Publications

Publications

Blockchain Compliance by Design: Regulatory Considerations for Blockchain in Clinical Research

Abstract:
As clinical research moves toward real-world data capture with increased data sharing, there is a growing need for patient-centered technologies that ensure data authenticity and promote researcher and patient access. Blockchain is one of an emerging set of distributed ledger technologies with the potential to offer both research data transparency and trust, while offering robust security measures. As blockchain-based systems are being developed for clinical research applications, these systems may be required to follow state and federal research regulations, such as ethical protections for human participants and data privacy.

Accelerating Life Sciences Research with Blockchain

Abstract:
As life sciences research becomes increasingly focused on patient-centered technologies that allow for remote participation and greater access, distributed ledger technologies (“blockchain”) are being developed to address these needs. Blockchain-based applications range from basic functions, such as securing electronic data with audit trails, to honoring research participants’ informed consent for secondary uses of their data, and to the advanced features of aggregating data on a single platform for sophisticated machine learning, and hundreds of examples in between. There are many questions, however, about the best uses of blockchain and implementation strategies for life sciences research. This chapter introduces uses of blockchain for life sciences research and offers ethical, regulatory, and practical considerations for implementation. Recommendations are pertinent for blockchain developers, researchers, and life sciences organizations considering blockchain solutions for their research.

Convergence Mental Health: A Transdisciplinary Approach to Innovation

Abstract:
The world is in the throes of a global health, economic, and mental health crisis with severe physical, societal, and economic ramifications. Modern mental health problems are characterized by their complexity, multisystemic nature, and broad societal impact, making them poorly suited to siloed approaches of thinking and innovation. To solve the unprecedented complexities and challenges associated with the current global crisis, a paradigm shift is needed. Convergence science integrates knowledge, tools, and thought strategies from various fields and is the focal point where novel insights arise. In the context of mental health, convergence involves integration of scientists, clinicians, bioinformaticists, global health experts, engineers, technology entrepreneurs, medical educators, caregivers, and patients; synergy between government, academia, and industry is also vital.

Blockchain Predictions for Health Care in 2021

Abstract:
With coronavirus (COVID) spreading across the world and the health care system being pushed toward more digitization and technology, last year was a unique year of human tragedy. There is a silver lining to this tragedy, that is, providers, payers, and pharma companies have shifted quickly toward better technologies, including artificial intelligence (AI) blockchain, and so on.

Ethical Benefits and Drawbacks of Digitally Informed Consent

Abstract:
As organizations steadily adopt remote and virtual capabilities, informed consent processes are increasingly managed by digital technologies. These digital methods are generating novel opportunities to collect individuals' permissions for use of private information but are blurring traditional boundaries of consent communication and documentation. Therefore, the rapid growth of digital technologies used for informed consent as well as the sheer volume of data resulting from electronic data capture are generating complex questions about individual engagement and data practices. This chapter presents emerging risks, benefits, and ethical principles about digital informed consent methods and technologies. For the areas where digital informed consent creates ethical uncertainties, ethical guidelines and user-design recommendations are provided.

Health Datasets as Assets: Blockchain-Based Valuation and Transaction Methods

Abstract:
There is increasing recognition that health-oriented datasets could be regarded as intangible assets: distinct assets with future economic benefits but without physical properties. While health-oriented datasets—particularly health records—are ascribed monetary value on the black market, there are few established methods for assessing value for legitimate research and business purposes.

An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology

Abstract:
Current best practices in tumor registries provide a glimpse into a limited time frame over the natural history of disease, usually a narrow window around diagnosis and biopsy. This creates challenges meeting public health and healthcare reimbursement policies that increasingly require robust documentation of long-term clinical trajectories, quality of life, and health economics outcomes.

Hybrid Healthcare Enhanced by Blockchain

Abstract:
As hybrid healthcare organizations strive to combine traditional in-person treatment models with digital health technologies, there is a need to manage data and technologies more effectively and efficiently. Blockchain technology is increasingly implemented in healthcare and may enhance functions to allow healthcare providers more capabilities and flexibility as they desire to utilize more features of digital health. At its most basic, blockchain is a time-stamped sequential list of data linked together using cryptography and managed by a distributed cluster of computers: a “distributed ledger technology.”

The Future of Blockchain

Abstract:
Blockchain's current uses demonstrate potential for enhancing efficiencies and patient-centered solutions in life sciences research. For blockchain to continue to present new features and remain relevant in life sciences research, it is critical for blockchain capabilities to evolve and integrate with newer technologies. This chapter introduces the role of blockchain technologies in smart data, quantum computing, digital twins, and the emergence of the metaverse. Additional predictions and recommendations for preparing for future blockchain needs are provided.

Regulatory Compliance Considerations for Blockchain in Life Sciences Research

Abstract:
Life sciences organizations are increasingly considering or utilizing blockchain as part of electronic systems used in life sciences research. However, these organizations may not be familiar with how life sciences regulations are applied to various uses of blockchain. There is additional confusion about whether some of the features inherent in blockchain, such as audit trails, may meet regulatory requirements for electronic records and signatures. This chapter explores how various blockchain features could meet U.S. Food and Drug Administration (FDA) regulatory requirements for electronic records and signatures, with cautions about necessary documentation expectations.

Valuing Research Data: Blockchain-Based Management Methods

Abstract:
Research data sets are not just considered highly valuable for scientific purposes; these data sets could be sold and traded for economic value. Data sets could also be regarded as intangible assets, which do not have physical properties but could provide future economic benefits. With consideration that life sciences organizations possess thousands of siloed data sets, these could be sold to support additional research and could add value when life sciences organizations are appraised.

Introduction to Blockchain

Abstract:
As life sciences research organizations explore methods to facilitate patient-centered and innovative technologies, they are increasingly exploring distributed ledger technologies (“blockchain”) to address many of these needs. Blockchain is demonstrating the potential to transform life sciences research, allowing more data capabilities and innovation. Blockchain-based applications vary from audit trails for provenance to integrating remote devices to managing data for decentralized trials.

Data continuity and linkage in the healthcare ecosystem

Abstract:
Data linkage is a method of bringing together disparate data sets about the same individual or entity to create comprehensive, richer data sets. Data linkage has been used to link insurance claims, electronic health records, registries, research databases, and even consumer data. The linkage allows for constructing chronological sequences and associations of exposures and outcomes to provide valuable insights for improving health delivery, research advances, and public health. This chapter provides an overview of data sources, preparation, and linking methods for healthcare projects and FDA-regulated studies. The chapter draws attention to ethical considerations for informed consent and privacy-preserving practices.

The Emergence of Blockchain-Based Dynamic Consent in Patient-Centric Health Information Sharing and Health Research: Protocol for an Integrative Review and Instructions for Future Research and Innovation

Abstract:
Blockchain has been proposed as a key technology to share health information and facilitate a shift towards more patient-centric research and decision-making. For instance, blockchain-based dynamic consent has been suggested as a potential solution to consent challenges encountered in longitudinal research and research repositories. However, blockchain-based dynamic consent is a relatively new concept, and it is not yet clear how well the suggested implementations will work in practice. While some studies and pilot projects explore blockchain technology in dynamic consent, there is no consensus on whether this technology can be effectively utilized with health or research data.

‘Block-Change’: Exploring Change Management Principles to Overcome Challenges in Blockchain Adoption

Abstract:
Blockchain technology has attracted significant interest and investment over the past decade across multiple industries. While the research and development has been robust and there has been no shortage of attempts at implementation, successful implementations at scale have been somewhat limited.

Blockchain-orchestrated machine learning for privacy preserving federated learning in electronic health data

Abstract:
Machine learning and blockchain technology have been explored for potential applications in medicine with only modest success to date. Focus has shifted to exploring the intersection of these technologies along with other privacy preserving encryption techniques for better utility.

End-to-end privacy preserving deep learning on multi-institutional medical imaging

Abstract:
Using large, multi-national datasets for high-performance medical imaging AI systems requires innovation in privacy-preserving machine learning so models can train on sensitive data without requiring data transfer. Here we present PriMIA (Privacy-preserving Medical Image Analysis), a free, open-source software framework for differentially private, securely aggregated federated learning and encrypted inference on medical imaging data.

A Taxonomy of Attacks on Federated Learning

Abstract:
Federated learning is a privacy-by-design framework that enables training deep neural networks from decentralized sources of data, but it is fraught with innumerable attack surfaces. We provide a taxonomy of recent attacks on federated learning systems and detail the need for more robust threat modeling in federated learning environments.

2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments

Abstract:
Federated Learning harnesses data from multiple sources to build a single model. While the initial model might belong solely to the actor bringing it to the network for training, determining the ownership of the trained model resulting from Federated Learning remains an open question. In this paper we explore how Blockchains (in particular Ethereum) can be used to determine the evolving ownership of a model trained with Federated Learning.

A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification

Abstract:
This work provides a comprehensive review of existing frameworks based on secure computing techniques in the context of private image classification. The in-depth analysis of these approaches is followed by careful examination of their performance costs, in particular runtime and communication overhead.

Pragmatic, Interdisciplinary Perspectives on Blockchain and Distributed Ledger Technology: Paving the Future for Healthcare

Abstract:
Background: Blockchain and distributed ledger technology is a disruptive force in healthcare. Methods: This article provides a globally relevant, interdisciplinary perspective intended to aid disparate group of actors, participants, and users that represent the diverse stakeholders of an increasingly complex and technologically reliant healthcare system. Domain expertise reinforced by literature published via industry, technical, and academic venues was used to inform these perspectives.

Blockchain in healthcare, research, and scientific publishing

Abstract:
Data are being transmitted and stored on cloud-based networks, including clinical, research, and publishing data. These cloudbased systems often lack comprehensiveness, accessibility, interoperability, confidentiality, accountability, and flexibility, which can cause delays for medical treatments, slowed research projects, and general inefficiencies. The advent of blockchain-based technologies provides a reliable solution to ensure that data storage and access are standardised and transparent, independent of a trusted third party.

Blockchain Compliance by Design: Regulatory Considerations for Blockchain in Clinical Research

As clinical research moves toward real-world data capture with increased data sharing, there is a growing need for patient-centered technologies that ensure data authenticity and promote researcher and patient access. Blockchain is one of an emerging set of distributed ledger technologies with the potential to offer both research data transparency and trust, while offering robust security measures. As blockchain-based systems are being developed for clinical research applications, these systems may be required to follow state and federal research regulations, such as ethical protections for human participants and data privacy.

Blockchain in healthcare, research, and scientific publishing

Abstract:
Data are being transmitted and stored on cloud-based networks, including clinical, research, and publishing data. These cloudbased systems often lack comprehensiveness, accessibility, interoperability, confidentiality, accountability, and flexibility, which can cause delays for medical treatments, slowed research projects, and general inefficiencies. The advent of blockchain-based technologies provides a reliable solution to ensure that data storage and access are standardised and transparent, independent of a trusted third party.

The case for establishing a blockchain research and development program at an academic medical center

To develop a research and development program to study factors that will support research, education and innovation using blockchain technology for health in an effective and sustainable manner. We proposed to conduct qualitative research to generate insights for developing a market strategy to build a research lab for the promotion of blockchain technologies in health in academic environments. The team aimed to identify the key barriers and opportunities for developing a sustainable research lab that generates research, education, and application of blockchain in healthcare at an academic medical institution and test those strategies in a real-world scenario.

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