RIM reimagined in 3D: exploring new data dimensions
SummaryIt’s likely that in the next waves of data transformation in life sciences, Regulatory and Quality teams will explore and interact with regulated product information and market intelligence using virtual or augmented reality (VR/AR). Amplexor’s Romuald Braun looks into the future.
- Author Company: Amplexor
- Author Name: Romuald Braun, VP of Strategy for Life Sciences
- Author Email: firstname.lastname@example.org
- Author Website: https://www.amplexor.com/
Graphical dashboards already bring data alive for business decision-makers, drawing their attention to what’s important and allowing them to drill deeper into anomalies or findings of interest. The logical next step is to be able to ‘walk through’ the data, making new data-driven discoveries using virtual or augmented reality (VR/AR). Indeed, in our own organisation, we’ve already started to walk through our own object data models wearing VR headsets to visualise the possibilities.
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.
Potential use cases
In life sciences, applying an object data model across Regulatory and Quality Management processes paves the way for different data fields - country, drug type, dossier and document – to be represented and can be viewed in different combinations, by their different inter-dependencies.
This presents a number of opportunities:
- In Pharmcovigilance and Safety, for signal detection.
Take the current situation with the Covid-19 vaccines, for which Phase III clinical trials are being conducted with people out in the real world, because of the urgent need to roll out the protection.
Mass monitoring for potential adverse effects is paramount then, which means collecting huge volumes of data and analysing it in a comprehensive way. With 5 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 AI (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.
- Impact assessment, forecasting and simulation.
If there is a change in regulatory requirements, VR or AR visualisation offers a chance to visually explore how the impact of that change cascades through a company’s 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 timeframe.
- 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, video and audio files. Making sense of all of this 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.
- Including emotion in PV 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.
- 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.
- Manufacturing & 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 multi-dimensional 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.
- Planning and managing marketing authorisation and variation submissions.
Assessing the progress of eCTD 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 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.
Looking through new lenses
In time, more intuitive 3D data modelling and visualisation will become the norm, bringing data alive in all kinds of important new ways for companies – ways that work with the human senses - supported by technology that is becoming an ever more seamless part of how people work.
Already, once-cumbersome VR headsets are giving way to slimmer glasses - without wires - which in turn could be exchanged for content lenses. And all of the heavy lifting – the intense data processing – can happen in the cloud today, connected via continuously-improving network bandwidth.
The AR angle
Finally, augmented reality (AR) offers further value in bringing digital and physical domains closer to perform real-time analyses.
Take the scenario of a pharmacist asked to perform an inventory check, to identify any non-compliant products in its stock room following a regulatory change. In future they might 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, triggering next actions if these don’t match.
What makes all of this so exciting is the prospect of being able to engage with data more intently and naturally, and to simultaneously include others in these explorations. For many organisations, that will be truly transformational.