Clinical Data Harmonisation: From Silos to Insights
In the rapidly evolving world of pharma research and development (R&D), data has increasingly been recognised as a strategic asset. A successful drug is a testament to the rigorous data management throughout its development. Despite the vast possibilities that clinical data holds, its usability remains a challenge that prevents pharma organisations from tapping into its full potential. This blog explores the significant advantages, including improved data quality, consistency, and enhanced analytical capabilities, of developing harmonised clinical data products and how evolving data management practices and modern platforms are breaking down silos, enabling accessible insights and faster, data-driven decisions.
Building a solid foundation: Clinical data products
Modern clinical trials generate vast amounts of data, with Phase III trials producing an average of 3.6 million data points.1 However, this data is often stored in incompatible formats, limiting its use for insightful analysis.2 In today’s technology-enabled R&D environment, without access to harmonised high-quality data, the full potential of AI and machine learning in life sciences cannot be realised.
Our previous blogs on clinical data management have explored the opportunities and challenges that organisations face in reusing their clinical data and the business value of harnessing data to enhance the digitalisation of R&D activities.3,4 Underpinning the effective reuse of data and digitalisation of R&D is the creation of reusable, analysis-ready data products that bridge diverse sources, formats, and levels of detail, enabling comprehensive analysis
Unlocking opportunities: Driving value across R&D
Applying AI to harmonised clinical datasets, offers numerous opportunities in R&D, such as developing more targeted treatments, improving patient outcomes, and enhancing regulatory compliance. This can lead to increased productivity and cost-efficiency in drug development as demonstrated in Figure 1.
Figure 1. Opportunities unlocked through harmonised clinical data products
Source: Deloitte analysis, 2025
Overcoming key challenges: A pragmatic approach
To effectively implement clinical data harmonisation, a clear strategy and roadmap with defined objectives should be developed, ensuring alignment with organisational goals and maximising value.
Organisations should consider the following three factors as they approach their own data harmonisation journeys:
I. Business priorities
These priorities will vary depending on the organisation's pipeline, market competitiveness, and data usage across teams. For example, continuous glucose monitoring data collected in a diabetes trial can be valuable in other therapeutic areas where glucose levels are relevant, demonstrating the potential for data reuse across diverse clinical trials.
Prioritise therapeutic areas where data harmonisation can have the greatest impact, such as those where new insights could accelerate drug development or where harmonised data can support regulatory submissions or post-market surveillance activities. This prioritisation informs which specific data domains (e.g., medical history, lab results, adverse events) should be prioritised for harmonisation.
II. Data maturity
As data quality varies significantly, organisations should assess the maturity, completeness, and adherence of their data to data standards, enabling them to prioritise efforts and maximise impact.
Fortunately, established clinical data standards provide a foundation for harmonisation efforts. For example, the Clinical Data Interchange Standards Consortium’s (CDISC) Study Data Tabulation Model (SDTM), provides a standardised method for structuring and submitting data.5 Additional guidance on terminologies and methods, such as those from the Medical Dictionary for Regulatory Activities (MedDRA) and International Organisation for Standardisation (ISO), can also be used for items including dates and countries.
III. Data governance and privacy
Ensure datasets balance research value with data privacy and governance, and adhere to relevant international (GDPR, OECD Privacy Guidelines), regional (HIPAA), and sector-specific regulations (e.g., NHS Digital's Code of Practice) while employing a risk-benefit approach.
Charting a path forward
Harmonising clinical trial data is a complex and time-consuming process, highlighting the need for streamlined, standardised approaches and for industry leaders, to actively develop innovative solutions. However, establishing a universal harmonisation framework can be challenging due to the constantly evolving pharmaceutical landscape. Therefore, organisations need to be both logical and flexible, see Figure 2.
Figure 2. Overcoming challenges with a tailored approach to harmonisation
Source: Deloitte, 2025
Having a strategic transformation plan is crucial if organisations are to realise the full value of data harmonisation. Initiatives identified in the plan should be prioritised based on their value, technical feasibility and strategic alignment. Consideration also needs to be given to developing or acquiring the skills and talents needed for data harmonisation (a combination of data engineering, data science and clinical data knowledge).
Exploring opportunities for your organisation
Connecting disparate data points across therapeutic areas and disease indications paves the way for groundbreaking research, expanding treatment options and reaching wider patient populations. A structured approach to harmonisation, coupled with robust data management can empower R&D teams to better leverage cutting-edge technologies like AI and machine learning. Investing in the necessary capabilities, skills and talent, alongside strong leadership and governance, is crucial to unlocking the full potential of clinical data and, ultimately, delivering better patient outcomes.
Acknowledgements
The authors would like to thank Myrian Gaspar and Tanisha Patel for their contributions to the research and drafting of this blog.
Get in touch
Sam Karabon
Senior Manager | Deloitte Consulting LLP
sdkarbaron@deloitte.co.uk
Toi Neibler
Senior Manager | Deloitte Consulting LLP
tneibler@deloitte.co.uk
