How virtual and augmented reality technologies will support data insights in future
All businesses are swamped by data. If only they could get to the real insights more speedily, they could truly transform the way they operate. Colourful, graphical dashboards with drill-down detail have done much to bring data alive for decision-makers, drawing their attention to what’s important and giving them the chance to slice and dice the data in a range of different ways to see what’s really going on. The logical next development is to be able to ‘walk through’ the data, uncovering new correlations and insights using virtual or augmented reality (VR/AR).
It might sound like something from science fiction, but technically much of this is already possible. In fact, in our own organisation, we’ve already started to walk through our own object data models wearing VR headsets to visualise the possibilities.
Revealing different perspectives
Up to now, companies have relied on two-dimensional ways of looking at this, limiting the correlations that can be made or the conclusions drawn. The ability to represent different data objects or assets in 3D models, and turn them in different ways to reveal different perspectives, could be transformational in delivering a richer understanding of a situation, and in projecting how this will play out under different parameters. The opportunity is to uncover previously unseen patterns and trends, and combine and see the correlations between diverse data sources.
In life sciences, once you apply an object data model across regulatory and quality management processes – so that different data fields such as country, drug type, dossier and document are represented and can be viewed in different combinations, by their different interdependencies – there are numerous practical ways companies could apply VR and AR-based data visualisation and navigation for useful effect.
Here are seven examples:
1. In pharmacovigilance and safety, for signal detection.
Take the current situation with COVID-19 vaccines, for which Phase III clinical trials are being conducted with people in the real world, because of the urgent need to roll out protection.
Although vaccines have been authorised as being safe to use, mass monitoring for potential adverse effects is paramount, which means collecting huge volumes of data and analysing it in a comprehensive way. With five billion people being targeted, and each individual potentially generating 1Mb of data, that’s an unthinkably challenging prospect – overwhelming not just scientific brain capacity, but the scope of artificial intelligence (assuming this hasn’t yet been sufficiently trained in what to watch out for). So those responsible need to be able to represent and configure the data in different ways to spot and compare potential adverse effects.
2. Impact assessment, forecasting and simulation.
If there is a change in regulatory requirements, VR or AR visualisation offers a chance to ‘pull on that string’ and visually see how the impact of that change cascades through its operations and current assets.
Although it’s already possible to conduct fairly extensive impact assessments using software, the addition of a third dimension would allow teams to factor in the current availability of resources and of network infrastructure as part of the calculations, and weigh up all of the correlations simultaneously.
Once companies can visualise the fuller impact of a change, across all affected products, they can more accurately determine how realistic it will be to achieve that within the given time frame.
3. Quality consistency checks across multiple data types and formats.
Today, data sources take multiple different forms, from structured data and numerical values to free-form text, images, video and audio files. Making sense of all of this, and being able to rely on what all of this diverse data is saying, means having confidence in the quality of all of these contributing sources – and being able to spot any overlap.
Introducing the VR/AR element could help ensure consistency across all the data and metadata, highlighting anything that needs to be corrected, completed or removed due to duplication.
4. Including emotion in pharmacovigilance reporting.
If headaches are emerging as a common adverse event, whether linked to a COVID treatment or some other medical intervention, the ability to include the dimension of emotion in analyses could help determine whether stress and anxiety might be significant contributors.
5. Clinical trials planning and management.
Clinical studies can be harder to plan and recruit for as pharmaceutical companies’ focus turns away from blockbuster drugs towards more specialised medicine such as therapies for rare diseases. Adding a VR capability to clinical study planning and management, including dimensions for patient recruitment and availability, could make it easier to factor in all the variables and make more realistic calculations.
6. Manufacturing and distribution impact assessments, forecasts and simulations, to aid planning.
Getting the BioNTech-Pfizer COVID-19 vaccine to market requires a complex logistics chain and infrastructure, because of its particular temperature requirements. Being able to navigate the complex considerations visually across multidimensional data sets would enable accurate planning including any contingencies required.
Roads and trucks could represent supply and demand, and colours signal time or quality issues. In the context of COVID, a model of the earth and spike lengths could signal where peaks of the virus are currently or where demand is building/least fulfilled.
7. Planning and managing marketing authorisation and variation submissions.
Assessing the progress of eCTD (electronic Common Technical Document) submissions by being able to visualise and navigate these as 3D pyramids, and see at a glance which parts are incomplete or waiting for documents or data, and which submissions have deadlines approaching, aided by colour coding, could make it much easier for regulatory teams to keep things moving.
As IDMP (Identification of Medicinal Products) submissions become obligatory, advanced data visualisation could provide an invaluable overview across all the different data dimensions, helping companies cope with their increasingly complex data gathering and maintenance burden.
The combination of AR and VR
More intuitive, 3D data modelling and visualisation is set to become the norm. Augmented reality (AR) will add to this, bringing digital and physical domains closer to perform real-time analyses. Take the scenario of a pharmacist asked to perform an inventory check following a regulatory change. He or she would simply put on a headset which automatically scans for affected products, by scanning and visually comparing the labels of products on the shelves with the correct latest information logged on back-office systems. The combination of AR and VR will bring data alive and work with the human senses, supported by technology that is becoming an ever more seamless part of how people work.
New ways of visualising and navigating data also present new scope for collaborating on data insights, applying the principle that several brains are better than one. The extra dimension allows teams to ‘look around the corner’ of data and what it’s telling them. As volumes of data multiply, existing analytics and reporting tools are hitting the ceiling in terms of delivering that clarity. AR and VR technologies will represent a step change towards the next generation of data analysis.
Romuald Braun is vice president of Strategy for Life Sciences at Amplexor