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Can dynamic consent facilitate the protection of biomedical big data in biobanking in Malaysia? (Papers: Mohammad Firdaus Abdul Aziz & Aimi Nadia Mohd Yusof | May 2019)0

Posted by Admin in on October 20, 2019
 

Abstract
As with many other countries, Malaysia is also developing and promoting biomedical research to increase the understanding of human diseases and possible interventions. To facilitate this development, there is a significant growth of biobanks in the country to ensure continuous collection of biological samples for future research, which contain extremely important personal information and health data of the participants involved. Given the vast amount of samples and data accumulated by biobanks, they can be considered as reservoirs of precious biomedical big data. It is therefore imperative for biobanks to have in place regulatory measures to ensure ethical use of the biomedical big data. Malaysia has yet to introduce specific legislation for the field of biobanking. However, it can be argued that its existing Personal Data Protection Act 2010 (PDPA) has laid down legal principles that can be enforced to protect biomedical big data generated by the biobanks. Consent is a mechanism to enable data subjects to exercise their autonomy by determining how their data can be used and ensure compliance with legal principles. However, there are two main concerns surrounding the current practice of consent in biomedical big data in Malaysia. First, it is uncertain that the current practice would be able to respect the underlying notion of autonomy, and second, it is not in accordance with the legal principles of the PDPA. Scholars have deliberated on different strategies of informed consent, and a more interactive approach has recently been introduced: dynamic consent. It is argued that a dynamic consent approach would be able to address these concerns.

Keywords
Biobanking, Autonomy, Data protection, Informed consent, Dynamic consent

Abdul Aziz, Mohammad Firdaus, and Aimi Nadia Mohd Yusof. 2019. Can dynamic consent facilitate the protection of biomedical big data in biobanking in Malaysia? Asian Bioethics Review 11 (2) 1-14.  https://doi.org/10.1007/s41649-019-00086-2.
Publisher: https://link.springer.com/article/10.1007%2Fs41649-019-00086-2

(US) Google and the University of Chicago Are Sued Over Data Sharing – New York Times (Daisuke Wakabayashi | June 2019)0

Posted by Admin in on October 17, 2019
 

SAN FRANCISCO — When the University of Chicago Medical Center announced a partnership to share patient data with Google in 2017, the alliance was promoted as a way to unlock information trapped in electronic health records and improve predictive analysis in medicine.

On Wednesday, the University of Chicago, the medical center and Google were sued in a potential class-action lawsuit accusing the hospital of sharing hundreds of thousands of patients’ records with the technology giant without stripping identifiable date stamps or doctor’s notes.

The suit, filed in United States District Court for the Northern District of Illinois, demonstrates the difficulties technology companies face in handling health data as they forge ahead into one of the most promising — and potentially lucrative — areas of artificial intelligence: diagnosing medical problems.

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Management of Data and Information in Research (NHMRC An Australian Code (2018) good practice guide | June 2019)0

Posted by Admin in on September 29, 2019
 

A guide supporting the Australian Code for the Responsible Conduct of Research

aContents

1. Introduction 1

2. Responsibilities of institutions 1
2.1 Provision of training for researchers 2
..2.2 Ownership, stewardship and control of research data and primary materials 2
2.3 Storage, retention and disposal 3
2.4 Safety, security and confidentiality 3
2.5 Access by interested parties 4
2.6 Facilities 4

3. Responsibilities of researchers 4
3.1 Retention and publication 6
3.2 Managing confidential and other sensitive information 7
3.3 Acknowledging the use of others’ data 7
3.4 Engagement with relevant training 7

4. Breaches of the Code 7

Additional Resources 8

Access the good practice guide

Why We Need Guidelines for Brain Scan Data – Wired (Evan D. Morris | September 2019)0

Posted by Admin in on September 18, 2019
 

Your brain is a lot like your DNA. It is, arguably, everything that makes you uniquely you. Some types of brain scans are a lot like DNA tests. They may reveal what diseases you have (Parkinson’s, certainly; depression-possibly), what happened in your past (drug abuse, probably; trauma, maybe), or even what your future may hold (Alzheimer’s, likely; response to treatment, hopefully). Many people are aware—and properly protective—of the vast stores of information contained in their DNA. When DNA samples were collected in New York without consent, some went to great lengths to have their DNA expunged from databases being amassed by the police.

Fewer people are aware of the similarly vast amounts of information in a brain scan, and even fewer are taking steps to protect it. My colleagues and I are scientists who use brain imaging (PET and fMRI) to study neuropsychiatric diseases. Based on our knowledge of the technologies we probably ought to be concerned. And yet, it is rare that we discuss the ethical implications of brain imaging. Nevertheless, by looking closely, we can observe parallel trends in science and science policy that are refining the quality of information that can be extracted from a brain scan, and expanding who will have access to it. There may be good and bad reasons to use a brain scan to make personalized predictions. Good or bad, wise or unwise, the research is already being conducted and the brain scans are piling up.

PET (Positron Emission Tomography) is commonly used, clinically, to identify sites of altered metabolism (e.g., tumors). In research, it can be used to identify molecular targets for treatment. A recent PET study of brain metabolism in patients with mild cognitive impairment predicted who would develop Alzheimer’s disease. In our work at Yale, we have used PET images of a medication that targets an opioid receptor to predict which problem drinkers would reduce their drinking while on the medication.

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