to flow in both directions, across firewalls.’


TURNING COLLABORATIONS ON AND OFF To ease the security concerns associated with working collaboratively, IDBS is developing a new solution, due for release in 2016, which will function as an extension of E-WorkBook. ‘The cloud-based module is based on the


22 | www.scientific-computing.com/lig2016


Quosa allows users to find, store, view, and share full-text scientific articles instantly through a secure, cloud-based environment


concept of hosting information that needs to be shared, from sample tracking and requesting analytics, to results sharing and collaborating on experimental protocols and workflows. It’s about getting the data structured the way you want it, being able to share and track that data, add context and comment on it and, critically, bring that data back behind your own firewall into E-WorkBook. We want to help companies turn these collaborations on and off very quickly, and securely.’ Being able to unpick documentation and


knowledge into component parts is particularly important when projects or parts of companies are out- or in-licensed, spun out, or acquired, Denny-Gouldson commented. ‘Any document or set of documents may contain information originating from different departments, or segments within an organisation, and if part of that organisation is then to be sold off, say, you need to be able to sort out and separate which bits of information belong to which organisational entity. This is nigh on impossible unless your documentation is fully traceable, accompanied by all the relevant metadata, and can be separated out.’ Unpicking documentation in these circumstances is something of which IDBS has had first-hand experience. ‘We were tasked by one of our customers to do just that. Because they were already using the E-WorkBook infrastructure, we were able to pull out the data that the new company could take with it, whilst ensuring that the incumbent retained all the remaining data.’


TAKING THE WORK OUT OF THE SEARCH The ultimate aim is to develop software that will instruct and point users in the right


direction, and not just provide a conduit for searching, opening and distributing files and databases, Denny-Gouldson maintained. ‘If you want to carry out an experiment, you will at the very least want to be able to search and mine repositories to see if anyone has done similar work before, search for data on your compound/new drug product or samples, and identify other relevant experimental protocols, for example. Take that a step further, however, and ultimately what we want is to be able to start to type in an experimental protocol, say,


Knowledge is what drives research through into


development and to market


and have the software automatically point you to relevant experiments that have been carried out in the past, or to a researcher who has specialist knowledge in your field of experimentation, or perhaps to a collection of data on your sample or biological pathway, or to some other IP that is relevant to your R&D. This isn’t really a huge leap, either conceptually or in practice, from the kind of intelligence that we are seeing in Amazon and Google analytics, as part of our everyday surfing on the web. But this will be a big step forwards in turning historical, contextual data into an even bigger asset to R&D organisations.’ And this brings us all the way back to the


ELN as the central source of information and mineable repository, Denny-Gouldson suggested. ‘We should start to think about ELNs as a gateway or jump off point, rather than just as a repository for recording experimental protocols and results.’ l


Elsevier


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