12 LABOURS – Enabling development and clinical translation of virtual human twins

Dr Thiranja P. Babarenda Gamage, Chinchien Lin, Linkun Gao, Dr Jiali Xu, Dr Ayah Elsayed, Alan Wu, Mathilde Verlyck,
Dr Greg Sands, Koray Atalag, Misty Edmonds, Assoc Prof Anthony Doyle,Prof Martyn Nash, Prof Peter Hunter, Assoc Prof David Nickerson, Auckland Bioenginering Institute, Clinical Translational Technologies.
Yvette Wharton, Andre Geldenhuis, Martin Feller, Laura Armstrong, Dr Bincy Jacob, Klim Belchev, Centre for eResearch
Nick Jones, Claire Rye Jun Huh Nathalie Giraudon, New Zealand eScience Infrastructure
Funder: New Zealand Ministry of Business, Innovation and Employment

Figure 1. 12 Labours’ 3 tech platforms

Overview

Over 20 years ago, the Auckland Bioengineering Institute (ABI) pioneered the Physiome Project, which aimed to:

Developing computational models of cells, tissues and organs to improve our understanding of human health and disease.
Investigating how every component in the body, from molecules up to organ systems works as part of the integrated whole.
Establishing open community standards for the archiving and sharing of reproducible and reusable computational models.

The 12 LABOURS Project extend the framework to develop personalised Physiome models and brings together this large body of knowledge to create a generic digital twin of the human body. These generic digital twins are then personalised from clinical images, diagnostics data, implantable and wearable devices. (Figure 1)

This provides:

better understanding of an individual’s physiological processes and any changes that could lead to serious health consequences,
enables medical professionals to perform controlled and repeatable tests to discover how outcomes differ for various interventions leading to rapid selection of optimal interventions for the patient,
forms a basis from which new strategies can be developed to treat diseases.

This initiative that is supported by a New Zealand Ministry of Business, Innovation and Employment (MBIE) grant is being applied initially in clinical workflows (Figure 2) for:

developing biomarkers for pulmonary hypertension,
enhancing rehabilitation techniques for upper limb disorders, monitoring uterine health, and
automating the reporting of breast cancer from diagnostic magnetic resonance images (MRI)

The anticipated outcomes of the project include:

Adoption of the technologies developed to support the development of all clinical workflows being developed by researchers at the Auckland Bioengineering Institute and their national and international collaborators
Improved health outcomes by enabling personalised treatment to disease and allowing proactive treatment.
Implantable and wearable devices will allow the ongoing monitoring and management of health conditions.
Economic impact for Aotearoa/NZ through the spinout of medical technology companies.
Position Aotearoa/NZ as a world leader in medical technology.

More information about the project can be found in the following links: 12 LABOURS project website, 12 LABOURS Seminar Series.

This case study will highlight two initiatives being developed in the 12 LABOURS project – the DigitalTWINS platform and the DigitalTWINS repository, which is being developed by the ABI’s Clinical Translational Technologies Group.

Figure 2. Clinical workflows initiative

DigitalTWINS Platform

As part of the 12 LABOURS project, an open-source collaborative platform called “DigitalTWINS” (Digital Translational Workflows for INtegrating Systems) is being developed. (Figure 3) This platform aims to provide common infrastructure and services to support the assembly of computational physiology workflows for creating personalised digital twins, while also supporting researchers in conducting clinical studies to demonstrate the efficacy of these workflows.

Infrastructure and services being developed for the platform include:

Enabling uploading of data including health research and clinical measurements, computational models, tools,
and existing clinical workflows.
Storing data in an access-controlled and harmonised database
Assembling and executing clinical workflows that will personalise computational models (digital twins) for clinical applications of interest.
Providing a web portal to allow secure access for different end-users to interact with the platform including:

- Data catalogues (“yellow pages”) for users to easily find available data for reuse
- Researcher dashboard to allow rapid testing of assembled clinical workflows on clinical measurements
- Clinical research study dashboard, where clinicians and researchers can work together to perform studies to assess the efficiency of the clinical workflows they are developing
- Patient dashboard, where patients can view their own digital twins that have been created when clinical workflows are run using their data
- Education dashboard, where visualisations from digital twins can be used to intuitive communication of complex health concepts.
Connecting to health systems to enable clinical studies to be more efficiently performed to accelerate translation of these clinical workflows.

Figure 3. DigitalTWINS platform

A prototype of the platform has been implemented on the ARDC Nectar Cloud with support from UoA Centre for eResearch and the New Zealand eScience Infrastructure (NeSI) team. It is currently being tested with the four clinical workflows being developed in the 12 LABOURS project. A production version of the platform will then be deployed for adoption across ABI. The platform is envisioned to become a national initiative in the future, for example, to help support the MedtechIQ initiative.

DigitalTWINS repository

Developing novel technologies, such as digital twins, for improving our health, well-being, and quality of life requires addressing the grand challenge of understanding how our organs link and work together. This knowledge is essential for discovering new approaches to diagnosing and treating diseases that affect multiple organs, such as cancer, respiratory and heart diseases, stroke, and diabetes. The information required to achieve this necessitates detailed measurements made with specialised devices in specific cohorts, which may not yet be part of standard data collection protocols in large-scale initiatives. Therefore, it is crucial to establish a resource and standardised protocols that enable the collection, linking, and reuse of data across multiple specialised research studies, while also enabling this data to be linked to existing samples in biobanks, and national health registers. Furthermore, it is also important for results derived from studies to be accessible for reuse. Critically important is upholding and giving practical effect to governance of Māori Data and ensuring Māori have are actively involved in decision-making. This will significantly enhance our ability to support groundbreaking credible research and drive forward innovations that improve health outcomes and quality of life.
The 12 LABOURS DigitalTWINS Repository is a pioneering initiative aimed at creating such a data resource where health information from participants across multiple research studies can be contributed, linked, and reused with informed consent. This invaluable Repository will deepen our understanding of the human body and is essential for developing technological innovations, such as digital twins of patients, hospitals, and populations for advancing human health, social, cultural and economic well-being, and quality of life.

Establish consistent procedures and infrastructure that is underpinned by data sovereignty principles for contributing and accessing data from the Repository.
Provide standardised protocols and infrastructure for linking data from contributing research studies.

Enable secondary use of previously contributed data in new research studies, once appropriate approvals are obtained.
Facilitate future contact with participants to gather additional data in new studies and link it to their previously collected data in the Repository.
Implement a consistent approach to data management in accordance with international principles that aim to make data findable, accessible, interoperable, and reusable.

The Repository includes the following components:

Data Contribution and Access Committee (DCAC) who will assess data contribution and access requests.
Data Management Plan: Outlining procedures for secure, ethical, and responsible data contribution and access that give effect to data sovereignty principles, Consent Form Options, and a data de-identification and linking protocol.
Data Platform: Comprising four tiers of data:
- Restricted Access, Identifiable Data Tier: Stores participant recruitment and consent information from contributing studies
- Restricted Access, De-identified and Linked Data Tier: Contains data from all contributing research studies, stored according to a data de-identification and linking protocol
- Restricted Access, De-identified and Unlinked Data Tier: Provides necessary data subsets for study teams with DCAC approvals.
- Public Access, Data Tier: Contains non-sensitive metadata to facilitate findability of data within the Repository along with any publicly accessible datasets.
Governance Board: Oversees the Repository, guided by Terms of Reference.

The vision for the repository is to ensure that participants’ data continues to positively impact the well-being of this generation and contribute to allowing future generations (mokopuna) to live healthy lives.

A New Zealand Health and Disability Ethics Committee (HDEC) application has been created in consultation with the community and a number of organisations, and is currently undergoing internal University of Auckland review prior to submission to HDEC for ethics approvals.

Acknowlegement
“The UoA Centre for eResearch has provided invaluable support for the development of the DigitalTWINS platform and repository. This includes providing infrastructure (virtual machines and storage) that has been used for deploying the prototype of the platform and for running the initial 12 LABOURS clinical workflows. CeR has also provided data management guidance and testing of Secure Research Environments (SRE) where the repository could be deployed.”