How-To Guide: Next Generation Biobanking/Biobanking with the Next Generation

It has long been well established that the availability of an extensive, systematic collection of human samples (both diseased and healthy) with well-documented phenotypic data is a crucial requirement for developing and strengthening precision and preventive medicine. Advanced science and tailored medicine need a global, integrated data based on translational biobanking. Biobanking global data (biological, omics, profiling, interfamilial and intergenerational data) over time implies participation and engagement and defines new frontiers of scientific citizenship.

“Omics, artificial intelligence (AI) driven process automation, data analytics, robotics, the internet, and other emerging technological advances are driving the revolution of biospecimen science, both providing new insights into the genetic component of human disease and developing a more personalised approach to healthcare.”[1]

Integrating and digitalising real-world data and biobanked samples with data correlated and improved by omics, AI/machine learning technologies produce a shift in science and society, creating a revolution. The translational biobanking/medicine, with its digitalisation, can be our training ground to identify the impact of this shift on ethical, legal, and societal practices and to rethink the risk assessment accordingly, in relation to ethical review, informed consent/assent, and oversight governance processes within a Responsible Research and Innovation (RRI) framework aimed at promoting a democratic (inclusive, transparent, accountable) governance of science and innovation. It is a challenge that broadly impacts and concerns every person. No wonder that the Nature editorial on the Cambridge Analytica personal data controversy firmly stated that “Academics across many fields know well how technology can outpace its regulation. All researchers have a duty to consider the ethics of their work beyond the strict limits of law or today’s regulations. If they don’t, they will face serious and continued loss of public trust.”[2]

The ‘next-generation’ biobanking model may overturn the guarantees and the participatory practice we identified from the Nuremberg Code to today: it is a driving force not only for Precision Medicine but also for Predictive Medicine, introducing the need for new rights such as the right to an open future for the children as well as the right of reasonable interferences, especially regarding predictions drawn from big data analytics with low verifiability. So as not to reduce the consent to a farce and to enable every citizen to consciously act and engage within a dynamic complex scientific environment, innovative, responsible, and participatory assenting/consenting models are required; assenting/consenting models must be capable of time travel, just as data are capable of time travel and must be closely in dialogue and structured according to the governance. Conscious that the real game is played by triangulating a renovated across-time role of the third-party bodies such as Ethics Committees, biobank-registries, and Access Committees, systemic oversight governance should be based on reflexivity, inclusivity, and responsiveness, that should include all social actors, first and foremost citizens, and a multi-actor engagement action to redress power asymmetries, to avoid a slippery slope but also to evade double discrimination, both as a consequence of real-world-global data-driven research and a not-inclusion in research.

The impact and implications of the paradigm shift with the technologization of science, biobanking (next-generation biobanking), medicine, and de facto of health, as well as the RRI challenge at stake, concern first and foremost the next-generation, future citizens, future researchers. The next generation, both as future citizens and potential scientists, and researchers, are at the forefront of the development, sustainability, and equity of Translational Medicine, requiring an extended scientific community, which recognises and includes both citizens and the clinicians as partners, and regenerates research as a responsible participatory process. 

The sample-and-data-based translational research is a challenging training ground to empower children to be conscious of their rights to take part proactively in research processes and make informed decisions about their own health. The research ecosystem should fully evolve into a participatory scientific ecosystem that guarantees the setting and tools to recognise and include the next generation not merely as research participants, but also as actively engaged and empowered RRI actors who have a deep knowledge and understanding of their rights to health and science as contributors to translational medicine and biobanking participants.