Pharmaceutical IT leaders: Speed drug discovery and development with data lakes

In pharmaceutical and life sciences companies, data is vast, diverse, and growing. It includes such varied forms as clinical trial data, genomic sequences, assay biology,

electronic health record (EHR) data, regulatory and compliance information, and much more.

Without a unified data foundation, this vital data remains siloed and fragmented, hindering collaboration, innovation, and insights in drug discovery and development.

A cloud data lake is a secure, central repository for vast amounts of disparate data in their original form. It is a platform to integrate multiple data sources, and to pre-process and harmonize data. This data becomes accessible to a wide range of applications, including advanced analytics, text mining, machine learning, and GenAI.

With a cloud data lake approach, pharmaceutical IT leaders can address three key issues:

• Compliance: Centralizing data management and governance enforces security and regulatory requirements.
• Business use: Loading data based on business function priorities enables cross-functional data utilization for tasks such as clinical trials, patient impact analysis and many more.
• Scalability and reliability: Cloud services enable on-demand scalability for handling peak loads and create multiple copies of data to avoid data loss during failures.

IT leaders should consider these six basic steps for establishing a unified data foundation.

1. Assess the current data landscape: Survey your organization’s existing data landscape to identify data sources, formats, quality issues, and integration challenges.
2. Define your data governance framework: Create a robust data governance framework that clearly lays out policies and standards for data management, security, and compliance.
3. Integrate and harmonize data: Take time to integrate and harmonize data from various sources for data consistency, accuracy, and timeliness.
4. Understand the principles of Master Data Management (MDM): Implement MDM solutions to create a single, authoritative point of reference for each key data entity.
5. Focus on data quality and cleansing: Leverage data quality tools to identify and rectify data errors, duplicates, inconsistencies, and inaccuracies. Clean, high-quality data is essential for reliable insights and analytics.
6. Enable data analytics and AI: Build robust analytics and AI capabilities to leverage the data lake for actionable insights, innovation, and process optimization.

A systems integrator can speed data lake deployment

Partnering with an experienced systems integrator like Tata Consultancy Services (TCS) enables pharmaceutical IT leaders to quickly unify data via data lakes. TCS collaborates closely with Microsoft cloud services and data platforms – including Microsoft Fabric, Azure Databricks, and more – to establish scalable, secure, and agile data lake solutions.

The key benefits of this collaboration include:

• End-to-end data services: TCS has capabilities from architecture design to implementation and support and aligns them with business objectives.
• Advanced analytics and AI: TCS helps organizations unlock the full potential of their data by leveraging Azure’s full range of advanced analytics and AI capabilities.
• Security and compliance: TCS and Microsoft prioritize data security, privacy, and regulatory compliance with a suite of security services.
• Accelerated time-to-value: TCS and Microsoft shorten the time-to-value for data initiatives in pharmaceutical organizations.

The bottom line

A unified data foundation is critical for pharmaceutical organizations to optimize drug discovery and development. IT leaders can accelerate this process by matching the organization’s requirements with capabilities available from an experienced systems integrator.

To learn more, visit Patient-centered Care Models Taking Center Stage in Life Sciences.