Final blog in series: Four economic fallacies of long term data management and how to avoid the surprising cost of “doing nothing” - Arkivum

Archiving & Preservation / 22 May, 2018

Final blog in series: Four economic fallacies of long term data management and how to avoid the surprising cost of “doing nothing”

Authored by Daniel Hickmore, VP of Health & Life Sciences @ Arkivum
Many Research & Development (R&D) executives express the same frustration. They may have a cure for cancer, or a revolutionary pharmaceutical discovery waiting to happen, but they just cannot quite grasp it. They think they already have the data somewhere, but have difficulty in easily searching for, and accessing, the data as they need to. Meanwhile investors want faster innovation, more effectively, while still controlling risks. This is a balance between cost, compliance and innovation at every stage of the pipeline.
The health, life sciences and pharmaceutical industries are all interconnected – via data, from research records and patient information, to monitoring and clinical trials. All these industries manage vast amounts of data, and often for many decades or even perpetuity. One significant challenge is that often the data is locked-in and unavailable due to inaccessible repositories, data silos, end-of life data stores, and decommissioned platforms. The data needs to be stored due to regulation, but immutable to guarantee data integrity. The situation has been exacerbated by rapid scientific technology innovation where data management considerations have been ignored. It is essential this is addressed now, or the situation will reach critical mass. Big data, AI, NLP and Machine learning solutions alone will not solve these problems, and without these problems being solved they will only be able to deliver limited insight. Roughly 70 percent of any data project now involves simply managing data, such as integrating, transformation, data quality management and ensuring data integrity; before any actual analysis can begin.

The four economic fallacies

In this series, we have discussed the four fallacies organisations have about long-term data management preservation. The challenges we have discussed here are symptoms of those assumptions. As we have discussed, data in this industry stands normal assumption on its head, such that:

  1. Data has primary demand, it is an asset in its own right and will increasingly be recognised as the end point to be sold and in demand. The value of information has risen. If data is the new gold, pharma executives are the new miners, prospecting eagerly for new sources and seeking ways to extract the maximum value for their enterprise.
  2. Data in the pharmaceutical industry often appreciates over time and is very fragile in terms of data integrity. With increasing costs for target discovery, R&D and post and pre-clinical trials, the cost of high quality data will continue to increase.
  3. Data is competitive in consumption but does create a perception that it is free. Data delivers competitive strength and increased value at every stage.
  4. Long term data is constantly at risk and needs continuous management to ensure data integrity. R&D risk is enormous; it takes on average 12 years and $2 billion to discover a successful drug. 56 new pharmaceuticals were launched from over 7,000 compounds in development.

Without a data management and a digital preservation strategy, much of the innovation and insight for these 7,000 compounds that could be retained and reused will be unavailable, lost or unreadable. There is no other industry that is exhibiting these challenges, on this scale today. Executives are recognising some of these new imperatives and asking themselves:

  • How can I re-use and recycle research and insight data?
  • How can I move towards new innovative insights quicker?
  • How can I achieve these insights more economically?

We know that 90% of all data is never looked at again. Leonardo da Vinci invented and designed the helicopter and countless other technologies hundreds of years before the actual manufacturing and material science capability were there to realise it. How many early stage research projects failed for the same reason? How do you know what you have if you cannot access it, synthesise the data together and search it effectively? Unleashing the huge data assets from regulated and research data calls for technology that integrates and manages legacy and current data types and sources of data flexibly and scalably – over decades, whilst maintaining the highest standards of data governance, data quality, and data security. Arkivum’s approach will let pharmaceutical companies increase efficiency, respond more rapidly to changing market demands, and ensure compliance while uncovering data relationships that lead to better outcomes with the data they already have.
The pharmaceutical industry is awash with large datasets, from home-grown pre and post clinical data to sales information. Procrastination is never good and with data it can have disastrous consequences, in terms of reputational risk, company valuation and even the sustainability of the industry itself. Whatever your current situation, benign neglect will not be the answer, act now, identify a key area of concern and start managing the data effectively. Look to data which is most fragile and at risk, such as end of life and decommissioned system data and address this first.
For further help with building your business case to start your digital preservation and data lifecycle management journey, click here to download our latest eBook. This eBook takes you through the steps required to build a compelling business case, and how to gain stakeholder buy-in.

Daniel Hickmore

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