From competition to collaboration: How secure data sharing can enable innovation

This article is brought to you thanks to the collaboration of The European Sting with the World Economic Forum.

Author: Hugo Ceulemans, Scientific Director, Discovery Data Sciences, Janssen, Johnson & Johnson & Mathieu Galtier, Chief Product Officer and Coordinator of the MELLODDY project, Owkin & Tinne Boeckx, Contract and grant project manager, Senior Life Sciences consultant, Avertim & Marion Oberhuber, Digital Health Consultant, Owkin & Victor Dillard, Commercial Operations Director, Owkin

• COVID-19 has necessitated a more collaborative way of working across sectors.
• Healthcare has been at the forefront of this shift and we must build on this momentum.
• Open data sharing can facilitate innovation and power a sustainable economic recovery.

Today’s economy is fundamentally driven by data – we already have more bytes than there are stars in the observable universe. Businesses are required to rapidly adopt technology to utilize this data and improve products and services.

This challenge has been dramatically amplified by COVID-19, creating a global health crisis as well as a supply and demand shock in many industries. While market forces will eventually bring back equilibrium, this may take years and have a significant negative social and economic impact, calling for novel mitigation strategies and innovation in business across industries.

Seventy-six percent of business executives agree that innovation requires new ways of collaborating with ecosystem partners and third-party organizations. This article is a pledge for out-of-the-box-thinking in business, healthcare and beyond, where competition and collaboration go hand in hand as “coopetition”.

Combining confidentiality and open-source

For many business leaders, collaboration equals data sharing. A research report by the European Commission on B2B data sharing cited fear of data privacy breaches as the main barrier to making data available to others, resulting in costly missed business opportunities. Indeed, collaboration is often associated with mistrust and concerns about losing control over data. Yet, given today’s technologies, is this really still a valid concern? What if businesses could get out of the “data gridlock” and collaborate without the risks associated with data sharing?

Decentralised approaches for collaborative data use are one of the top strategic technology trends for 2021, according to Gartner. Such technologies make data aggregation on a central server unnecessary – reducing the risk and cost of moving sensitive data from its original location and thus protecting data confidentiality and IP.

Our relationship to technology is changing from protectionism to democratization. —Hugo Ceulemans.

Even our relationship to technology is changing from protectionism to democratization. Today, whilst investing in proprietary IP is still valuable, businesses are increasingly recognizing the value of open-source and sharing insights. Contributing to open-source tools means putting transparency first while simultaneously fueling fast-paced innovation and building trust with stakeholders. Software giants such as IBM have endorsed open-source initiatives for some time now. The Linux Foundation, for instance, fosters open technology ecosystems and provides a platform for developing industry-wide data standards and governance. This promotes interoperability and supports businesses with cloud-native transformation.

Making a case for coopetition

Our biggest societal challenges cannot be tackled in isolation. From climate change and health crises to poverty and social exclusion – collaboration is essential. Coopetition is one such strategy: cooperating with competitors to multiply knowledge, skills and resources without losing your competitive edge.

Whilst some might not be comfortable with the thought of multiple winners, it is worth considering the risks of not taking a cooperative opportunity: delaying breakthrough discoveries, overlooking new markets, missing out on cost savings by duplicating efforts, or simply the risk of there being no winner at all. “Co-opetition requires mental flexibility, but firms that develop it can gain an important edge.” Harvard Business Review.

The number of use cases for coopetition is growing. In 1997, Apple and Microsoft famously announced a previously unthinkable strategic partnership that allowed Microsoft software to run on Apple devices. Both tech pioneers recognized the potential of unlocking new market opportunities outweighed the risk of going solo.

“We have to let go of this notion that for Apple to win, Microsoft has to lose.” Steve Jobs said at the 1997 Macworld Expo.

Tesla, more recently, chose to apply an open-source philosophy to their patents by announcing it “will not initiate patent lawsuits against anyone who, in good faith, wants to use our technology”. Competitors and the general public alike are stimulated to innovate and adopt electric vehicle technology. IMEC’s business model is another example of digital technology and nanoelectronics experts joining forces to build an open innovation model, keeping R&D costs low for its industry partners.

Coopetition in healthcare

Ripe for coopetition is healthcare, on account of the complexity of unmet medical needs, the sensitivity of health data accompanied by stricter regulations, and the staggering investment requirements. On average, it takes 13 years and €1.9 million of investment to bring a new drug to market. New paradigms are, therefore, vital to bringing down costs.

It is well known that pharmaceutical companies have accumulated immense proprietary data warehouses, representing an untapped source of information across data types. Imagine that the pharmaceutical industry could leverage each other’s data to build more powerful predictive models for drug discovery without compromising data and model privacy. What could this enable?

MELLODDY (Machine Learning Ledger Orchestration for Drug Discovery) is the first of its kind where the pharmaceutical industry is embarking on the journey of coopetition with the help of technology experts. This flagship project brings together 10 pharmaceutical companies to advance drug discovery using a decentralized and data-private machine learning technology called federated learning, built on open-source software.

In 2020, MELLODDY met its first milestone of successfully training a model at scale. The consortium is now working to prove that models can be more effective when trained on data across multiple institutions, demonstrating that coopetition is not only possible but beneficial for all involved. Beyond benefitting the drug discovery field with better predictive models, MELLODDY serves as a foundational case study for industry-wide coopetition and data challenges, combining open-source and confidentiality-preserving approaches to advance technological progress. Health and healthcare

How is the World Economic Forum bringing data-driven healthcare to life?

The application of “precision medicine” to save and improve lives relies on good-quality, easily-accessible data on everything from our DNA to lifestyle and environmental factors. The opposite to a one-size-fits-all healthcare system, it has vast, untapped potential to transform the treatment and prediction of rare diseases—and disease in general.

But there is no global governance framework for such data and no common data portal. This is a problem that contributes to the premature deaths of hundreds of millions of rare-disease patients worldwide.

The World Economic Forum’s Breaking Barriers to Health Data Governance initiative is focused on creating, testing and growing a framework to support effective and responsible access – across borders – to sensitive health data for the treatment and diagnosis of rare diseases.

The data will be shared via a “federated data system”: a decentralized approach that allows different institutions to access each other’s data without that data ever leaving the organization it originated from. This is done via an application programming interface and strikes a balance between simply pooling data (posing security concerns) and limiting access completely.

The project is a collaboration between entities in the UK (Genomics England), Australia (Australian Genomics Health Alliance), Canada (Genomics4RD), and the US (Intermountain Healthcare).

Knowledge sharing is the future

In game theory, positive-sum games are situations in which no one wins at the expense of others, yet the collective knowledge and resources will have grown. Coopetition is one such win-win situation. The continuous development of distributed learning projects with state of the art technologies has the potential to demonstrate that big data challenges, sensitive information and fragmented data ownership within competitive industries can indeed be solved collaboratively.

We invite business leaders to ask themselves: which major socioeconomic or industry challenges can be solved by sharing knowledge and combining insights with my competitors? The opportunity is here today to shift our thinking and dare to execute new paradigms for collaboration.