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RWE, RWD and Tokenization for Asset Development: What Biopharma Teams Need to Know

Real world data and real world evidence drives insights that can be used throughout the product lifecycle. How can the industry compliantly link RWD to enrich insights and unlock the value of data?

Real world data (RWD), and real world evidence (RWE) derived from it, are becoming essential tools in the asset development team's playbook and can be leveraged at all stages of the development lifecycle. Linking disparate RWD with traditional clinical data can enrich broader understanding of the therapeutic area, tap into longitudinal patient journey post clinical trial completion, or augment real world health economic data with clinical trial data to understand impact on health economics earlier in the development lifecycle. Use of RWD, like clinical trial data, requires strict adherence to privacy laws. How can teams tap into this vast trove of patient-specific RWD without sacrificing patient privacy?  

"Tokenization is a foundational tool we can leverage to unlock the full value of RWD," stresses Mike D'Ambrosio, Vice President and Head of Real World Evidence Solutions at Syneos Health. Tokenization, in simplistic terms, is the process in which sensitive or personally identifiable information (such as name, date of birth or identifiable health data) is replaced with non-reversible encrypted tokens that have no identifiable details in or of itself. The technology de-identifies a patient record and generates one or more tokens for that record. These tokens are based on the personally identifiable information (PII) in the record. As a result, the tokens can be created consistently from any data set where the underlying PII is the same. By matching these tokens, data sources across a patient's record in one data set can be linked with a record for the same patient in a different set, providing a more detailed history for that patient without ever exposing the patient's PII.  

The ability to link disparate data from the same patient across multiple datasets offers many possibilities, including analysis of longitudinal healthcare trends for that patient or leveraging advanced analytics, artificial intelligence (AI) or machine learning to identify potential biomarkers for diagnosis or outcome prediction.  

So, how should asset development teams think about tokenizing patient data to provide the most value? D'Ambrosio and Bob Zambon, Vice President of Solution Architecture at Syneos Health, break down the critical points for developers: 

  • Broader value is obtained through a strategic play, not a tactical one. Proactively having sponsors critically appraise full development programs and map out an integrated evidence plan demonstrating RWE needs and value at different stages of the development cycle is crucial. This approach can maximize return on investment when overlaying a tokenization approach to link or enrich the body of evidence. In summary, asset developers need to be thinking about the future needs for RWE and RWD upfront.  
  • Consider economy of scale from a data and economic perspective by tokenizing an entire program, not just a study. "When teams generate a bespoke real world dataset, that data can be leveraged far more broadly than just for a specific study outcome. Using that data to generate insights that inform other assets, potential indications and competitor assets allows companies to further differentiate themselves within highly competitive markets," says Zambon. It's critical for development teams to understand that clinical trial data can have the principal purpose to contain data and endpoints of interest to those who matter most for short to mid-term gain (such as regulatory approval and reimbursement authorization). Comparatively, clinical trial evidence is a small part of the overall data available to add differentiated value. For example, beyond trial endpoints, RWD empowers health economics and outcomes research (HEOR), Medical Affairs and Commercialization teams to drive better analysis for future asset development through a complete understanding of the patient journey. In some cases, RWE from an entire program could be the most extensive existing data set on a specific patient cohort, making insights even more valuable to the whole therapeutic area. From an economic perspective, establishing a unified tokenization architecture and process that can be deployed across multiple studies instead of multiple-point solutions can dramatically shift the costs of trial tokenization by a factor of 10 or more. 
  • Value is in the eye of the beholder (for now). The perceived value of RWD is highly variable among stakeholders. For example, in the rare disease space, it is not uncommon for sponsors to use RWD from natural history studies to pre-identify patients but also gain a better understanding of the natural progression of the disease and more accurately define target product placement in the treatment continuum, optimize protocol, etc. Conversely, the value or utility of this RWD and translated RWE to patients and physicians is that the evidence and insights generated can have practical utility in their own understanding of treatment gaps, day-to-day treatment practices, patient treatment journey and other softer measures. The same can also be said of rare disease registries where the data needs of the patients and the wider community may differ from the developer's and stakeholders' immediate needs (regulators, payers, etc.). When considering the utility of tokenization, it is vital to consider within the wider strategy what the potential data linkage and enrichment is being used to solve for. It's critical in asset development always to remember that the ultimate end user of a drug product is the patient, their caregivers and their communities. Developers should therefore keep front and center not only what RWD and RWE will be critical for the developer but what data will be practically impactful to the patients and their communities and use this to drive our tokenization strategy. "If the patient community truly derive benefit from this data enrichment then that in some way is the biggest return-on-investment you can obtain from employing a tokenization strategy. The RWD/RWE is then being used to empower patients' and directly impact outcomes which can only benefit developers and patient communities" says D'Ambrosio. 
  • RWD can help identify more diverse patients for clinical trials. In terms of the FDA's 2022 push for more representative clinical trial diversity, tokenized RWD can connect social determinants of health or non-health to integrate into patient populations. Zambon explains, "previously, you may have only been able to look at claims data – like just all the patients with diabetes. Period. Now, teams can use tokenized RWE and link in demographic and social determinants of health information -- socioeconomic status, ethnicity, and gender -- to design trials to reach those diverse patients and ensure their impacts on safety and efficacy are fully understood." 
  • RWD can fill in the blanks. Many developers are facing a common challenge when patients are lost to follow up, particularly in some of the longer-term mandated follow up environments such as in cell and gene therapy trials where 15 years of long-term follow up are often required. "While not a silver bullet, tokenization can provide a safety net to be able to either back-fill missing follow up information or indeed enhance/enrich follow up data - leading to improved longitudinal understanding of product safety, efficacy and patient benefit" says D'Ambrosio. That ability to augment this RWD back into clinical data sets then provides a more holistic view of the product and this is an approach that many developers are now taking.  

While tokenization addresses privacy concerns about linking health data, the information derived can have tremendous impact on the entire product lifecycle – from enhancing registries to augmenting data needed for approval. "Using RWE and RWD is reshaping asset development into a more continuous data-driven loop" explains Zambon. "The insights this enhanced data provides are helping the industry reach a synergy between R&D and commercial throughout the development lifecycle, overall accelerating timelines, laying the groundwork for new assets, and bringing much needed therapies to market while providing unique value to both sponsors and patients." 

Is your team looking to leverage real world data and real world evidence into their product development strategy? Explore your options with our Real World Late Phase specialists at Syneos Health.


Mike D'Ambrosio, Vice President, Head of Real World Evidence Solutions, Real World and Late Phase at Syneos Health

Robert Zambon, PhD, Vice President, Solution Architecture at Syneos Health

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