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Accelerating Data & Analytics Transformation in Life Sciences: Key Challenges and Solutions

Life Sciences has entered a new era of innovation, with breakthroughs across scientific disciplines that are driving major advancements in drug discovery and development. However, with rapid growth also comes mounting challenges for Life Science organizations to keep pace with explosive volumes of clinical, genomic, and image data. It is vital for Life Science organizations to harness the power of cutting-edge tools and technologies, particularly those capable of housing and analyzing tremendous amounts of structured, semi-structured and unstructured data. This impacts not only the ability to accelerate the development of new therapeutics but also optimizing key business functions and enhancing overall organizational efficiencies at scale.

Tackling complex data management challenges in Life Sciences

Bringing a drug or device to market involves substantial expenses and effort in navigating discovery, clinical, regulatory, and commercial challenges. Effective management of data across these business functions is essential to accelerating regulatory approval timelines and maximizing resources throughout the discovery, development, and commercialization stages. To accomplish this, the adoption of cloud-based data and analytics solutions becomes paramount in order to acquire, clean, store, catalog, and analyze these large datasets.

However, many Life Science organizations have been slow to adopt or modernize enterprise data management technology, largely still leveraging a combination of manual Excel sheets and stand-alone analytics point solutions to manage discovery, development, and commercial processes. With such massive and distributed data sets, these inefficient processes consume countless hours, days, or even weeks to process, ultimately slowing down progress and stalling critical stages of the development pipeline.

Benefits of migrating to the cloud for data management

Data and analytics solutions can help to de-silo information from several sources into a centralized repository, such as a data warehouse or data lake, providing easy, user-friendly access for employees. This accelerated data retrieval platform empowers Life Science companies to access critical data in a much more timely manner.

In addition, Machine Learning and Predictive Analytics are enabling companies to quickly analyze millions of potential data relationships in order to cull out critical insights. Comprehensive analysis of biomarkers, imaging, and other clinical data is now possible in very short time frames. Such tools are essential to having a 360-degree view of the patient to shorten the drug discovery and development process.

Beyond discovery and approval, there are numerous benefits to having a data platform to manage and optimize Supply Chain and Commercial processes:

  • Enables data-driven decision-making — for supplier selection, price negotiation, forecasting demand, and identifying risks.
  • Real-time monitoring of supply chain – companies want to reduce the lag time in analytics related to movement through the supply chain in order to optimize inventory levels, and meet increasing customer service expectations.
  • Integrate with supply chain partners – gain global supply planning visibility
  • Monitor effectiveness – from physicians and patients to caretakers selling and marketing tools and campaigns.

While traditional enterprise resource planning (ERP) applications are already effectively helping to collect shared transactional data from multiple sources—eliminating data duplication and providing data integrity with a “single source of truth”—they were not built as data platforms to aggregate and leverage all an organization’s data.

Unlock the Power of Holistic Data

Today’s modern, Cloud-based data and analytics platforms provide a cost-efficient and scalable solution for organizations to harness the power of ALL their data. These Cloud-based platforms typically include a data lake for storage of all data at low cost (structured, semi-structured, and unstructured), a data warehouse for storage and analytics of transformed, governed, and curated data, and an analytics layer to support access to information and insights as and when needed—including on a real-time basis.

These Cloud-based data and analytics platforms also enable a whole new level of data sharing among industry participants without having to transmit files to each other, dramatically increasing efficiency and improving the customer experience. To gain a comprehensive understanding of operations, increase the pace of innovation, improve the customer experience, and make use of the massive volumes of information available to Life Sciences companies, it is essential to have the correct infrastructure.

Once in place, a scalable, flexible, and efficient data and analytics solution enables Life Sciences organizations to get actionable insights from all data sources across the entire business. Equipped with this level of information, Life Science organizations can:

  • Accelerate drug discovery and development cycles
  • Gain enhanced visibility into important transactional flows that empower better-informed data-driven decisions and efficiencies throughout the entire business
  • Drive business process improvements with cross-function views of Research, development, Production, Quality, Operations, and Finance, leading to a deeper understanding of the state of the enterprise

Importance of the right guidance and third-party support

Before embarking on the implementation of a Cloud-based data and analytics platform, it is crucial to collaborate with a trusted Data and Analytics partner who possesses a profound understanding of the Life Science industry’s processes, challenges, and ecosystem. Expertise in connecting a supply network, implementing process manufacturing, managing clinical trials, facilitating workforce recruitment and training, ensuring compliance with regulatory GxP standards, and enabling foreign currency financial reporting is essential for a successful implementation. By appropriately managing and accounting for these vital components, you can ensure the best practices are followed throughout the implementation process.

By tapping a third-party partner experienced in assessing unique data challenges and evaluating current systems, the outcome will be an impactful solution to both short- and long-term business needs and goals.

To learn how we help Life Science companies achieve a new level of enterprise performance, leveraging the entire data ecosystem to achieve game-changing improvements in drug discovery and development, business operations and customer experience.

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