Blog / 25 Feb, 2020

What does the future hold for data management in the pharmaceutical sector?

What does the future hold for data management in the pharmaceutical sector?

In Roman mythology, Janus was the god of beginnings, transitions, duality, and endings – he is depicted as having two faces as he looks to the future and to the past. If data in life sciences were to be represented by a mythological twin, it would be Janus.

The regulatory controls and requirements around data are incredibly and increasingly challenging. The amount of distributed data, systems and partners involved in the lifespan of a drug product has proliferated in recent years and the ability to centralise and manage data for the long term is more challenging than ever as a result.

However, data is a necessity – it validates science, helps take product to market and ensures products viability – and more importantly, holds immense, as yet unrealised value.

Compliance remains a core challenge, but getting clinical data management right will offer untold opportunities for Life Science organizations. Below, we have explored 4 key drivers of change that will influence the sector in the coming years.

1. Regulations

Life science companies are required to keep key GxP records (eTMF data, clinical study reports, lab notes etc…) for extensive periods, in some cases indefinitely. Regulatory authorities must have readable access to this archive throughout its lifetime – for inspection purposes or should they need to reconstruct a clinical trial.

This means that ensuring that quality data is created, stored, and made accessible in a secure way is now just as important as conducting the trial itself. Over the past decade, ever more data is digital and we’ve seen increased trust and reliance on digitally stored data.

Regulations and standards have needed to evolve to follow this trend:

  1. Robust data standards. Compliance officers, standards for data management and storage such as ISO 9001 and the rise of standards agencies (ICH, HL7) have become prominent.
  2. Patient-centric regulations. Regulations including GDPR, HIPAA  and FMD have been introduced to protect patients and their data among other things and have mandated for the digitalisation of data and file management.
  3. Quality-focussed regulations. GxP requirements and the FDA’s Title 21 CFR Part 1 don’t directly mandate the digital processes but serve as a core requirements in the groundswell of  industry  digital solutions that help businesses perform (and comply) in a more efficient way.

We’ve also seen many companies move to decentralised storage of data to prevent a single source of failure which could compromise integrity. Regionalisation has also become commonplace as companies seek to simplify their clinical data management processes by storing data ‘locally’ to aid compliance requirements. Counterintuitively, this often complicates matters as the organization then has to deal with multiple points of security, access and potentially different needs for retention and recovery.

Consolidated data storage and analytics tools that have the capability to meet numerous regulatory controls, facilitate better visibility and efficiency are now a must and we’ll see a notable uptick in the adoption of these solutions in the coming years.

Flexibility moving forward is also key. If we look at consumer and patient privacy laws as a use case, there is likely to be considerable change in the immediate future. The EU’s GDPR enshrines personal data rights for consumers, stating that “Personal data should be as broadly interpreted as possible” – including  “contextual” information and any information that can “directly or indirectly” identify a person. The California Consumer Privacy Act (CCPA) followed suit in January 2020 and it will become a de facto national standard as the numbers of Californians means most businesses in the USA will have to comply.

There is likely to be harmonisation in other areas as well over the coming years. The European Medicines Agency’s (EMA) guidance on Trial Master Files (TMFs) came into effect in mid-2019, now companies throughout the life science industry may need to store eTMF and clinical data for over 25 years and in line with the ALCOA+ principles. This poses a question for companies in the US which have no such law domestically, but will likely want to maintain compliance in the EU and potentially invest in future-proofing their processes at the same time.

Life science companies are often left with limited time to get a handle on the patient information they have and how they will manage it – non-digital and inflexible solutions will be found wanting very quickly in these evolving regulatory environments.

2. Creating efficiency in clinical trials

The competitive nature of the sciences means there is always a need to innovate and collaborate while creating efficiencies wherever possible. Harnessing the power of data offers the greatest opportunity to improve the efficiency and success of clinical trials, and the approvals process.

The cost of bringing a drug to market can approach and exceed the billion-dollar mark, and takes over a decade on average. Simultaneously, the patents for blockbusters are expiring and the drug pipeline is shifting towards precision medicines. This has created a perfect storm of demand for anything that can accelerate the process of drug discovery and development.

The industry is in the early stages of demand for rapid data reporting and analysis during a clinical study to enable adaptive studies for bio-marker based precision medicine trials.  As efficiencies and data collected in these studies grow, there is increased need to be able to manage this data over the long term and still untold value in it’s reuse for both future study planning and product development.

3. Data Analytics and Big Data

The pharma and biopharma industries have R&D at their core and will always rely on quality data to identify patterns, test theories and prove the efficacy of treatments.

Analytic technologies have evolved quickly over recent years and the capability now exists to process huge volumes of data, representing a great opportunity for scientists and life science companies.

Big data is full of unrealised potential – it could answer questions we don’t yet know to ask – and will lead to accelerated drug discovery and a better understanding of patient trends. We’re seeing companies ‘reuse’ genetic data to learn and make new discoveries from old data. While we don’t yet know how great the impact of this will be, to get the maximum value from this data, it must be stored and remain accessible for the foreseeable future to ensure that scientists can apply analytics tools and mine valuable information in a compliant environment.

4. Accelerating drug discovery and development

Now we are on the cusp of discovering how powerful artificial intelligence (AI), virtual reality (VR) and augmented reality (AR) might become in aiding research. There’s been a huge leap forward in processing capabilities in recent years which has allowed businesses to collect and manage additional data and various file types seamlessly. This has created opportunities to apply predictive analytics to the search parameters on large datasets and help researchers hone in on information and get more robust and reliable insights into which avenues are likely to yield the best results.

The industry is exploring greater access to more data and collaboration could help accelerate discovery and development. Pharmaceutical companies including AstraZeneca, Bayer, Celgene, Janssen Research and Development, Memorial Sloan Kettering Cancer Center, and Sanofi have launched Project Data Sphere. An initiative that sees the companies share historical cancer research data to aid researchers in the fight against the disease today.

Data is an ally

The ‘trickle down’ or ‘exponential effect’ of data collection means that companies need to move their focus beyond simply collecting active data. As it piles up, they will have to worry about it year after year so it is essential that they invest in accessible, flexible, secure, long-term data management solutions while ensuring compliance.

Importantly, this investment is not just about managing a ‘problem’. Such platforms will allow Life Sciences to leverage the incredible potential that easier data migration between organisations, removing silos and facilitating the ability to consolidate, access and reuse data will create.

Ultimately, data is an ally that can inform and guide life science companies through discovery, development and clinical trials and with the right solutions in place, there will be incredible opportunities for drug developers in the coming years.

George Waidell

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