Anyone who works in pharma will be mindful of the regulation surrounding the sector’s data use. Of course, organisations must be transparent and adhere to regulatory requirements, but there are still many ways that pharma firms can gain enormous value from data.
The challenge is that the most insightful data in any industry is unstructured.
In healthcare that usually encompasses primary data – from direct interaction with an end-user and purchased data, such as clinical trial reports, patient testimonials and adverse events – and secondary data, that gathered via market research from sources such as social media and websites.
But unstructured data can be anything that doesn’t lend itself to easy analysis because of its form.
Unstructured data is of critical importance in pharmaceuticals, helping to manage and mitigate risk, monitor competitors and market trends, and more. But most organisations are not set up to manage it and get maximum value from it.
The benefit of unstructured data
Most people are aware of the need to use data and make informed data-based decisions to achieve business objectives. But data in and of itself has little value. It’s the insight that it brings that holds the value.
But many organisations aren’t using most of the data at their disposal. Even if they are, they mostly do so inefficiently, especially the unstructured data that is so rich with insight.
This is a potential problem when it is so vital for pharma firms to be agile and responsive to remain competitive.
The work that these organisations do is so essential – look how quickly vaccines were produced to combat the COVID-19 pandemic – and generates such value that the slightest hitch or challenge can bring operations grinding to a halt. Utilising unstructured data can help, in ways including:
Managing and mitigating supply chain risk – it’s virtually impossible to track all the incidents and events that might affect production and safety in pharmaceutical manufacturing businesses.
But monitoring large volumes of unstructured data and extracting actionable insight means users can make informed decisions about the supply chain.
Categorisation of molecules in clinical trials – the tracking and monitoring of molecule performance is a key element in clinical trials, which will determine how likely a molecule will become a standard of care for any specific disease.
But the teams involved need to check vast amounts of data to find the performance of different molecules in multiple stages.
Tapping into unstructured data delivers huge insight, and can even rank all under-trial molecules by safety and efficacy across different phases of clinical trials.
Responding in real-time – if an incident is allowed to escalate, then the consequences become ever greater. Therefore, the onus is on pharma firms to react in real-time to anything that might impact safety on the supply chain or other potential risks.
This real-time awareness of safety concerns, product recalls and potential supply chain breakdowns is essential and means firms can act almost immediately to prevent the situation from escalating and avoid long-term damage.
Competitor and market monitoring – understanding what competitors are doing and what is happening in the broader marketplace are essential within healthcare.
But tracking everything that affects this is highly inefficient. Tapping into unstructured data delivers the most relevant insights about competitors, their markets, and their products, meaning you can make informed decisions in real-time
Protection against non-compliance – there is much industry-specific regulation in health and pharmaceuticals, as well as more general regulation around data, such as GDPR and CCPA.
There is a lot of data relating to compliance and many triggers that require action.
Working with insight-rich unstructured data means users can be informed in real-time when action is necessary for different compliance regulations, offering deeper protection against non-compliance.
Unstructured data challenges
When attempting to achieve the above benefits, there are a number of challenges to be considered.
One is that there are almost limitless volumes of unstructured data relating to risk in the pharmaceutical sector.
Looking for trends and patterns within this unstructured data is difficult because most platforms cannot manage it.
Another challenge for pharma firms is that unstructured data can reside in many different databases, applications and software platforms.
Some organisations choose to have this unstructured data flow into a data lake, in which it can exist in its raw, unstructured format.
Such an approach allows data to be exported from multiple systems but also makes things too complex for business users to manage, requiring the input of a data science team. This is not tenable or realistic.
Augmented intelligence and unstructured data
But utilising the right technology platform can be a significant help in managing unstructured data and keeping it simple enough for business users.
Working with an Artificial Intelligence (AI) solution adds structure to unstructured data, meaning that pharma firms can benefit from the full and contextual picture.
But augmented intelligence – which combines the power of AI with humans’ imagination, intuition and intelligence – can unlock even more insight.
AI can help gather data sources but augmented intelligence solutions allow far greater access to information and deeper insight collected from unstructured data.
This insight is presented to the user in the form of insight-based recommendations.
A pharma firm using unstructured data for protection against non-compliance, for example, would see the user recommended exactly what action needs to be taken to ensure compliance.
Pharma is bound by strict regulations around the use of data, but that does not mean the sector cannot make more effective use of unstructured data.
The key to doing so is via the use of augmented intelligence, which can bring vast benefits to pharma firms.
About the author
Dr. Dorian Selz is the CEO and co-founder of Squirro, which works with organisations to bring them greater insight from their data.
