Data fabric for the pharmaceutical industry: a game changer

Everybody is ready for AI, except your data

In the life sciences industry, big data can translate into very big returns – even more so now, with the adoption of AI systems.

According to Gartner^®, "Using generative AI (GenAI) as part of the drug discovery process by pharmaceuticals and biotech can reduce the cost of preclinical drug candidates by at least 50% and the time to reach early clinical stages by at least 80%."^*

But for AI tools – including GenAI-enabled applications – to be effective, the underlying data must be accurate, unbiased, accessible, relevant and at the right level of granularity. If not, the quality of your AI output will suffer and your return on investment won't materialize.

In the biotechnology, pharmaceutical and biomedical industries, major advances are being made in smart manufacturing, where sensors gather large volumes of data from across the manufacturing environment.

The clean, processed data is then made available to employees as well as tools and systems via interconnected networks to be used along the whole value chain in predictive analytics, process optimization and decision-making.

Democratizing data

The challenge of continually managing all of this data can be solved by using a data fabric, an architecture that provides data services across cloud and on-premises endpoints.

It helps you manage your data and makes data available where it's needed, regardless of where it resides or how it is structured. Without proper data management, AI cannot deliver its full potential. And to manage data properly, you first need to understand it.

A data fabric can use AI and machine learning to automate data discovery, governance and orchestration. This approach improves data visibility and usability and assists in maintaining data security and compliance – an important consideration in the life science industry, where regulations are paramount and environments highly controlled.

In a recent webinar, I explained the importance of data integrity in life sciences – especially in the age of AI – and the key role a data fabric plays in supporting data strategies in these industries.

GxP – the good practice guidelines

The abbreviation "GxP" refers to "good [field] practice" – guidelines and regulations for ensuring a product is safe. The "x" is replaced by the field being referred to: GMP, for example, means "good manufacturing practice". Other good practices include laboratory (GLP), clinical (GCP) and distribution (GDP).

These guidelines are crucial in industries such as pharmaceuticals, biotechnology and medical devices, where product quality and safety are paramount.

GxP compliance is mandatory in regulated industries, and noncompliance can have severe legal consequences, including product recalls, damage to business reputation and, most importantly, patient risk.

Uniting GxP and data fabrics

NTT DATA's Data Fabric Accelerated for Life Sciences is a specialized private data platform – a combination of technologies and a methodology – designed for data-driven decision-making within organizations that are subject to GxP.

The platform can extract, transform and integrate vast amounts of data from different sources to enable new insights. It prioritizes data protection and security, and it's fully compliant with industry regulations and standards.

We provide computer system validation, data and development services to keep the data platform in a qualified state – meaning the data is considered reliable, accurate and usable

The Data Fabric Accelerated for Life Sciences supports not only advanced reporting and analytics but also collaboration with external entities by making data more accessible – thereby linking the entire value chain and supply chain with relevant information.

In this way, our GxP-compliant "data platform as a service" – backed by our 30 years of experience in the life-sciences industry – becomes a key contributor to your organization's data-driven success.

• * Gartner^®, Emerging Tech: Tech Innovators for Generative AI Novel Drug Discovery (Published: 31 October 2023, Eric Goodness)
  https://www.gartner.com/en/documents/4893531 (Gartner Subscription Required) GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

WHAT TO DO NEXT

Read more about NTT DATA's Data Fabric Accelerated for Life Sciences (Coming Soon) to see how it can make a difference in your organization.