Article | January 4, 2024
Discovery through data transparency: at the heart of scientific collaboration
With rapid development and adoption of advanced bioanalytical technologies, the capacity for data generation has grown exponentially, enabling the output of multi-omics data at greater depth and scale than ever before. The implementation of innovations including next-generation sequencing and next-generation mass spectrometry approaches have accelerated the pace of scientific discovery across disciplines, propelling advancements in biomarker discovery, target identification, and precision medicine through data that builds a holistic view of human biology, disease, and drug response.
Generating such large amounts of data at speed often requires high-powered equipment and specialized expertise. In many cases, researchers and drug developers choose to outsource bioanalytical work to CROs or discovery service providers, with a goal of accelerating timelines and enhancing discovery while optimizing cost effectiveness. The increasing scale and complexity of omics studies also means these engagements have become much more than just data generation projects. Service provider relationships have evolved from a transactional engagement to a pivotal scientific partnership, in which they also help to define experimental parameters and interpret results.
As these scientific collaborations deepen, however, an important question comes to the forefront – who actually owns the data?
Data transparency: a scientific and strategic imperative
Data is the lifeblood of scientific innovation, and data transparency is imperative to ensure the accuracy, reproducibility, and quality of findings that inform discoveries and drug development. The scientific community has increasingly embraced the notion of open data sharing to enable discovery, most notably with the creation of FAIR Data Principles developed by diverse stakeholders across academia, biopharma, and publishing to lay out steps for ensuring research data and metadata is Findable, Accessible, Interoperable, and Reusable. These guiding principles are aimed at improving efficiency and collaboration in scientific R&D. Many scientific journals follow FAIR Data Principles and require authors to deposit their data in community repositories for public access.
Most recently, the National Institutes of Health (NIH) set forth a new Data Management and Sharing (DMS) Policy which mandates that all scientific data – including raw and processed data – generated through NIH-supported research be publicly shared. NIH references multiple reasons for promoting scientific data sharing, from accelerating biomedical discovery research to enabling validation of research results and their reuse in future studies.
Data transparency is equally important for biopharmaceutical investigators, as regulators and auditors might request access at various points in the drug development process to confirm the rigor and reliability of data on which findings have been built, especially for more stringent applications such as New Drug Application (NDA) or Biologics License Application (BLA) packages for marketing approval. Owning this data in full also protects precious IP in the competitive pharmaceutical landscape.
Why data ownership should be a key consideration when selecting a discovery partner
When forming collaborations with an outsourced discovery partner, aspects of data transparency and ownership should not just be a procedural detail, but a topic that is discussed early and defined upfront. All partnerships are structured differently, and can range from sharing all generated data to delivering only processed results, and/or allocating IP rights to the partner for generating the data. Understanding your CRO’s standard data sharing policies and defining any caveats for your project will help avoid surprises as the partnership progresses while maximizing the service provider’s value to your study.
In these discussions, there are many reasons why indexing toward full data access and ownership can benefit your organization, including:
Completeness of data for confident decision making – The data your CRO delivers can inform critical drug development program decisions, from target selection to determining whether to progress a clinical trial. When you are able to see the entire scope of discovery data, you can have a clearer understanding of the service provider’s research processes, including their data QC and analytics approach. Full insight into how findings were generated – and why signals were selected as significant over others – builds confidence in the delivered results and in the decisions that are based off the data.
Flexibility for iterative, adaptive research – Data transparency ensures that data assumes a living identity, and can grow and mature and be revisited in the future. Your own team can delve into the entirety of the data to iterate on the methodologies initially used or perform their own analyses and data mining based on evolving insights. Access to the raw data also gives you opportunity to leverage it in subsequent studies by integrating additional datapoints and/or sharing the data with other partners for additional interpretation in the context of new projects.
Protection for IP and patentability – Full data ownership is paramount for ensuring the robust protection of your IP, particularly when applying for patents. Owning all data enables you to present a thorough and compelling case for the novelty, inventiveness, and utility of your therapeutic innovations, meeting exacting patent standards and safeguarding your groundbreaking discoveries, drugs, and technologies from potential infringement or unauthorized use.
Questions to ask your service provider about data sharing
Partnering with a CRO can amplify your ability to innovate, giving you access to unique technologies to generate more biomarker data that can be applied toward advancing precision drug development. No matter the type of scientific collaboration you decide to pursue, it is vital to do your due diligence before signing a contract, especially regarding data transparency and ownership. Here are a few questions we recommend asking:
- What type of data is returned to me, and in what formats, and what is retained by the CRO?
- How do you validate the collected data for accuracy and reliability?
- Who owns the unprocessed and raw data files, and will my organization have access?
- What sort of IP constraints are involved in a standard project or for one in which we agree to share data rights?
- How long do you retain raw data, and what is the process for data disposal after a project is completed?
As pharma-CRO relationships become deeper and more scientifically collaborative, the importance of clear delineations in data access and ownership cannot be overstated. By proactively addressing questions of transparency and intellectual property with potential service providers, you can ensure a productive partnership that enables meaningful discovery.
