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With so much focus on artificial intelligence, you may be missing out on the real opportunity: making the most of your data.
This is especially true for organisations who operate in the healthcare sector. Often, your data is unstructured and sits in siloes. Think lab reports, clinical trial documents, regulatory submissions, scattered across paper records and SharePoint repositories. The challenge is to turn this unstructured data into unified, secure, and actionable intelligence. All while ensuring audit-ready compliance.
How these companies exploit their data and how they enhance it could be the crucial difference between success and failure. We aren’t simply talking about using your data for AI training purposes, but protecting it. Connecting it so that it doesn’t sit in siloes. And then activating this precious resource.
It sounds like a Herculean task, but this is where Iron Mountain Insight DXP steps in. This AI-powered data platform is scalable, low-code and SaaS, and it has been specifically designed to unify physical and digital information. What’s more, Iron Mountain has a proven track record of working with NHS Trusts and hundreds of medical organisations worldwide.
To provide concrete examples of what this looks like in practice, we focus on five use cases specific to this sector. As you will see, they reflect what InSight DXP was designed to do: to protect, connect and activate company data.
If an upcoming compliance deadline keeps you up at night – all that paperwork, chasing down information, and the difficulty of proving chain-of-custody and version control – then Iron Mountain is the partner you need.
InSight DXP has been designed to help organisations turn critical documents – be they clinical reports or regulatory paperwork – into structured data. It ingests, unifies and automatically classifies all physical and digital regulatory assets into a single, secure platform. It can even extract and tag key metadata, such as study ID, drug name and version number.
Once your data is in InSight DXP, its tools give you full version control – including the ability to roll back and restore – and provide full audit trails.
All of this means that your regulatory teams can find the documents they need instantly, with the help of AI. This can reduce submission assembly time by days, even weeks.
“In highly regulated environments, documents can be subject to an exhaustive verification process to confirm certification, compliance and legal integrity,” said Walker. “Instead of relying on manual, resource-intensive checks, such as visually confirming signatures or validating every required field, we use InSight DXP’s automated workflow engine to instantly perform these duties. This not only guarantees the defensibility of the record but also frees up staff from mundane, error-prone tasks, allowing them to focus on higher-value, strategic work.”
And your sleep will be further improved knowing that you have full traceability and a comprehensive audit trail for every asset. Compliance with the FDA, EMA and other regulatory bodies has never been easier.
Complying with retention and destruction policies for your records and data is increasingly difficult as new regulations related to privacy and AI are enacted around the globe. That’s especially true if you’re relying on your teams to manually classify documents and track retention rules across regulatory jurisdictions, whether that’s HIPAA, GDPR or GxP. The almost inevitable outcome is a combination of high costs and non-compliance.
Then there’s the problem of ROT data. That is, redundant, obsolete and trivial data, which not only increases storage demands but also increases your exposure to legal and security risks.
This is yet another area where InSight DXP can help. Iron Mountain’s Policy Center integrates information governance to automatically apply legal hold and retention schedules to documents and data based on classification and jurisdiction.
It’s boosted by AI-powered data discovery, which systematically identifies and flags ROT data. It turns the job of remediating unnecessary data from a time-sapping nightmare into a streamlined task.
All of this not only mitigates your compliance risk but also reduces your costs. First, the painful, manual task of automating the enforcement of complex, global retention policies has become automated. Second, by proactively identifying and removing unneeded data, you both reduce storage expenses and improve the quality of your data.
For a real-world example, consider one British multinational pharmaceutical and biotechnology company that’s based in London. Without a fully defensible Global Record Retention Policy, it turned to Iron Mountain for help in creating a managed service that kept its schedule up to date. Plus, they wanted to outsource the management of their policies and create a dedicated helpdesk service for queries.
This is exactly what Iron Mountain created for them by implementing a Global Record Retention Schedule that focused on their seven core jurisdictions. And by outsourcing the policy and helpdesk service, they also saved money to reinvest back into their core business.
Anyone who has ever been involved with a clinical trial will be aware of the mountain of paperwork and data that’s created. Not only is it time-consuming to manually extract key data points from the trial master file (TMF) documents, but that can also lead to errors. These can take many forms, such as mishandling patient consent forms, case report forms and site contracts.
Any form of manual process also means you’re missing out on real-time visibility. This means you can miss emerging trends and potentially make decisions too late – even after the trial has concluded.
Insight DXP’s Intelligent Document Processing is the saviour here. Thanks to Iron Mountain’s years of experience and investment, it has pre-trained models specifically designed for high-accuracy extraction of data. What starts as a jumbled mix of patient demographics, dosing, and adverse events, spread across various clinical documents, becomes structured data ready for examination.
What’s more, agentic AI and custom workflows can enrich data with context-aware metadata and then integrate the actionable data into core clinical systems.
All of which means that problems like manual data entry and unstructured data become a thing of the past. Instead, research organisations have rich, context-aware data that boost their chances of improving both insights and patient outcomes.
Testing a batch of drugs must be done to the highest possible standards, with every batch subject to fierce regulations and quality control. That’s as it should be and unavoidable. What is avoidable: the slow and often error-prone process that accompanies each batch of tests.
Rather than relying on manual review and validation of batch records, pharmaceutical companies should switch to automated workflows enhanced by agentic AI. Here, specialist AI agents created by Iron Mountain – as part of its InSight DXP platform – can validate data completeness, route approvals and compare data against the system of record or defined business rules.
This helps avoid the frequent problem of missing information or exceptions, which often aren’t caught until late in the QC process. Instead, human experts are alerted as soon as the platform detects exceptions or missing information – the crucial Human-in-the-Loop (HITL) review.
Such an approach has multiple benefits. At the top of the list is faster batch release, which reduces the time needed for review and sign-off, allowing the drugs to hit the market sooner. But you also reduce the risk of a costly rework process. Win-win.
One of Iron Mountain’s clients had a significant challenge: a deadline to transfer data from a third party that was carrying out studies and trials.
Liaising directly with the third party, Iron Mountain provided a secure cloud storage platform that complied with industry standards and meant that as soon as each of the trials was completed, the data could be directly uploaded entirely independently of the client.
Along with digital information, Iron Mountain InSight DXP provided the capability to capture physical documents from trials and studies, offering a complete, auditable solution that was fully indexed and searchable.
One of the unknown unknowns in drug research is exactly how much valuable data is trapped in lab notebooks and internal research papers. Then there’s the mountain of publicly available data found in patents and scientific journals. How on earth can this be unlocked without a consistent means of classification and metatagging?
In recent years, another potential missed opportunity has emerged: AI. If your data isn’t tagged properly – or even if it’s simply tagged incompletely – then you’re missing out on a potential goldmine. This is proprietary information that AI algorithms could exploit.
Once again, Insight DXP is on hand to help. By creating a “Knowledge Graph”, it grounds your data, giving it consistency and surfacing it when relevant, in a way that wasn’t possible two years ago.
As a result, you can accelerate data discovery across the previously disjointed mix of digital, physical and rich media assets, using semantic search that understands context to reveal hidden patents and relationships in the data.
AI can then help classify and enrich your data by automatically applying standardised metadata to all assets, regardless of their source or format.
Your researchers can then tap into this enriched data pool to gain scientific insights that were previously unavailable, perhaps even leading to new discoveries and product launches. And you’ve also turned your unknown unknowns into a solid foundation of data ready for the next project – one that can feed into future AI models.
