The Current State of Consent

Biomedical research has long relied on broad consent models where participants provide a one-time, open-ended consent for their data to be used across a wide array of future studies. However, this traditional approach faces major ethical limitations especially with technology like genomic sequencing becoming more commonplace, generating rich yet sensitive datasets of genomic information with or without clinical annotations.

In a broad consent model, participants are limited in their ability to control how their genetic data is used after their initial consent and may also not receive information on how their information is used, despite the enormous potential of this information which may inform their healthcare, as well as that of their families. Other common considerations of participants when they are consenting to research are privacy and security of data concerns, which in a broad consent model is usually controllable only through an inflexible complete opt-out method.

As we move closer to the mainstreaming of genomics in the Australian healthcare setting, there is a need for a solution which offers robust and secure yet flexible systems of genomic data management, one that enables informed consent and reconsenting to align with participants' updated informed choice and maintain trust in healthcare and data sovereignty. Such a model would be critical in promoting informed health choices for the general public. The key challenge of developing such robust systems lies in the balancing of data protection and ethical practices with the need for efficiency and access across research, clinical, and population health contexts.

The traditional model of informed consent in genomics relies heavily on a skilled Genetic Counselling workforce to offer in depth pre-test counselling and education to patients. With the rapid expansion of genomic technology and its increasing use across all areas of healthcare and research, a digital solution to complement an informed consent discussion must be considered.

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The CSIRO and TRAIL Proposal: GeneGuardian

To address these challenges, we proposed GeneGuardian, a  framework for secure and ethical genomic data management centred around participant education and informed consent, which we are developing together with the MRFF-funded (MRF2017165) Newborn Gen Seq TRAIL (Newborn Genomic Sequencing: Therapy Ready And Information for Life) study. TRAIL aims to accelerate our understanding of the capabilities for using genomic sequencing technologies as a complement to newborn screening programmes, assessing feasibility, scalability (automation and bioinformatics) effectiveness and acceptability, alongside increasing logistical capacity and resources.

TRAIL are exploring the potential use of genomics as a complement to newborn bloodspot screening, which includes all of the nuanced complexities associated with seeking and providing consent in a dynamic way to such a test. Applying a dynamic consent (DC) model to the NSW newborn screening space represents a paradigm shift in the approach to consent in genomic data management for research and clinical applications.

The DC model puts participants at the centre of the decision-making by facilitating dynamic two-way communication between researchers/clinicians and the participants. This DC approach emphasises engagement and participant control, leveraging digital systems for efficiency while ensuring data security.

Key Components of GeneGuardian, with the first three directly applicable to TRIAL:

1. Self-Sovereign Identity (SSI): GeneGuardian leverages SSI to enable participants to control their data assets with verifiable credentials and presentations. This empowers participants to manage their digital identities and data access rights to independent organisations and/or studies, making it particularly valuable when multiple organisations seek access to their genomic data for different use cases.
2. Decentralised Dynamic Consent: GeneGuardian incorporates a decentralised dynamic consent platform, enabling participants to track, manage and change their consents in real-time.
3. Future-Proof Encryption: GeneGuardian proposes the use of post-quantum cryptographic methods to encrypt participants' genomic data, aiming to ensure long-term security against next-generation quantum computing attacks.
4. Interoperability: GeneGuardian aims to seamlessly integrate with existing and future healthcare systems by leveraging HL7 FHIR standards for its internal data model. While research systems currently use different standards (e.g., OMOP), ConsentGuardian anticipates future convergence towards healthcare standards and aims to bridge these gaps.

"Genomic data represents the most private information about the past, present, and future of an individual"

Dr Bertalan Mesko, the Medical Futurist

This quote by Dr Bertalan Mesko highlights the comprehensive and deeply personal nature of genomic data, underscoring its sensitivity and the crucial need for stringent privacy and security measures when dealing with such data.

GeneGuardian is working in concert with our wider thinking about safe genomic data management [1].

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