A practical plan for becoming truly data-driven in life sciences

    Guest contributor Peter Brandstetter explains why a digital approach to content control is the way forward for life sciences companies.

    SUBSCRIBE TO OUR BLOG

    Life sciences firms are starting to look more deeply at what’s involved in embracing a holistic, data-driven approach to information management - from R&D to Quality. In other words, "how can companies eliminate documents in the future?"

    Life sciences companies are well aware of the impracticality of managing processes using single-use documents. It’s incredibly inefficient, and it doesn’t save any time or effort in the long run if a new document has to be generated from scratch each time a report or submission is needed. Ultimately, documents were designed to serve human use. They were not designed to be processed by computer software.

    This is generally agreed upon now. So the ideal scenario pharma and medical device manufacturers need to be working toward is one in which all information is captured and stored once, for broad, multi-purpose use across - and even beyond - the organization. In a format which can be readily and reliably updated at the source, and processed by software as needed to fulfill each given reporting or submission requirement.

    How can life sciences firms make the switch to digital?

    This leap to a data-driven operating model promises to be hugely ‘transformational’ for companies - in the truest sense of the word. What’s more, all of the technology to enable this is available and readily accessible today. The more challenging element is the shift in mindset that must accompany this fundamental change to how companies manage and work with information.

    There are two particular issues to overcome here.

    The first is the need for alignment across the different functions, from Quality, Manufacturing and R&D to Commercial teams, which up to now have each had their own approach to managing information and generating output. To affect real step changes in efficiency, these individual departments all need to collaborate using the same master data source. This is a significant adaptation from previous ways of working.

    The second challenge is figuring out how and where to start on a journey which is likely to be long – straddling some 5-10 years in total. Where to begin is actually not so important. The key is to establish a common north-star vision which spans all of the different stakeholder groups/departments, which will inform any next moves. And these do not have to be taken sequentially. Slowly, pharma is adapting to a more agile, ‘scrum’-based approach to delivering new projects. This is the take that is needed here, because it encourages parallel developments in smaller steps towards a common goal.

    In this context, companies can start to make real progress toward a data-driven future.

    I advise the following:

    • Start with a clear vision with a 5-10 year horizon. This needn’t be a major undertaking. A couple of targeted workshops will help identify key pain points.
    • In the spirit of a more agile approach to change, encourage and motivate everyone to bring ideas to the table, with a means of evaluating them quickly to establish or discount them based on their real potential.
    • Don’t wait for technology. Don’t spend time evaluating the thousands of tools out there. Take a cloud-based platform approach to trying out new capabilities. This will promote easy, low-risk experimentation /prototyping as a means to test out improved ways of working.
    • Be clear that a 10-15 year vision does not equate to a large, unwieldy single-scope project. The idea is to move towards that goal incrementally, adjusting as you go. This allows companies to maximize the value of existing systems where appropriate along the way, and to move toward the target set-up in a way that feels manageable and achievable. It also allows for dynamic reaction as new conditions or requirements arise – as mergers and acquisitions come along, as product portfolios change, and/or as regulatory conditions evolve.
    Published on    Last updated on 02/09/2021

    #Regulatory Information Management (RIM), #Life Sciences

    About the author

    Peter Brandstetter is a Senior Manager for Technology Consulting at Accenture in Zurich, Switzerland. A respected authority in IT-enabled transformation in life sciences, he has more than two decades’ experience of solving complex IT challenges for pharmaceutical companies globally -gained across senior life sciences consulting/IT roles including Life Science Central Region Lead at CSC, Senior Managing Consultant for GBS Life Sciences at IBM, and Senior Manager at PwC. Peter specializes in quality management and quality assurance in manufacturing and R&D, enterprise content management, and R&D (clinical data management, pre-clinical, R&D Lab, R&D collaboration and project management), as well as computer validation.

    SUBSCRIBE TO OUR BLOG