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informatics in pharma

Dr Othmar Pfannes, CEO at Genedata


he automation of R&D processes in general, and

data analysis workflows in particular, is a driving force within pharma as the time it takes to move research projects forward is critical. Frequently, raw data is collected from different sources over a long period of time and understandably once the data is there researchers don’t want to spend another few months integrating that data and waiting for the analysis results. Most large pharmaceutical companies are recognising the need to standardise data analytic processes, therefore, and are working with partners to do just that. In the past, these companies could afford to run internal soſtware development projects in order to have customised data analytics workflows. Today, however, pharmaceutical companies need to look more


closely at the return on investment and consider solutions that work out-of-the-box with little configuration effort. Not only is this a cheaper option, but the deployment process becomes significantly easier and shorter. Companies are also beginning to embrace

enterprise platforms. Tis is driven somewhat by necessity as desktop soſtware solutions are no longer able to cope with the rising amount of data and do not support collaborative research. An enterprise approach also ensures that external partners can gain easier access to the same algorithms and types of analytic workflows. Tere needs to be a slightly different mind-set when investing in an informatics solution for an entire organisation rather than an individual laboratory, but the key considerations remain the same: security, to ensure that data is protected from manipulation and theſt, and that any outside partners only see the data sets they are supposed to; and, of course, scalability, which gives researchers the flexibility needed to grow. I would recommend that any company that is in a position to evaluate its informatics strategy pay close attention to enterprise solutions.


and networked research models. When using this model it’s important that any outsourced activities are made as much a part of the internal workflow as possible. Te same level of care needs to be given to preparation, understanding and time tables for delivery, and a robust informatics platform is necessary for managing that flow of information. Externalisation and the use of partners such as contract research organisations remains prevalent, but we are beginning to see a change as pharma companies now look to pull their assays back in-house. Te cost advantages that drove the move to externalisation in the first place are becoming less obvious now and although I don’t believe we’ll see a wholesale reversal, the balance is shiſting towards in- house research. Tis change is forcing pharma companies to


look at their informatics deployments because one side of the business has been essentially virtualised in order to simply load up received data. Now that a higher level of control and functionality is needed, companies are

Andrew Lemon, managing director at The Edge

lmost 10 years ago, the pharmaceutical industry went through a revolution with the push towards more outsourced

investing in systems that can support the transitional model where some aspects remain outsourced while others are brought in-house. Progression of each project needs to be tracked and compared to all the others. Tis transparency can have a profound impact on the decision-making process. Ensuring that the informatics system adds quality to the data


at the point of capture is also crucial because without the metadata, it becomes more difficult to exploit that data further down the line. Te importance of effective data management should not be underestimated, especially in research biology, and it’s important that companies invest in an informatics platform that can handle the entire life cycle.

Kabir Chaturvedi, director life science solutions portfolio marketing, Elsevier


nformatics tools in pharma have been keeping pace with the rising torrent of data, but there are several challenges. On average,

there is a 10-year incubation period before a drug is ready to hit the market – and, as roughly just six per cent of candidates succeed, there is a considerable amount of risk involved. Te cost implications are equally significant, as each candidate when taken through the pipeline aſter preclinical can cost several hundreds of million dollars at a minimum. Te informatics needs of pharma are complex

but one underlying point is that companies need a solution that can take the torrent of data streams and anchor them into fact. Taking next-generation sequencing as an example, there will be a time when every human will have their genome sequenced and the amount of data being generated will simply be incredible. Tose predicted features within those genomes will need to be grounded in scientific fact. Providing well indexed data and associations in that data will help inform predictive analyses, minimise

risk and ensure that there is no need to reinvent the wheel each time. Many companies have their own vast

repositories of internal data and paper records that are waiting to be mined, and it’s vital that this is integrated with external bodies of information. When faced with a proliferation of


data, scientific publications, and new methods of reporting, users need access to a structure that will be able to navigate across the different standards and data formats. Interoperability and a common structure and format are priorities for pharma, and informatics solutions provide that stability. Te analytical tools do need to be scalable and in the future I believe cloud will definitely impact the pharma community.

@scwmagazine l

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