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Protect Patient Identity, Maximize Data Utility and Comply with Regulatory Requirements

Scale your internal disclosure and transparency processes, leverage a quantifiable risk modeling process, adhere to Health Canada and EMA regulations, support voluntary disclosure requests using Real Life Sciences Protect and Managed Services experts.
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Road Tested - Regulator Proven

Purpose Built to Support Global Regulatory
and Voluntary Data and Document Disclosures

Real Life Sciences Protect is the industry leading solution to automate a fully quantifiable risk modeling, document redaction and anonymization process for your organization. With over 1 million pages and thousands of datasets processed successfully, RLS Protect is purpose built for pharmaceutical Sponsors and CROs to support the growing demands of regulatory bodies, changes in regulations and increased volumes from voluntary sharing requests.

A Repeatable Process

Metrics Driven Data Utility Optimization (MD-DUO)

A quantitative and metrics driven framework for maximizing data utility while balancing re-identification risk.  Implement a structured, high efficiency and proven approach to incorporate quantitative risk and data utility methodologies.

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Stay Ahead of Regulatory Changes

Exceed Regulator Expectations Using A Quantitative Data Analysis Approach

Traditional redaction approaches do not support data utility. Health Canada and EMA strongly prefer a quantitative risk modeling methodology for new submissions. Maximize data utility while minimizing re-identification risk using RLS Protect data scenario analysis.

Increase Speed & Efficiency

Promote Transparency and Data Sharing for Secondary Research

Balancing the need to protect the patient’s privacy with a need to maintain data utility is a difficult task without technology. Encourage innovation by supporting transparency and data sharing initiatives with the confidence that patient data is protected and data usefulness is retained. Enable secondary research bodies to further analyze data while protecting patient identities.

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Document & Data Anonymization

Replace Manual, Time Consuming Processes with RLS Protect's Purpose Built Capabilities

RLS Protect delivers repeatable automated workflows to batch process, model and anonymize datasets and documents saving you large blocks of time. Avoid highly manual processes that are difficult to quality control. Minor adjustments to business rules allow you to systematically re-process datasets for regulatory submission and voluntary disclosure –for example, adhering to different risk thresholds based on how the data will be consumed and by whom.

Efficient and Repeatable

Experience Matters:
Real Life Sciences Training and Process Best Practices

RLS provides an extensive range of documentation and training modules that help organizations transition from performing basic redaction and qualitative approaches to more advanced quantitative and automated anonymization processes. Learn of the requirements when submitting documents to Health Canada and EMA, and how to best navigate these processes.
  • Expert advisory services, including webinars and trainer-led tutorials around the latest de-identification techniques and regulatory changes
  • Technical support services, providing end-to-end, production implementation support
  • On-demand anonymization business processing outsourcing to support volume ‘spikes’ in your business

Let us show you how RLS can help.

Data & Document Anonymization Made Easy

We work with leading global life sciences companies, services providers and regulatory organizations.
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Metrics Driven Data Utility Optimization

Metrics Driven Data Utility Optimization (MD-DUO)

Use MD-DUO to take subjectivity out of the equation and provide a definitive set of guidelines from which to base disclosures. Provide regulators with objective data they can rely upon to make clear decisions. Inform Health Canada and EMA ahead of time to accelerate your regulatory disclosure timeline.

We're With You Every Step of The Way

Our team is made up of passionate leaders in the fields of machine learning, natural language processing, clinical trials, data analysis and regulatory submissions. We help Pharmaceutical Sponsors and CROs focus on your primary business goals while protecting patient identity and company confidential information while maximizing data utility and adhering to regulatory requirements.
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Clinical Trail Transparency and Disclosure Regulations

Not Sure How to Best Navigate the Regulatory Puzzle?
We've Got You Covered

RLS has been supporting Sponsor and CRO disclosure submissions for years. We understand the gotchas and how to stay clear of unexpected regulatory hurdles. The team members at RLS pride themselves on partnering closely with our customers and supporting them through the end-to-end process. Manage your business with the confidence that your regulatory submissions are defensible.

EMA Policy 0070

EMA Policy 70 seeks to enable the wider scientific community to make use of detailed clinical data to develop new knowledge in the interest of public health.

Health Canada PRCI

Health Canada's objective is to make anonymized clinical information in drug submission applications publicly available for non-commercial purposes following the completion of Health Canada's regulatory review process.

Voluntary Disclosure Policies

Making clinical trial data available for external secondary research or internal sponsor teams comes with its own set of challenges. Ensure your data is shared safely and the patient is protected.


Document & Data Anonymization, risk modeling, PIM meetings, regulator feedback, identifying timelines can all be tricky business. Inserting a repeatable process is key for many teams. We have gathered FAQs from Sponsors and CROs we have worked with to provide you with some insight.

Health Canada and the European Medicine Association require Sponsors to disclose clinical trial results. This includes providing an explanation of how personal information was anonymized so the identity of trial participants remains confidential while the trial results are made public.

Historically, Sponsors simply redacted information pertaining to study results. While redaction keeps personally identifiable information confidential, redaction renders otherwise useful attributes about that data unusable -- for example, a study participant's age, weight or other comorbitities which are relevant to trial results. A quantitative modeling approach uses advanced statistical methods to de-identify the information while maintaining the utility of the data. This allows the information to be useful for the reader of the study results and meaningful for purposes of secondary research by academic institutions and other researchers.

Regulators and Sponsors will accept a measured amount of re-identification risk in order to maintain data utility. Quantitiative risk modeling provides a framework to let you know which data variables must be transformed, which can stay in their original form and which must be redacted to meet the required risk threshholds while balancing protection of personal information.

RLS Protect and RLS Managed Services support the following teams: Clinical Operations, Clinical Development, Biostats, Medical Writing, Regulatory & Trial Disclosure Teams.

RLS has extensive experience with disclosure of large and small clinical trials and those with large and very small patient populations. With rare diseases, a more conservative approach/risk threshold is considered (i.e. larger equivalence class sizes). Grouping study participants into larger equivalence classes reduces their identifiability, ensuring we mitigate the risk of re-identification in rare disease studies.

RLS Protect is the industry leading "fit for purpose" solution to support data and document disclosure and anonymization requirements. RLS supports large and small Sponsors and CROs globally. Our Managed Services team combines regulatory knowledge with leading edge system capabilities to deliver dozens of EMA and Health Canada submission projects and hundreds of dataset processing and voluntary disclosure initiatives. To date we have processed over one million pages for Pharma organizations.

RLS Protect consists of two interoperable applications that are used to anonymize patient data. The Risk application generates a quantitative risk report, providing the sponsor with the risk metrics and most optimal transformation options to anonymize your data with the confidence that the required risk thresholds are being met while maintaining clinical utility . This report can then be loaded into the Docs application, automating all of the markings into their respective anonymized terms and values, thereby eliminating manual processes and increasing efficiency, accuracy and quality.