But today we'll be talking about blockchain and how blockchain can be usefully applied in the context of consent.
Consent. It can be useful both in clinical trials when consent needs to be recorded,
but also and that's what I'll be talking about primarily for managing consent mechanisms for
pre-existing for epidemiology or data driven research that relies on on data that already exists.
So by the turn of the 20th century, the introduction of scientific techniques into medical research was increasing
demands for subjects to study with new knowledge came new hypotheses to be tested,
but subjects were often hard to come by. Therefore, it was tempting for medical researchers to use the resources they had at hand,
namely patients in the hospital that were admitted for other reasons.
From time to time, these patients would suffer some kind of injury from these experiments,
and quite often they would have no clue that these additional procedures were being performed on them,
not for their own benefit, as it were, but as part of an experiment.
And as a result of that public debate concerning the ethics of such research intermittently flared up in the media and in political fora.
In 1898, for example, this man, Albert Nasser, published a series of trials concerning serum therapy in syphilitic patients.
Nasser had attempted to produce a vaccine against the disease.
But to test it out, he went searching for syphilis, free prostitutes at his university hospital, D.C., injected with cell free serum.
And when some of them later went on to contract syphilis, he concluded that his vaccination was ineffective.
Moreover, he argued that they had contracted syphilis because they were prostitutes and not because he had injected them with it.
To local and national media. This is presser and we quickly picked up the story.
And later in the same year, Professor Nisar was fined by the Royal Disciplinary Court for his failure to
obtain consent from his subjects and not notably for the harm he had done.
The next year, 1899, the case prompted the relevant press and minister to commission a report from the Scientific Medical Office of Health,
which included a number of August German researchers as foreman and Vienna, who detailed the story and how they recommended the BMJ article noted.
The Commission focussed explicitly on two important factors when it came to medical the ethical assessment of medical experimentation on humans.
The first was beneficence and the second was autonomy.
They concluded that both informing the patient and getting their consent were both prerequisites for ethical medical experimentation.
These rules were later formalised first in a 1931 pressing government directive, and then, more famously at noon back.
And here we can see Blanche, who was the personal physician to Hitler being given his death sentence.
The prosecution focussed on the coercion rather than the harm that was involved as a primary criterion
for the unethical status of the Nazi doctors experiments during the war over the subsequent decades,
and notably in the sixties and seventies. Laws and policies introduced informed consent requirements for most human subjects.
Research in most places that such research was carried out. By the turn of the 21st century,
the introduction of information and computing technologies into medical research
was causing an increase in both the supply and demand of biomedical research data.
But concerns about consent were by now taking a different turn. For example, in 2003,
the results of a survey conducted by the Association of American Medical Colleges found that consent regulations in
the form of the US Privacy Rule had won reduced patient recruitment to increase the likelihood of selection bias.
Three Increase the cost of conducting research by requiring more paperwork, yadda yadda.
Four Increase the number of errors in research. Or de-identified information was being used.
And five made multi-site trials more difficult because of variations in local IAB review.
And finally, Six had caused researchers to abandon projects entirely because of an increased number of rules for operating a research study.
The survey, along with many others other sources of evidence,
is quoted approvingly by the U.S. National Academies Institute of Medicine Report 29, which you can see here.
By this time, it was becoming increasingly clear that rules made to protect prostitutes from random syringes and any
human against medical war crimes might not be necessarily appropriate for all other kinds of research.
In particular, these rules are not tailored to nor flexible towards research based on pre-existing data.
For example, in electronic health records and other medical databases.
With the exception of the Nordic countries,
which have allowed registry based research for health data and many other kinds of data since the sixties, largely for economic competitive reasons,
countries around the world have largely failed to update their consent legislation to accommodate the changes over the last 50 years,
particularly failed to accommodate data driven medical research.
This is a problem because these rules were made to protect human subjects in the flesh,
and they did not foresee the very different issues involved when it comes to the use of people's data.
Although asking people for consent to use their medical data respects their autonomy in much the same way as asking for consent before interventions.
The potential for harm. And thus the stakes are radically different.
Smaller. At the same time, the potential for beneficence,
the for the use of these medical data to lead to a generally better world for everyone has increased appreciably.
So why would anyone argue against consent requirements beyond being enshrined in various codes and laws?
Consent requirements make intuitive sense.
If you're going to expose someone to potential harm for the benefit of others, then you better make sure that they're game for it.
But there are good reasons. One major reason is the difficulty in obtaining consent from individuals in a registry or database setting database study.
For example, many individuals in our registry might be deceased or they might have changed address making them difficult to contact,
or they may miss or ignore or simply not care about letters, phone calls, emails, and other requests for consent.
In one extreme case mentioned in the Institute of Medicine report,
it quoted earlier registration to the Hamburg cancer registry fell by 70% after consent requirements were introduced,
after which use of the registry had to be discontinued. Although this percentage is going to differ widely in various cases,
it is clear that consent requirements sometimes lead to reduced subject recruitment, just as the Institute of Medicine said.
This in turn, leads to economic costs and delay in the conduct of research,
which translates into ailments not ameliorated and at the extremity labs not safe.
More significant still, is the impact that these consent requirements have on the quality of medical research that is conducted.
We cannot generalise the results of the study if the underlying population is not representative.
For example, if it is carried out only on young or elderly people.
Similarly, research using volunteer data will yield results that are not valid for non
volunteers because volunteers and non-violence use differ in important respects.
One meta analysis on this topic, which is called Selection Bias, looked at nine variables known to affect responses to treatment.
All nine of these variables differed significantly between considers and none considers.
The extent of the bias varied in each case to.
Worse, none of these biases could be mathematically corrected.
Thus wherever consent is required, this is a statistically irremediable bias of unknown magnitude and significance automatically appears.
There are also more fundamental problems for consent requirements as judicially conceived.
In order to be legitimate,
the person consenting must understand and assess the most relevant risks and benefits likely to be involved in the specific research study.
This is difficult to do in 1899. Nowadays, few comprehend the details behind a biomedical study outside their speciality.
The researchers conducting the study may themselves not even know all the relevant risks or benefits involved.
Consent is also supposed to be specific to a singular instance.
Yet with changes in computing and information technology, the same person's data may be queried hundreds and hundreds or thousands of times each year.
We really study the minutiae of the protocol each time it is tweaked.
And do we even have the time and motivation to do so if we want it?
For example. McDonald and Crane were found in 2008 that simply reading never mind understanding
the privacy policies that an average American was likely exposed to online.
In a year it would have taken 76 working days. This is simply not a scalable option as the complexity and volume of research continues to increase.
In 2016, Julian said. The rescue by Sahakian and I argued that a duty of easy rescue applies to medical
data contribution because contributing data does not involve significant risks,
costs or effort. It has large potentially life saving benefits and refraining from from sharing
seriously hinders the provision of these benefits to individuals and groups.
There are no other ways to get there. This concept of minimal risk is important for the discussion I want to have today,
because we believe that it might be possible to reduce the risk of most,
if not all, records based research to a minimum using advances in computing and encryption.
Notably a set of technologies known as blockchain and secure multiparty computing.
So what is a blockchain? A blockchain is essentially a better way to record transactions.
We might say that a transaction occurs when X gives A receives Y from Z.
Here X and Z could be one or more entities of any kind, say one or more humans or computers.
And why is the thing that is transacted could be data or items of any kind and description and quantity.
To illustrate the first application of blockchain technologies with the Bitcoin currency.
And this concerns monetary transactions, mostly between individuals.
So in this case, X and Z are individuals or groups of humans or perhaps even institutions.
And they are involved in a mutual transaction transaction of WHI, which is some quantity of fiscal value here represented in the Bitcoin currency.
As you might imagine by analogy to fiat money, to normal money,
many such transactions take place during any given window of time to make things more manageable.
These transactions can be grouped together periodically and aggregated into chunks or blocks of transaction data indexed by time.
The Bitcoin transaction data in block one precedes the transaction data in block two
and the two blocks are chained together by their sequential release and in time.
Each block carries a timestamp and a hash of the previous block.
Now, a hash is essentially a mathematical function where you give it a certain input and it will come out with a certain output.
But if you change the input in any way, the output would be radically different.
So for example, if you have downloaded illegal materials like a movie and you want to check whether there is a virus in it,
you could go online and find out what data stream of actual movie should has to hash
the file that you have downloaded and see whether it comes out with the same value.
If not, then it's been messed with. It's also used in many other things.
The database, which stores this information is not kept at headquarters,
but crucially it is distributed amongst hundreds of thousands of nodes and, uh, server nodes.
So node is a computer or any computing device.
In fact, anyone who has a reasonably young computer or a reasonably new smartphone can download
and store this database and run it in its entirety since its since inception.
This has a number of important consequences.
For one, the structure makes the blockchain resilient against attacks because the record is distributed amongst hundreds of thousands of nodes.
You get one. You need to get the others for a new block to be added to the chain.
A majority of these servers are nodes. Have to agree on the contents.
Thus the computer which proposed a block in which there was a transaction giving user x say access to the funds or information of prison
officers and said this will achieve nothing unless at least 50% of the other computers are persuaded or verify that this is indeed the case.
Similarly, if someone attempts to change the previous block, this will cause that block and all subsequent blocks to change their hash values.
And this is a clear signal that someone has tried to tamper with your record.
The system is also set up in such a way that hacking or controlling that many computers
would cost more in electricity consumption than the resulting outcome would be worse,
even if it were possible to do a hostile takeover thanks to something known as the proof of work protocol.
Um. This is what is meant when people say that blockchains are tamper proof.
Moreover, each entity in a blockchain transaction is represented by a cryptographic identifier.
And it is can choose whether to exchange that identifier for each transaction, thus maximising their level of pseudo anonymity.
Or they could choose to use the same identifier repeatedly, thus opting for less pseudo anonymity.
To access the money data. Information that is stored or associated with an identifier requires a corresponding password known as a private key.
In addition to the public key, which from which the identifier can be generated.
The details here are not important.
Using a private key, an individual can create a unique digital signature for any message or transaction, thus verifying their identity.
No one else could do so. Anyone who possesses a corresponding public key can use that key to verify that that
message did indeed come from the person represented by the private key signature.
Both of these keys are created through an iterated one way,
hashing out a rhythm which makes it impossibly difficult to guess or reverse engineer the private key.
Knowing only the public key or any other information except for the private key.
Thus, even if the blockchain were to be compromised by a malicious actor with more than 50% stake of service under their belt,
they would not be able to figure out who all these people are.
Indeed, the hope Bitcoin blockchain is transparent because of this feature.
Anyone can see the entirety of history of transactions who sent how much to whom?
When? Because no one knows who that is. And the stats are.
Unless they want to be known. So that is the blockchain in a nutshell.
It's, of course, a lot more complicated than that. And there are lots of variations and numerous modifications.
For example, it is possible to add code to a blockchain or layer on top of the blockchain, which can trigger further events to happen.
If certain criteria, predefined criteria are met.
Such pieces of code are known as smart contracts and they can be used to automatically fulfil transactions or carry out calculations.
Once these predefined criteria have been met. So a classic example. I want Doug to give me a house.
Dog wants to get money for the house, but he's not sure I won't run off.
So we create a smart contract that says once the criterion of house built is fulfilled, the money will automatically leave my account and go to dog.
Crucial thing, though, about all this is that the blockchain can record any type of data, not just Bitcoin, finance, whatever.
It could just as easily store access keys to electronic health records or record the sequential steps in a clinical trial protocol.
Or even buy a smart contract, automate child data release and integrate such child data into near real time meta analysis.
And it can do this safely, quickly, transparently, efficiently, with effectively zero chance of privacy breach,
effectively zero cost, and no chance at all of transaction falsification.
For example, the Enigma Project uses blockchain technologies to manage access to data which are themselves stored in a location not on the blockchain.
Data are encrypted upon collection,
using an encryption key that is shared between the data owners and the data requires only a hash of this original data is kept on chain.
Computations can then be performed on small chunks of still encrypted data distributed throughout the Enigma
Network so that no one at any point can tell either the pseudo identity of the data owners or acquirers,
nor the data itself. This data can then be queried by subject and investigator in aggregated form,
with statistics performed whose identities are in turn verified by the encryption keys.
In another example, Nebula Genomics.
A person wishing to access data since a request by a blockchain transaction to relevant nodes in the network once authenticated,
the subset of data relevant to the researchers study is then sent automatically via a smart contract to a data enclave,
at which point it is de-identified to the highest level of abstraction compatible with research aims and aggregated before being made available.
Of course, there are many other models and potential ways to do this.
In addition, the blockchain enables novel interactions between all kinds of stakeholders in the health care environment.
Whereas your research. Whereas previously a doctor would ask an individual for consent to take observations or to share data.
It is possible through the blockchain for that or any other individual to request data or
otherwise interact with the researcher the other way around at any level of anonymity.
Pseudo anonymity. This feature, which we termed Frozen, opens up a veritable cornucopia for health data sharing.
On one level, it could be envisaged as a data marketplace in which patients with rare genomes can sell
their genetic data to pharmaceutical companies or university researchers at high prices.
At another it kipping considered a marketplace of ideas in which patients with rare disorders could seek out one another.
We'll offer researchers incentives to study their conditions, which are otherwise not being offered.
Similarly, the government or any government or really any institutional or individual or computer could in theory become involved
with any research project through this present mechanism without anybody necessarily knowing who the other person is,
except that they are who they claim to be. So for example, I claim to be a medical researcher.
You can verify that, but you will not find out. My name is so.
But here again, there are critical questions.
What kinds of data should be up for sale and which should only be allowed to be donated and which shouldn't even be allowed to be done?
Should there be restrictions on what kind of data people can buy without a background in health research?
What criteria would qualify one as a researcher allowed to access some types of sensitive data through this mechanism?
Which criteria would disqualify an individual or organisation from donating or acquiring or buying or selling data?
So blockchain is definitely something I think that we should be thinking about when it comes to the use of health data.
The interesting question is not whether but how we should implement it.
One attractive proposal is to give each individual access to their own health data.
The health data would be stored somewhere secure and in the cloud of a physical location, and the key to access it would be stored on a blockchain.
This key could then be given by its possessor to their physician or really any of anybody else that they would allow access to,
that they would like to have access to their records. All kinds of access management would be possible here in theory.
There could be keys to the whole record. Accused to part of the record. Single use, multi-use keys, you name it.
Using an API and application programming interface designed for ease of use.
Data owners could grant, modify or revoke permissions to access data by means of a near instantaneous transaction on the blockchain.
In doing so, they still retain access to their own data. But gain greater flexibility in determining who else may use it.
For example, some data owners may wish to grant permission for data access only to qualified researchers.
We're only two researchers working on publicly funded projects or from public institutions.
They may also like in the Nebula model briefly discussed earlier make their data available to
those willing to purchase it or to a combination of these modalities or really any other.
Alternatively, they may make their data completely open for anyone to see, like their research and his Open Humans Project.
Personal Genome Project. Or they can keep exes entirely restricted to themselves, not even letting their doctor see.
Importantly, this would allow people to treat different kinds of data differently.
Medical data, for example, access to sensitive medical data, which may concern issues such as reproductive choices,
mental health history, substance use services and so on, might be kept entirely private, but granted only to highly select entities.
Other types of medical data, such as flu status or height, could be put up for sale for donation to anyone that wishes to use.
And this way the blockchain would provide a practical means of implementing the notion of matter concerns introduced by some sometime in 2016.
The individual would have maximum control in this case over their health data.
The ethical principle of autonomy would correspondingly be maximised.
Alternatively, however, one could imagine other ways of arranging access control.
For example, some information on a person's health record might simply not be that sensitive.
That type of information could be grouped together, and then access key to non-sensitive information might be made automatically available
to anybody who fulfils certain criteria and qualifications as a researcher.
Or I might go one step further and give qualified researchers access privileges to all health data relevant to their study.
Of course, the form of this data would reach. The researchers then would be aggregated de-identified with all the statistics already done correctly.
So did the smart contract. Thus, no individual identifiable information would be made available to any human eye.
Or really to any computer either because it's encrypted. When they perform a calculation that the difference such a system could make
to the efficacy and efficiency of biomedical research is hard to overstate.
So there are these options. And the question is, how should we choose between them?
Well, the question is which one should we choose, but also what kinds of reasons or thoughts?
How should we be deciding this? We should be deciding. One one way.
Is my favourite bioethical analysis. So the easy rescue that I introduced earlier, strongly motivated towards some kind of mandated data sharing.
If the blockchain could make privacy breaches and hacks pretty much impossible,
then it seems to me that there are no or only minimal risks involved in my data being used for medical research on encrypted data.
Encrypted data. And if I did it. And because of this, it seems to me that we should that I said that we should, everybody should.
And furthermore, that it would not be wrong to require people to do so passively if there are no burdens to them.
So that's my personal view. I lean towards beneficence.
And in this in this case, just regarding people's autonomy so as to increase justice and for the greater good,
seems like a good weighing up of the principles.
But of course, reasonable people disagree, and I would love to talk to anybody that does.
Another way to approach these issues is through public engagement.
The Danish Board of Technology, for example, has done excellent work on contentious scientific issues,
such as genetically modified genetic modification of various types of stem cell research.
In one of their models.
They ask citizen volunteers to meet every weekend for some months, and then they are given scientific lectures and homework by both pro and con.
And in the final by the final weekend, they have a deadline and they produce a report.
And this report is then considered to be the considered judgement of the Danish people.
Of course, there are many other ways to do public engagements,
but some public engagements should be absolutely or would be absolutely necessary
to achieve legitimacy for any change in the way that we handle people's data.
Just think about what happens with health data.
Although public engagement is fascinating, my colleagues and I are currently interested in a very different third way,
namely the human right to enjoy the benefits of the progress of science and its applications.
This human rights is much neglected, but it has the same legal status as all the other economic,
social and cultural rights enshrined in the Autonomous International Covenant.
This means that just like governments are required to respect, say, the right to health or free assembly,
so they must also respect the right to enjoy the benefits of scientific progress and its applications.
The right to science is highly underdeveloped, but international human rights law,
which is used to interpret other human rights obligations, is equally applicable to it.
Thus, we can argue by analogy, for example, to the right to health. The governments must ensure that as many individuals as possible benefit as
much as possible from the advances that are made in science and technology,
as long as any policies to that effect are also human rights compliance.
One such argument could be quite simple to make.
Since improved medical research constitutes a benefit of the progress of science and has applications.
The starting point from a human rights perspective is that everyone should benefit, where possible, from improved medical research.
Like other human rights, though, this rights is not absolute.
It may be outweighed by other rights or concerns or the underlying principles in human rights.
However, any such limitations must be appropriate.
They must be proportionate, and they must be strictly necessary for the general well-being in a democratic society.
Otherwise they are unlawful. We discuss this further for those that are interested in the articles shown here.
So the Right to Science Framework thus provides us, I think,
with an approach to the question of consent in medical research that also has some legal weight added to it.
Roughly, we could argue from a right to science perspective that blockchain be used to facilitate
medical research to the extent that this is necessary for the general well-being,
which I believe it is, but only as long as this is consistent with other human rights and is appropriate and is proportionate.
We might then discuss whether some kinds of mandates as automatic data processing are appropriate and appropriate, for example,
where someone does not wish on religious or normative grounds that their data be used for research into abortion or blood transfusions.
We might also wonder whether the full removal of autonomy from consideration is proportionate.
For example, by observing that some low level of selection bias is acceptable.
After all, we have high levels right now. As well as noting that where the feasibility and scientific merit of a proposed data usage is low,
concerns about autonomy become correspondingly weightier.
This is exciting work for me because of all the possibilities that are novel and powerful and for the same reasons.
It is important that we ponder and discuss them, which I propose we do now or shortly after.
I thank the teams involved. This is the blockchain team.
And this human rights. The Science group which originated.
That's Harvard Medical School Centre for Bioethics. And it's still going strong.
So thank you.