Blockchain technology: driving change in the scientific research workflow

Step #1: develop hypothesis/define idea

The chief application for this step is the timestamping of an idea or hypothesis once it is posted on a blockchain via a hashtag. This was the first application of blockchain and the force behind Haber and Stornetta’s blockchain technology development to certify when a document was created or last modified so that conflicts over things such as intellectual property rights could be more easily resolved.

Since timestamping was the first blockchain application, it is logical that there are several organizations who offer such a service. In alphabetical order, here is a sampling of the organizations who are active in this space as of this writing:

Step #2: seek funding (if needed)

Ironically, since blockchain technology in more recent years has risen in prominence because of Bitcoin and cryptocurrency, it is not widely used as a funding mechanism for scientific research…. yet. There were some initial players that emerged in 2017–2018, for example Scienceroot, ⁵⁶ KnowbellaTech, ArnoGenomics, etc., but they seem to have either disappeared or have changed their business objectives. That said, there are a few examples of companies with funding platforms (the DEIP, Matryx, and Molecule approaches are outlined below). An even stronger example of the use of blockchain technology to manage the federal funding/grant processes efficiently and cost-effectively is described in Section “Project: Grant-recipient Digital Dossier (GDD)” on the U.S. Health and Human Services Grant-recipient Digital Dossier project, GDD.

Step #3: perform the experiment/make observations

It is in this area of the scientific research workflow that the inherent features of blockchain technology are invaluable. Consider what information can be captured in this step and how posting it to a blockchain can make research transparent and reproducible.

Who did the experiment? The digital identity and signature of the researcher(s) can be hashed to a blockchain while maintaining the privacy of the individual(s) involved. In addition, the expertise credentials of the experimenters can be hashed as there are organizations who now use blockchain for the creation of micro-credentials ⁷¹ (more about this later in Section “Uses of Blockchain in Higher Education”). As a related, real-life example, Hashed Health ⁷² and other such organizations were used to ensure that the doctors/nurses who moved from one geographic location to another during the peak of the Covid-19 pandemic had the necessary experience and expertise.

When was the experiment performed? As already discussed, blockchain timestamping is a key feature of the technology – it was the reason for which it was originally developed by Haber and Stornetta, and it plays an essential role in protecting a researcher’s Intellectual Property.

What materials/methodologies were used? Details on the exact reagents/animals/people and methods that were used can be compiled and linked via a hash posted to a blockchain to ensure that the provenance is captured. This is a step that facilitates the reproducibility and transparency of scientific research because the information becomes immutable.

What equipment was used? Details on the manufacturer, when the equipment was obtained, its maintenance, prior uses and users, the location of the experiment, etc. can be hashed to a blockchain. Going back to the micro-credentials mentioned above, details on the training/expertise of those using the equipment can also be added to provide a level of confidence in the results that are reported. This use has become important in the healthcare industry and for more information there is an interesting article published in late 2020 that details the adoption of blockchain technology in healthcare. ⁷³

What data was gathered? The raw data gathered during the experiment is a digital asset that can be stored, shared, verified, etc. and this is a common use of blockchain technology. Once the data is hashed to the chain any tampering would become immediately apparent, because the hash would be different. The immutability of a blockchain adds a layer of trust to the data. For more detail on the storage of “data” on a blockchain – whether that data is a hash of a file or the data itself – see Sections “Blockchain Technology and Intellectual Property and Data Management on Blockchains”.

What are the results of the experiment? The results are an outcome of an analysis of the raw data. Again, the methodology can be detailed and posted to a blockchain. Key information may be any software that is used, specific calculations, who did the analysis, where and when the analysis was done, etc.

As of this writing there are several organizations who offer services in support of the experimental phase of the scientific workflow. Among these are:

ARTiFACTS: Already discussed within the context of time-stamping ideas and hypotheses.

Bloxberg Consortium: Already discussed within the context of time-stamping ideas and hypotheses.

Matryx: Already discussed within the context of crowdsourcing of research funding.

Step #4: perform analysis/make insights

The next step in the scientific workflow process involves taking the results from the experiment performed in Step #3 and performing one or more calculations, analyses, and visualizations on that data to generate conclusions, make insights, and to guide the next stage of the experimental discovery cycle.

In many respects “perform analysis” is like the “perform experiment” in Step #3, except that the analysis experiment is performed without tangible or physical materials or equipment – unless one calls pen and paper, or a PC, equipment! For the purposes of this article, we have assumed that “perform analysis” means executing in silico (i.e., using a PC and analytical software) an operation or an algorithm on experimental data that is generated in vitro or in vivo. In other words, Step #4 takes the data generated in Step #3 and uses computational processes to generate more results, again in the form of data, which supports, or not, the experimenters’ initial hypothesis. In the Step #4 in silico experiment, we have to all intents and purposes, the same “actors and artefacts” as we had in Step #3, namely: (i) the person who ran the analysis (the “who”); (ii) the methods that they used (the “how”), which in this case comprises the software, algorithms, and mathematics that they used; and (iii) the results, observations, and conclusions that they generated. And just as in step #3, there are tools to help these in silico experimenters or “informaticians,” to capture and manage the metadata around the experiments that they run. Perhaps the most widely-used of these informatician tools is the Jupyter notebook. ⁷⁹ The Jupyter notebook is an “open-source web application that can be used to create and share documents that contain live code, equations, visualizations, and text”. ⁸⁰ While it does not have blockchain technology embedded within it, a Jupyter notebook can quite easily be connected to, for example, an Ethereum node to deploy a smart contract. ⁸¹ Note also that there is a new Electronic Laboratory Notebook (ELN), Labii, ⁸² that uses blockchain to secure research data. In addition, in 2021, the National Institute of Standards and Technology (NIST) funded a research project for the development of a prototype Digital Research Notebook system called KnowLedger. The concept for this new ELN is to build a system where research data is captured semantically immediately at birth and stored on a blockchain, and updated incrementally as knowledge is added. This initiative is the brainchild of one of the authors of this blockchain white paper, Dr. Stuart Chalk (see Appendix A for more details).

But why might one want to involve blockchain technology in in silico analysis? Because the technology’s main value rests in its transparency, immutability and auditability, disintermediation, and trust enablement. If the data that result from a physical or in silico experiment have, by some mechanism, been registered or captured on a blockchain (e.g. by storing a hash of a data file), then whoever takes that data file and performs an analysis on it can have a higher degree of confidence that the results they generate can be traced back, or audited, to an immutable, time-stamped dataset (as fixed by the hash). In other words, if the informatician, whose role is now increasingly being called “data scientist,” also captures their results and methods on a blockchain, they can now demonstrate a clear line of sight (akin to a data family tree ⁸³ ) back to a starting dataset. This trusted auditability and integrity enabled by blockchain technology is being viewed increasingly as a compelling use case by data scientists, ^{84 , 85} so much so that some commentators are now saying that “data science and blockchain are made for each other”. ⁸⁶

Putting this axiom aside for now, it is perhaps more important to recognize where blockchain-enabled data analysis can have genuine real-life benefits and utility. In our view, wherever the conclusions and resultant actions from an experiment need to be unequivocally and irrefutably linked to a dataset which resulted from that experiment, then blockchain technology can play a significant, value-adding role. One primary example would be in the GxP (Good Laboratory/Manufacturing/Clinical Practice) area of drug discovery (for more on GxP see Section “Blockchain Technology and GxP: Enabling Adherence to Regulations” that covers legal and regulatory considerations). In this highly-regulated domain, the effective and immutable capturing of experimental data, the analyses that are performed on that data, who performed those experiments and where, and the ultimate conclusions on that data, all of which together may decide whether a drug is suitable (safe and effective) for human consumption, could be made more reliable, more secure, and more transparent if those data and metadata were captured on a blockchain. Currently, if such data lineage is being captured using DLT we, the authors, are not aware of it. But if data analysis, data science, and blockchain technology are truly “made for each other,” the GxP domain could be one area where that statement is proven correct.

Step #5: publish/share results

Steps one, three, and four create the content that can be shared on a blockchain if desired, and/or submitted for publication to be made available to the global scientific community. There are several diverse players in this space that offer publishing/sharing services via blockchain, some of whom could potentially disrupt the traditional publishing process because of the value that blockchain brings to the table. Current challenges ^{87 , 88} in the overall publishing/science communication process are as follows:

1. Academia has a “publish or perish” mindset and researchers choose to publish in the top journals for a variety of purposes including tenure (commonly in what are known as “High Impact Factor” journals). As a result, a handful of publishers control most research outputs.

2. Access to research findings can be difficult because of the journal subscription model. Access depends on a university’s library budget. Access by the public is even more difficult.

3. Research only becomes accessible at the point of publication. Everything that takes place prior to that point – such as collecting and analyzing data, peer review, etc. – is not transparent, leading to reproducibility problems.

4. With peer review – the process whereby research papers are evaluated by peers in the same field before a paper is published in a journal – there is lack of visibility, as well as recognition and accountability recognition for reviewers, with their review work remaining largely unnoticed and unrewarded.

5. Scientific results are primarily published in academic journals, which have a strong tendency to publish positive and novel results. Scientists themselves are more inclined to report on their successful outcomes rather than on failed experiments. A lot of research that did not lead to positive results, therefore, remains unpublished and unknown – possibly leading to more time, effort, and funding being spent on similar efforts.

6. Publication cycles can be lengthy.

7. Scientific “misbehavior” such as plagiarism, tampering with research results, etc., unfortunately does happen.

While there is no technological solution to the first two challenges noted above, blockchain technology can help to deal with the others. Players in this step of the scientific research workflow who are using blockchain technology for publishing are aware that the technology promotes transparency, fosters speedy communication, mitigates data tampering and fraud, and can offer rewards (tokens) for usually unrecognized efforts such as peer review. As of this writing the following is a representative sample of the players in this step (in alphabetical order):

Medical/pharma supply chain

There are several good examples in this area. For example, the U.S. Federal and Drug Administration (FDA) is running a pilot program to help the pharmaceutical industry move toward meeting the 2023 requirements of the Drug Supply Chain Security Act (DSCSA) which requires that the U.S. pharmaceutical industry be able to track legal changes of ownership of pharmaceuticals in the supply chain. The MediLedger Pilot Project, a consortium of leaders from 25 pharmaceutical companies, was accepted into the program with the goal of evaluating blockchain as the solution to the 2023 DSCSA requirements. The pilot is now complete and the resultant solution is now available. ¹¹⁸

The FDA has also joined forces with the Good Shepherd Pharmacy and RemediChain, two non-profits with the mission of getting unused but still valid drugs into the hands of people who cannot afford them. ¹¹⁹ This is most useful with high-priced chemotherapy drugs where 40 % of the patients die before the drugs that they are using expire. Such drugs in the USA can cost upwards of 30 thousand dollars a month. Both non-profits are small organizations`, but despite their modest beginnings`, both use blockchain technology which works well for heavily regulated industries such as pharmaceuticals to track “medicine transfers” in the drug supply chain. At Good Shepherd Pharmacy, medicine transfers take place when, for example, the family of a deceased cancer patient donates unused medication to the organization. RemediChain then matches those donated medicines with the most appropriate patients in multiple U.S. states. RemediChain, also handles donations from a variety of sources, including individuals and cancer clinics, taps back into the supply chain data and re-creates any missing information, such as manufacturing and expiration dates. The re-creation of the “chain-of-custody” via blockchain technology assures a medication’s origin and quality. According to the FDA, “The program is intended to assist drug supply chain stakeholders in developing the electronic, interoperable system that will identify and trace certain prescription drugs as they are distributed within the United States”. ¹¹⁹

A more recent example is the partnership between the Distributed Pharmaceutical Analysis Lab (DPAL) at the University of Notre Dame and ARTiFACTS (an organization mentioned throughout this paper) to develop a prototype solution for tracking pharmaceutical chain-of-custody information in real-time using ARTiFACTS’ blockchain platform. The partnership was announced on October 20, 2021, and the press release states that “up to two billion people worldwide lack access to authenticated medicines. The World Health Organization has estimated one in 10 medical products in low- and middle-income countries are substandard or falsified, with some experts estimating monetary losses of between US$70B and US$200B. More troubling is the human cost – two hundred thousand lives are lost per year in Africa because of fake antimalarial drugs alone”. ¹²⁰ Today’s efforts to reduce fraud are manual, time-consuming, lack transparency, and have no chain-of-custody. This partnership aims to: 1) make all relevant information directly available online for researchers and regulatory authorities; 2) create a trusted and secure chain-of-custody of drug samples and their metadata; and 3) scale-up across the DPAL participant community. This partnership was mentioned in Section “ARTiFACTS” of this paper where ARTiFACTS was first highlighted under step #1 of the scientific research workflow.

One of the more visible healthcare projects is PharmaLedger, ¹²¹ a three-year project involving 12 global pharmaceutical companies and 17 public and private entities including technical, legal, academic, regulatory, and research organizations as well as patient representative organizations. The project was sponsored by the Innovative Medicines Initiative (IMI) and the European Federation of Pharmaceutical Industries and Associations (EFPIA) under the Horizon 2020 program (now Horizon Europe ¹²² ) and had the goal of building a scalable blockchain infrastructure that will support supply chain, clinical trial, and health data use cases. The initial project ended in December 2022 and the project wrap-up has been published. The work continues through the not-for-profit PharmaLedger Association founded in March 2022. ¹²¹ Note that PharmaLedger released its first product, electronic Product Information (ePI) in April 2023. ¹²³

Clinical trials

Another project worth noting is the Pistoia Alliance’s Informed Consent project, which sought to demonstrate the value of blockchain technology as part of a decentralized digital identity solution for the informed consent process that is essential for pharmaceutical clinical trials. ¹²⁴ The two companies involved were AstraZeneca and Novartis. Richard Norman, the Project Manager at the time of our interview, described the traditional informed consent process as follows: an informed consent form (ICF) template is created by the pharmaceutical company and sent to the Ethics Committee for approval. Once approved, the ICF template is returned to the pharmaceutical company, and this is sent to the clinic where individual ICFs are created for each clinical trial participant. The participant is informed of the clinical study and is asked to sign the ICF which then goes to the Principal Investigator (or other authorized person) for countersigning. Once this is done, the individual ICF is returned to the pharmaceutical company for safe storage. He noted that although the high-level look of the informed consent process is quite generic, when you dig down there are variables that make the process quite complex, e.g., the ICFs vary between countries and studies; participants need to be informed and re-consented using an updated and approved version of the ICF following any change to the clinical study protocol; and consent can be withdrawn at any time. It is a manual process, and it takes a lot of time. He added that the process can be digitized, but despite many benefits, eConsent platforms are centralized and this can raise questions around the privacy and handling of participant personal information during and after a clinical study.

The conceptual solution developed through the Pistoia Alliance Informed Consent project implemented key components of decentralized digital identities: Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and a blockchain registry, BlockSent, enabled participants to provide consent, be reconsented, and withdraw their consent to participate in a clinical trial. BlockSent provided multiple stakeholders – study sponsors, clinics, ethics committees and study participants – with an audit trail of all the transactions during the clinical trial informed consent process. It ensured regulatory compliance and enabled a real-time overview of the approvals and signature process. The project is listed on the Pistoia Alliance website as being completed in 2022 at which time the Pistoia Alliance announced that the organization has a new strategic theme – Empowering the Patient in R&D – and has called for its members to restructure around patient “centricity” based upon what they have learned during the pandemic. ¹²⁵ Richard Norman has since left the Pistoia Alliance and has said that if the project continues, most likely it will not continue in its present form. ¹²⁶ A brief summary of their efforts and their current outlook was published online in Drug Discovery World on February 20, 2024. ¹²⁷

For more information on this topic note that an article ¹²⁸ was recently published on the opportunities and challenges of using blockchain in clinical trials and it is an interesting read.

Medical device tracking

In the section on the scientific research workflow (Section “Blockchain Technology: A Brief History”), it was noted that use of blockchain technology is particularly valuable when doing an experiment because all the requisite information for replicating an experiment can be captured – including essential data on the equipment that is utilized. Similar information is essential in hospitals with regards to medical devices that are utilized for patient care. Sean Manion introduced us to a pilot project that was initiated in 2017 between Spiritus Development and Edinburgh Napier University in Scotland to demonstrate the benefits of blockchain technology in tracking medical equipment through their life cycles. ¹²⁹ The pilot use case was to track the unique device identifiers (UDIs) which are required from a regulatory standpoint for medical devices to improve their traceability.

We interviewed one of the pilot organizers, Susan Ramonat, who noted that medical facilities are concerned about the operating life of medical devices (and other equipment) as they move through the ecosystem from the manufacturer and their upstream suppliers, through distributors who may provide logistical services such as audit inspection. The equipment may ultimately be decommissioned and disposed of. But more often expensive and highly-valued assets, or those reconditioned or repaired, end up at auction and are distributed around the world to underdeveloped countries that have large populations and rely on secondary markets and auctions for their medical equipment. She said that there is a real challenge in bridging across such diverse parties to ensure that they not only know the chain of equipment custody, but also the service history associated with the device. This use case is not unlike the Vehicle Reports offered by CARFAX, ¹³⁰ a U.S.-based company that compiles the history of an automobile – so providing a portable history which accompanies an automobile showing the history of its routine maintenance and repair, whether it was involved in any accidents as well as in recalls, and what actions were taken. The organizers of the pilot saw an opportunity to have a similar shared registry for medical devices and equipment using blockchain. The blockchain ledger that they created provided traceable, verifiable, and tamper-evident records across an asset’s entire lifecycle. It is a shared registry among all parties involved with shared control and governance and includes both physical and digital assets. It facilitates not only tracking, but also ensures that the right level of skills to use the equipment is made known and that all adverse results are noted. The pilot was successful and when we last spoke to Ramonat, the company that emerged from the pilot, Spiritus Partners, ¹³¹ had been working with U.S.-based hospitals for almost five years.

When we went to do a follow-up, we found that Ramonat had moved on and that the blockchain service that Spiritus offered appears to have been discontinued. Why? We do not know definitively, but she did say that the pandemic had slowed things down and had mentioned that one of the challenges that they faced was getting participants to share what she termed the de minimis amount of information – what needs to be shared to get the transparency and assurance required by all who are involved – a challenge/hurdle that exists for many, enterprise-related blockchain use cases, whether in healthcare or in the conventional corporate world. However, we do know that there is significant interest in such a service. For example, a group of hospitals in Switzerland used blockchain to track medical devices for the very reasons that Ramonat put forth. ¹³² Also, there is a company in the U.S., Culinda, that provides a medical device tracking service. ^{133 , 134}

A relatively recent article ¹³⁵ highlights the opportunities that blockchain technology brings to supply chain processes in healthcare such as medical device tracking and the delivery of pharmaceuticals from supplier to user. It describes the technology as potentially “transformative” for healthcare processes and is worth a read.

Degree/document/identity certification

There are several examples of the use of blockchain technology for the certification of scholastic degrees, documents, and even identity. Just as ARTiFACTS’ blockchain application allows researchers, authors, publishers, etc. to post and time-stamp their work, and the Pistoia Alliance’s blockchain platform was developed to certify the informed consent process in clinical trials, institutions of higher learning are using the technology to certify education credentials. In 2016 the MIT Media Lab, together with Learning Machine, came up with the idea of “blockcerts”. ¹³⁶ This allowed students to establish their own unique identity on a blockchain and when it was time to graduate, they could quickly and easily obtain a verifiable, tamper-proof version of their diploma that could be shared with employers, schools, family, and friends, giving them autonomy over their personal records. While MIT is no longer involved, Learning Machine was acquired in 2020 by Hyland ¹³⁷ who continue to steward the project and have extended its use beyond higher education to commercial applications, government agencies, and healthcare institutions.

In 2019, the Malaysian Ministry of Education introduced a blockchain platform, E-Skrol, to tackle the rampant use of fake educational certificates being issued by diploma mills. ¹³⁸ The platform makes it possible to verify the authenticity of Malaysian educational degrees and is available for all public and private universities in the country.

Another example is work being done by the Open University, the O.U., in the United Kingdom. ¹³⁹ The University was established by Royal Charter in 1969 with the objective of giving anyone, no matter where in the world they lived, an opportunity to learn, and it is a globally-recognized institution. In early 2021 we spoke with Dr. John Domingue, a professor, and the Director of their Knowledge Media Institute. At that time the O.U. had one hundred and seventy-five thousand students enrolled, making it (by student number) the largest university in the UK and one of the largest in the world.

John said that they became interested in blockchain in 2015 mainly for the purpose of accreditation, but they also have other use cases. Their goal is to empower their students, describing them as “self-sovereign students.” He went on to say that the O.U. wants its students to have control over their own individual learning process and that blockchain technology allows the university to facilitate that control. The idea is that students have their own personal data store, which the university configures to store a student’s accreditation data and then everything is verified on a blockchain. The institution that issues the accreditation signs a hash. He noted that the university utilizes “Solid” ¹⁴⁰ which is a personal data store technology. John added that the O.U. has several ongoing projects that are blockchain-based. One is QualiChain, ¹⁴¹ a collaborative effort that began in January 2019 to develop a decentralized platform for storing, sharing, and verifying education and employment qualifications. The project conducted pilots in four key areas: (i) lifelong learning; (ii) smart curriculum design; (iii) staffing the public sector; and (iv) providing recruitment and competency management services. It looked at the hiring process across Europe with the goal of adding another layer of transparency using blockchain technology. The project was given its final review in early 2022 and is considered to have been a complete success. ¹⁴² We highly recommend that you visit the QualiChain website to learn more. It includes a YouTube overview of the platform’s applications for researchers and educators. You might also consider looking at John Domingue’s explanation of blockchain technology as well as some of its uses in education along with a video on the Open University’s blockchain research. ¹⁴³

Identity certification

Like the “self-sovereign student” mentioned in the above paragraph where the student has control over their education-related certifications, self-sovereign identifiers (SSIs), also based upon blockchain technology, allow individuals and organizations to take control over their digital personal/organizational identities. ^{144 , 145} With an SSI, an individual or organization can control who can access their information, maintain their identities themselves, use it for verifying their identity online, etc. We are all used to physical IDs, credentials such as cards issued by a government, employer, university, etc. for verifying that the cardholder is a citizen, employee, or student of the organization. These tangible IDs have several issues associated with their production and use, but the biggest one now is that of ID theft and impersonation. Digital IDs are accessible currently by registering for a service with an email address or username and a password. Digital IDs also enable users to leverage third-party login services such as those offered by Facebook or Google. However, digital IDs also have issues, especially when the ID services are controlled and managed by the larger data-leveraging and technology companies. These issues include the fact that users do not have direct control over the sharing of their data and that they face risks due to the vulnerability of the centralized repositories of personal data on the issuer’s servers. Privacy is often at risk with third-party login services featuring financial incentives for data collection and storage. Self-sovereign identity involves setting up a highly secure, digital peer-to-peer network between ID issuer, ID verifier, and ID owner. Even the SSI system provider does not have any idea about the exchange of credentials. Therefore, the process of issuing credentials becomes faster, simpler, and a great deal more secure. The self-sovereign identity blockchain characteristics are evident with cryptographic hashing ensuring that SSI credentials are tamper-proof. Examples of SSI system providers are Evernym, who were acquired by Avast in 2021 ¹⁴⁶ and Spherity. ¹⁴⁷ The latter was involved in the Pistoia Alliance Informed Consent Project that was discussed in Section “Blockchain Technology Applications in Healthcare and the Pharmaceutical Industry”. Organisations such as the European Union (EU) have also put in place an SSI regulation called eIDAS to facilitate secure cross-border transactions, by establishing a framework for digital identity and authentication. It aims to create confidence in electronic interactions and promote seamless digital services in the EU. ¹⁴⁸

While we have included digital identity here in the section on higher education because the early use was education-related, note that blockchain-based digital identity can also be used along the scientific research workflow (see Section “Blockchain Applications Along the Scientific Research Workflow”, particularly steps #3 and #4), to capture the education, experience, and expertise of those doing the experimentation as well as the evaluation of results.

Blockchain for peer review

The Blockchain for Peer Review project led by Joris van Rossum, then at Digital Science, was officially launched in early 2018. The initial participants were Digital Science, Springer Nature, Katalysis, and ORCID. Soon to follow were Taylor & Francis, Cambridge University Press, Kargers, and the Wellcome Trust as an advisor. The goal of the project was to gather information about the peer review process and share it among the participating publishers. They believed that by creating a trusted data store of peer review data they could coordinate the review process, identify reviewers better, and create a trusted and independent data trail of the peer review process, making it more transparent and trustworthy. The process would then become more efficient, transparent, and recognizable (see the paper that van Rossum wrote after announcing the project at the NFAIS annual Conference in 2018 ⁸⁸ ). A year later they published a high-level view of the system’s architecture, ¹⁴⁹ but once the proof-of-concept was completed, the group had to decide about moving onto the next step. On September 5^th, 2019, they met in London to debate the issue and in November they announced that they “could do more in terms of collective action to improve the peer review process, but at the same time there is not one large, specific thing they should focus on” and the project was terminated.

We interviewed van Rossum about eight months after that announcement was made to get his view on what happened. He said that his original pitch to publishers regarding the initiative was that the peer review process is the main plus that publishers bring to the publishing process and peer review is under attack. Why continue to give their information (a key asset) to a commercial company, Publons, ¹⁵⁰ who may not exist down the road (it was founded in 2012 and purchased by Clarivate in 2017)? Why not build a decentralized system and eliminate the middleman who now has a stake in the publishing process? That pitch was repeated at the September meeting in 2019, but in the end the publishers chose to stay with Publons. Arguments for continuing the project did not provide sufficient pressure to raise the project higher in the publishers’ priorities in light of other factors which at that time had to be considered, such as: 1) the next step would require an investment, and publishers were concerned that Open Access, Plan S, ¹⁵¹ etc., might put a strain on their revenue stream; 2) the building of the infrastructure was in the hands of a small technology start-up (three people); 3) ultimately the project would need to find an organizational home or a non-profit organization would have to be established to oversee it; and 4) there was an existing alternative already being used by the publishers, Publons, which provided a system that can integrate seamlessly with a publisher’s peer review submission system to streamline the process of recognizing their reviewers. Interestingly, the fact that blockchain was a new, young technology that requires trust, but had been proven to work was not a major issue. In summary, a system that worked (albeit not blockchain-based) already existed and Clarivate is not a competitor to primary publishers. The peer review project was terminated, but not because the technology did not work – it did. In further support of these observations about the appropriate application of blockchain technology Sean Manion said during his interview that blockchain technology, when applied to a specific use case, may not be needed for that use case, so when it “fails” one has to ask if the failure was due to the technology or to human concerns, e.g., will the implementation risk an organization’s business model, is there a concern about sharing a platform with competitors, etc.? One must wonder in this specific case how much the last concern that Sean mentioned impacted the publishers’ decision.

Van Rossum added that if the Bloxberg Consortium discussed in Section “Bloxberg Consortium” had existed when his initiative started, he would have gone to them for the technology piece. They would have been a great player to interact with the large publishers who were involved with the project, and it would have allowed the publishers to engage with the consortium members in a new way. He does not view the project as a failure, but rather as a useful experiment from which others can learn. More importantly, the critical lesson to be learned out of all of this is that blockchain can play a major role if you do not have a trusted middleman already providing the required service unless there are other compelling reasons – time and cost reduction, increased revenue, improved service to stakeholders, etc.

Clinical support tools

The second example of where blockchain technology ended up not being a good fit was when Elsevier was looking to use blockchain for one of their clinical support tools. We found out about this because they gave a presentation on this particular use case and why it failed, and it was brought to our attention when we interviewed Sean Manion. He graciously put us in contact with the person who gave the presentation, James R. Sacra, who was, at the time of their foray into blockchain technology, a senior director in Elsevier’s Precision Medicine group within Clinical Solutions and he kindly agreed to be interviewed for this paper. In 2016 Elsevier bought a small company that had a clinical trial and design study product called “MACRO” – MACRO V4 to be specific, and at that time it was still very much in use, particularly in the UK. ¹⁵² His group was tasked to see if they could create a next-generation clinical study design and capture tool. Their goal was to find out how they could ensure the validity of data in a research process in the clinical space. Blockchain seemed to be a potential answer because it ensures that data cannot be overridden – an essential aspect of a clinical research study. So, they decided to learn more about the technology. One of the interesting aspects was trying to balance the real-time exchange of data and the process required to upload to a blockchain (e.g., waiting in a queue). They were concerned about how they could manage this in line with the user’s expectation of their product. Another issue was the cost of moving data onto a blockchain. Elsevier is a commercial organization and wants to cost-effectively create products that people need and will buy. However, they decided not to let cost limit them in the beginning. The time issue was more problematic, so they thought that they might just use blockchain as an audit history of the data rather than for the real-time exchange of data. This did limit what they were leveraging blockchain to create, but on the other hand, the technology certainly worked to ensure the validity of the data and that was one of the main issues that they were attempting to address. So, they decided to take the audit history goal for the use of blockchain.

They then discovered that there was another requirement for the product that was popping up in their market research. Customers did not just want to use Elsevier’s clinical trial tools for research design – they wanted to use them for clinical registry. Looking at this issue they ran into the laws around “the right to forget and the right to be forgotten” ¹⁵³ which vary from country-to-country (see Section “Blockchain Technology: Legal & Regulatory Considerations” on legal and regulatory considerations). They then tried to see how they could handle this by separating the components of the tool (public vs. private) and finally came to the realization that they were having to design around blockchain rather than with it. The particular use case for which they were designing was not a good fit for the technology at that time. They needed technology that would add value and expedite bringing the product to market and blockchain was not working so they walked away from it. When we spoke to Sacra he still strongly believed in the value of the technology, but noted that it must be the right solution for the task at hand, for example some of the use cases we have described earlier such as document management, intellectual property, real estate transactions, etc.

Lessons learned from consortia

1. Consortium usage of blockchain technology (i.e., a group of companies working together) is more effective than single-entity usage because the technology can automate the trust among the organizations that are collaborating, e.g., pharmaceutical companies, healthcare networks, etc., because they can share information without revealing everything (controlled sharing). However, consortium usage requires both technical development and governance as noted by the Bloxberg consortium. They said that 50 % of their work is technical development; the other 50 % is organizational – community maintenance, administrative, and legal. Governance can be challenging.

2. One of the main challenges for consortia is getting consortium members to share the de minimis amount of information – what needs to be shared to get the kind of transparency and assurance that all parties involved need at the end? This challenge/hurdle exists for many enterprise-related blockchain use cases, whether in healthcare or in the conventional corporate world.

3. The challenge for enterprise distributed ledger and blockchain implementations is getting that consortium of the willing to gather, to agree on the value of the benefits, and to start the journey of collaboration together. They need to decide, often at a fundamental operating level, what information needs to be shared and why? Who has access? Who is running the nodes? What data and information are they as a group going to rely upon? How does this integrate into their own internal systems, and how do they play with interoperability more generally to the extent there are other initiatives within their ecosystem to promote interoperability?

When we interviewed Dr. Naseem Naqvi, Editor-in-Chief for the Journal of the British Blockchain Association, he said that he believes in applying an evidence assessment framework when considering the potential use of blockchain technology ¹⁵⁵ and tells people to take what he calls the “PICO” approach: P – what is the problem; I – what is the new intervention; C – how does it compare to the existing intervention; and O – what are the outcomes and the evidence that it is better and that it works?

His ideas are summarized in an approach that he terms Evidence-Based Blockchain and the comments in his article ¹⁵⁶ on this approach echo the “lessons learned” noted in this section.

Naseem himself is very enthusiastic and passionate about the technology, but made it clear that there are practical implications, regulatory issues, and many other things that inhibit a successful application. He views that the technology’s major contribution is providing a data audit trail with immutable timestamps and noted that in scientific research the practical implementation of blockchain is targeted at protecting intellectual property – pre-published data, articles, etc. as well as for published work. Dr. Naqvi said that blockchain could certainly be applied to research funding because it allows for the transparent allocation of funds, the auditing of spending, and the tracking of funds. But how this would play out with regards to regulatory and policy issues remains to be seen. He noted that regulations and policies are very important and this needs to be highlighted in the white paper – which is the perfect segue into the following section – Blockchain Technology: Legal & Regulatory Considerations.

Blockchain technology and privacy: the general data protection regulation

It is a widely held belief that transactions performed on a blockchain are anonymous and hence private. On public blockchains, this belief is incorrect. ¹⁷⁶ Transactions on public blockchains such as the bitcoin blockchain are “pseudonymous” meaning that your actual identity is hidden behind one or more hexadecimal strings (your private and public keys). ^{177 , 178} Whilst it is possible to obfuscate your identity on a blockchain using more sophisticated techniques such as zero-knowledge proofs ¹⁷⁹ and transaction-joining protocols, ¹⁸⁰ it is always worth remembering that it is possible, albeit not easy, to identify who performed a transaction on a public blockchain. Misunderstanding of the connection between blockchain technology and anonymity, and hence privacy, has led to many concerns about the use of blockchain technology to transact and manage private data. This has been particularly true in the European Union (EU) because of the General Data Protection Regulation, or GDPR. ¹⁵⁴

GDPR is a legal framework which sets guidelines for the collecting and processing of personal information from individuals who live in the EU. Since the regulation applies regardless of where websites or systems which might collect personal information are based, it must be heeded by all sites that attract European visitors, even if they do not specifically market goods or services to EU residents. ¹⁸¹ A key aspect of GDPR which directly conflicts with the foundations of blockchain technology is the legal right to be “forgotten” – in other words your legal right for any information about “you” on any system stored by an organization anywhere in the world to be deleted at your request. A prime tenet of blockchain is its immutability and the absolute inability to edit, let alone delete data or metadata ¹⁸² held in one or more of its blocks. This tension has led many organizations to avoid using certain blockchain technologies when seeking to manage personal data (e.g., clinical trial data). However, judicious choice of the right DLT can make the benefits of blockchain accessible, even for personal data. More specifically, the use of private or more tightly controlled, permissioned blockchains can circumvent this apparent barrier, even in Europe. ^{121 , 124} For more information on blockchain and the GDPR please refer to a recent report on this topic. ¹⁸³

Blockchain technology and intellectual property

One use case area that would seem to be a good “fit” for blockchain technology ¹⁸⁴ is that of intellectual property protection. Blockchain provides the ability to capture a time-stamped, immutable record of an original innovation, most easily through a unique cryptographic hash of a document. As noted in Sections “Blockchain Technology: What is it? and Blockchain Technology: A Brief History” in this paper, so-called “hashing” of data is a critical component of blockchain technology. In summary, hashing is the process of putting a computer file of any kind (document, image, sound or video file, etc.) through an algorithm which compresses the entire file, including not just its content, but also its formatting, into a defined multi-character hash string. ¹⁸⁵ For every file, that hash is unique and exactly represents the content and format of the original file. ¹⁸⁶ Putting a hash of an original document onto a blockchain achieves two things:

1. It provides an immutable record, in a small piece of text (the hash string), of the existence and the content (albeit cryptographically concealed) of a file.

2. It provides a confirmed timestamp for when that hash was installed on a blockchain.

With these two properties, anyone who has a file which, when hashed using the right hashing algorithm, generates a hash which is identical to one already present in a block on a blockchain, knows that the file that they have is identical to a file and its content which existed at the time the original was mined into the particular blockchain. By this mechanism the blockchain operates as a surrogate file and document registry.

Storing hashes of original documents or files on a blockchain is an obvious potential for the use of DLT in the protection of intellectual property in all its forms, of which evidence of creatorship is only one, but it has yet to be fully explored legally. ¹⁸⁷ Nevertheless, various governmental agencies and IP registries such as the European Union Intellectual Property Office (EUIPO) are actively looking into the capabilities of blockchain. Relatively recently the U.S. Congress created a Congressional Blockchain Caucus as a platform for industry and government to come together to study and understand the implications of blockchain technology. ^{188 , 189 , 190} One other key point to note in this “blockchain & IP” section is another extensive strand of L&R discussion and publication which covers how to generate IP on the topic of blockchain technology – i.e., where the foundation of the IP is “the blockchain” itself. This area does not fall within the scope of this paper so is not covered in any more detail here, but for more information on this often-complex topic please refer to this report. ¹⁹¹

Blockchain technology and supply chains: the FDA pilot

One of the most important global regulatory bodies is the U.S. Federal Drug Administration – the FDA. The FDA’s primary responsibility is to “protect the public health by assuring that foods (except for meat from livestock, poultry and some egg products which are regulated by the U.S. Department of Agriculture) are safe, wholesome, sanitary, and properly labeled; ensuring that human and veterinary drugs, and vaccines and other biological products and medical devices intended for human use are safe and effective”. ¹⁹² The FDA’s position on blockchain technology was mentioned in the agency’s 2019 Technology Modernization Action Plan (TMAP). ¹⁹³ In that plan, it was stated that “Data-informed technologies, such as distributed ledger solutions such as blockchain, will be essential to support the FDA’s track-and-trace priorities.” Consequently, the FDA then announced ¹⁹⁴ the launch of a pilot program under the Drug Supply Chain Security Act (DSCSA) in which “participants representing the drug supply chain can pilot the use of innovative and emerging approaches for enhanced tracing and verification of prescription drugs in the U.S. to ensure suspect and illegitimate products do not enter the supply chain.” This led to four organizations, IBM, KPMG, Merck, and Walmart, to propose a pilot program to examine the use of blockchain technology in verifying and tracking pharmaceutical products in preparation for future DSCSA requirements. The two objectives of the program were to:

1. Demonstrate that blockchain can provide a common record of product movement by connecting disparate systems and organizations to meet DSCSA 2023 interoperability requirements in a secure way.

2. Improve patient safety by triggering product alerts and increasing visibility to relevant supply chain partners in the event of a product investigation or recall.

The results of the pilot were reported in 2020 ¹⁹⁵ and the four component organizations agreed that not only was the program a success, but also that “there are benefits to using blockchain both for, and beyond, DSCSA compliance.”

The use of blockchain technology to support and enhance the management of supply chains in multiple industries, from food to luxury goods, and logistics more widely has, outside Fintech, been one of the technology’s primary use-cases and this seems likely to be a major area for DLT in the years to come. ^{196 , 197}

Blockchain technology and GxP: enabling adherence to regulations

The blockchain-FDA example above describes how blockchain technology has the potential to help organizations better comply with specific legislation. Blockchain technology also has the potential to enable better and more effective adherence to regulations. The regulatory use-case example we will briefly describe is the potential for blockchain technology to help with good working and operating practices in the domain usually referred to as “GxP”. ¹⁹⁸ The ‘x’ in GxP is a catch-all abbreviation to cover the variety of different good practice regulations that exist. Well-known examples include Good Laboratory Practice (GLP); Good Manufacturing Practice (GMP); Good Clinical Practice (GCP). More specifically, GxP is a set of good practice quality guidelines and regulations, employed around the world in regulated industries such as pharmaceuticals, food, medical devices, and cosmetics. GxP has been put in place to ensure that the products and services from these industries are safe and meet their intended use. There are several essential components which enable GxP compliance. These are: (i) the People; (ii) the Processes; (iii) the Kit, Devices, and Facilities; and (iv) the Inputs and Outputs. In all four of these areas blockchain technology could be of significant assistance to help with compliance, ¹⁹⁹ but to pick just two (for brevity): in the “people” area, blockchain technology could help provide better personal digital identity, which is itself another important potential use-case for blockchain technology, ²⁰⁰ and/or to better manage training records and qualifications ¹³⁶ as noted earlier; these could enable better Good Laboratory Practice (GLP) compliance. Secondly, in the kit, devices and facilities area, as noted in Section “Medical Device Tracking” of this paper, blockchain technology is already being used to track and manage the maintenance of medical devices and equipment, but that use could be extended to cover bigger equipment and facilities in manufacturing and therefore help with better Good Clinical Practice (GCP) and Good Manufacturing Practice (GMP) compliance.

Blockchain legal & regulatory considerations around the world

In this section, we have focused mainly, but not exclusively, on the L&R considerations and issues as they apply to the United States at both the national government and state levels. The primary reasons for this are that we do not have the space in this paper to provide a comprehensive global view and, most countries (including the U.S.) are still in the process of developing and evolving their own sets of laws and regulations around blockchain technology. That situation is likely to persist for some years to come. However, we would like to provide you with some more links to reports and articles which describe in more detail how blockchain technology is being considered and, in some cases, legislated, in various jurisdictions around the world. All have been published since 2019.

1. “Blockchain and the Law” – International and European perspective ²⁰¹

2. “Blockchain and the Law: Regulations Around the World” ²⁰²

3. “Blockchain and the Law” – U.S.-focused ²⁰³

4. “How Blockchain Projects Can Succeed (and Avoid Legal Hassles) in the USA” ²⁰⁴

5. “Blockchain Regulation and Governance in Europe” ²⁰⁵

6. “Legal And Regulatory Framework for Blockchain” – EU-focused ²⁰⁶

7. “Blockchain: Legal and Regulatory Guidance Report” – UK-focused ²⁰⁷

8. “Blockchain and Cryptocurrency Regulations”: Japan ²⁰⁸

9. “Blockchain and Cryptocurrency Regulations”: Canada ²⁰⁹

10. “What the New PRC Blockchain Regulations Mean” – China-focus ²¹⁰

In closing, in this section we have endeavored to provide a very brief introduction, through four broad use-cases, to the legal and regulatory challenges of using blockchain and distributed ledger technology from the primary perspective of how these new technologies are impacting the scientific industries. For the sake of brevity, there are several areas we have chosen not to cover, e.g., blockchain governance; some of those we have omitted are outlined in a separate article. ²¹¹ We have also provided links to reports with a broader coverage of the legal and regulatory aspects of blockchain technology and we urge the reader to refer to these if they want to know more about this complex and still-evolving area. One more recent regulatory framework that does warrant further mention is MiCA, the European Union (EU) regulatory framework designed to establish uniform market rules for crypto-assets across the EU. MiCA aims to protect investors, innovators and collaborators, and promote the widespread adoption of blockchain and distributed ledger technology (DLT) in the EU’s virtual asset sector by providing legal certainty. More importantly, MiCA provides a firm legal basis for the incentivization, and the possible monetizing of scientific assets in the EU. ²¹²

Finally, while it may appear that the areas of blockchain and DLT are complex, daunting, and subject to a great deal of uncertainty regarding regulations and the law, what is certain is that this technology will impact and disrupt the science-based industries in the coming years. How it will disrupt and how visible that disruption will be, is yet to be seen, but we do believe that blockchain and crypto technology will come into scientific businesses in unexpected, but productive ways. Scientists should be prepared for that disruption, and they should, in our opinion, embrace it.

The first generation

As we stated earlier, the first generation of blockchain, exemplified by Bitcoin and based upon the 1991 work of Haber and Stornetta, was born in 2008. ²⁷ It was based on a conceptually simple consensus mechanism, proof-of-work. From the application/use case perspective, the technology was designed simply to form the technological base for a new kind of electronic money, cryptocurrency, by providing mechanisms to prevent double spending. While some exciting applications existed outside the domain of cryptocurrencies, such as Namecoin ²¹³ which was intended to change the way the Domain Name System (DNS) ²¹⁴ worked, the first-generation blockchains did not offer mechanisms that would enable a dynamic growth of new applications.

In terms of design, the technology was introduced by the relatively high-level white paper, Nakamoto’s “Bitcoin: a peer-to-peer electronic cash system,” ²⁷ and the open-source computer code. There was no authoritative, detailed specification separate from the code. While this approach worked quite well initially, it was an obstacle on the path toward applications beyond cryptocurrency.

Even so, the most popular and iconic first-generation blockchain, Bitcoin, still dominates the cryptocurrency market. Notably, at the time of writing, two other first-generation blockchains, Dogecoin ²¹⁵ and Litecoin, ²¹⁶ still top the chart of the most popular cryptocurrencies.

The second generation

One of the most distinctive aspects of the second-generation blockchains is the capability of offering functionalities that exceed those needed by crypto-assets systems. The most important feature is the systems’ capacity to execute smart contracts, in other words, pieces of software that can represent transactions or events in both the real and digital worlds, and which are also relevant within the context of business relations between the parties to a contract. Properties such as these allowed the second-generation blockchains to offer platforms for carrying out legally-binding actions with no central intermediaries. As regards the security features developed in the era of the first-generation blockchains, their second-generation counterparts lowered arbitration costs and significantly reduced the risks of fraud and technical failures in the digital infrastructure used for the transactions.

The most significant blockchain of the second generation is Ethereum which was first mentioned in Section “Blockchain Technology: What is it?”, and which is also a crypto-asset platform. However, its fundamental attribute is the availability of a Turing-complete programming platform. The Turing-completeness ²¹⁷ of a platform allows it to act as a computationally universal environment, enabling every possible computer algorithm to be executed. As of this writing, the Ethereum coin, known as Ether (ETH), is currently the second most valued crypto asset after the first generation’s Bitcoin.

Thanks to its radically new features, Ethereum brought multiple ‘derivative’ tools into play. The most noteworthy are the ERC20 ²¹⁸ token used for an Initial Coin Offering (ICO), ²¹⁹ a crypto economy analog of the Initial Public Offering (IPO) ²²⁰ for real-world businesses, and the Non-Fungible Token (NFTs), which are used for the creation of unique digital objects. NFTs, as mentioned earlier (e.g. in Sections “Matryx and Blockchain Technology: Legal & Regulatory Considerations”) can be used to represent ownership of nearly any object, tangible and intangible alike, which can be expressed in digital form. ²²¹

When it comes to design, Ethereum introduced something known as ‘client code,’ a new way of creating alternative software solutions compatible with the original at the protocol level rather than the source code compatibility level. The availability of detailed specifications has created several alternatives; in other words, it has facilitated many and varied implementations using a range of programming languages. All these systems can work together on the same network without problems.

Second-generation projects also offered a variety of different consensus mechanisms. As we have previously indicated in Section “Blockchain Technology: A Brief History” this paper, Ethereum was rolling out proof-of-stake consensus mechanisms with the final act of that process (called “The Merge”) played out on September 15^th, 2022. ²²² However, other consensus mechanisms or “protocols” such as delegated proof-of-stake (DPoS), ²²³ proof-of-burn (PoB), ²²⁴ practical Byzantine fault tolerance (pBFT), ^{225 , 226} and many more gave the second-generation blockchains a much higher transaction throughput, while reducing the associated energy consumption.

There are a great many interesting second-generation projects. It is worth mentioning the NEO blockchain, ²²⁷ which created an ecosystem intended to become the foundation for the next generation of the internet by providing tools for digitized payments, digital identity, and digital assets of a general kind. NEO has also proposed a unique consensus protocol. Known as delegated Byzantine Fault Tolerance (dBFT), ²²⁷ it represents an improvement on the pBFT protocol and has enabled NEO to exceed the 1,000 transactions-per-second (TPS) limit. By way of comparison, the credit card organization Visa can process over 1,700 transactions-per-second. ²²⁸

Another noteworthy case is the ICON project, ²²⁹ which is sometimes regarded as a precursor to the third generation of blockchains, given that it is focused on interoperability. It implements a ‘blockchain transmission protocol,’ enabling independent blockchains such as Bitcoin and Ethereum to exchange transactions. ICON adopts the Byzantine Fault Tolerant Delegated Proof-of-Stake (BFT-DPoS) consensus protocol ¹¹ and the economic-governance Delegated Proof-of-Contribution (DPoC) protocol. ²³⁰

The Hyperledger community mentioned in Section “Blockchain Technology: A Brief History” mostly contains second-generation blockchain projects. However, the recent release of Hyperledger Fabric (version 2.2 LTS) ²³¹ is also a big step toward third generation blockchains.

The third generation

In spite of the successes achieved with the second-generation blockchains as regards both the quality of their use cases and the technological innovations that they proposed, numerous unresolved major challenges remained, primarily related to scalability (the number of transaction per unit of time and/or number of network nodes), interoperability (the ability to work in an ecosystem where other blockchains exist), the protection of user and data privacy and confidentiality, and essential data management, particularly on-chain data management.

Fig. 4:

The three generations of blockchain.

Some analysts saw the arrival of Decentralized Applications (DApps) on the second-generation blockchain scene as the birth of the third generation of blockchains. ²³² DApps enabled the blockchain industry to have a real-world/business purpose. Blockchains of the third generation directly addressed the challenges of scalability, privacy, and interoperability which were identified as issues of concern in the previous generations.

Directed acyclic graph-based distributed ledger technologies

The quest for much higher scalability lay behind the development of solutions based on Directed Acyclic Graphs (DAGs). ^{233 , 234} An alternative or even, perhaps, a rival to blockchain, DAGs are types of Distributed Ledger Technology (DLT) solutions. A DAG DLT ²³⁵ is a network of individual transactions linked to other transactions. DAG-based networks do not have the linked lists of blocks that the classic blockchains do. In structure, they resemble a tree formed by branching transactions. The use of DAGs and the elimination of costly replication and consensus over blocks of data means that these solutions offer the theoretical throughput of millions of transactions per second (TPS) without the need for expensive mining. In practice, existing DAG-based DLTs reach a throughput of 10k TPS.

Notable examples here include IOTA, ²³⁶ which was designed for large-scale internet of things (IoT) networks. However, with its design of consensus protocol, Fast Probabilistic Consensus (FPC), ²³⁷ it has become a regular cryptocurrency platform.

Another important DLT technology that uses DAGs is Hashgraph, ²³⁸ with its patented ‘gossip about gossip’ protocol for building directed acyclic graphs of transactions. In effect, the protocol resulted in the creation of a special kind of asynchronous Byzantine Fault-Tolerant (aBFT) consensus algorithm. However, unlike the classical blockchains, Hashgraph transactions are not stored in blocks. Instead, strictly enforced transaction time-sequencing creates a secure, high-speed distributed ledger in the form of a DAG. Unlike most DLTs, Hashgraph is not open-source, and the only network running the protocol is Hadera Hashgraph. ²³⁹ Its cryptocurrency is HBAR. ²⁴⁰

However, despite the high transaction throughput, there is still no wide-ranging industry consensus on how much trust can be placed in DAG-based DLTs. Both IOTA and Hashgraph, as well as other DAG DLTs such as Nano ²⁴¹ or Obyte ²⁴² (formerly Byteball), have drawn a considerable amount of criticism concerning the uncertainty as to whether they provide enough security, even against fundamental threats such as double-spending attacks.

Multilayered blockchains

The uncertainties surrounding DAG-based DLTs, and the innovations of developers associated with traditional, first- and second-generation blockchains have given rise to solutions that have expanded the capacities of the second generation of blockchains, rather than replacing them. There are a great many interesting proposals for such expansions, however the most important are those related to multilayered architecture.

The multilayered nature of blockchain architecture brings a clear separation of the software responsible for transactions from the software accountable for maintaining the entire network and smart contracts. The underlying reason for this is that it increases the network’s capacity and speed. One of the most prominent examples of multilayered blockchains is Cardano, ²⁴³ with ADA, ²⁴⁴ its cryptocurrency, numbering among the highest valued of those related to third generation blockchains.

Nonetheless, an entire family of innovative third generation blockchain solutions known under the umbrella term of ‘Layer-2 solutions’ ²⁴⁵ contains the most noteworthy examples. These new systems are built on top of the second-generation blockchains, which are classified as Layer-1 solutions. In general, the Layer-2 systems achieve a much higher level of efficiency by limiting the dissemination of every transaction to the whole network. This is achieved by executing them in a separate part of it, known as the off-chain mode. The use of the main chain, which is usually expensive and slow, is then only used when needed to resolve potential disputes. Layer-2 off-chain operations are performed in sidechains pegged to the main chain. The Layer-2 architecture is illustrated in Fig. 5.

Fig. 5:

The conceptual architecture of Layer-2, third-generation blockchains.

While the ‘Lightning Network’, which was invented back in 2015 ²⁴⁶ and built on top of Bitcoin, was the first Layer-2 solution implemented in practice, most of the innovative ideas originated in Ethereum developer circles. The first such idea was Plasma, ²⁴⁷ which can be visualized as a living tree ²⁴⁸ with numerous branches, rather than as a linear chain. The main blockchain is then depicted as a trunk. In most cases, Ethereum, which is supported by its trusted consensus mechanism, guarantees security and the flow of proofs, much like a trunk supplying energy and nutrients to its branches. And in another analogy, the main blockchain plays the role of a Supreme Court, which imparts judicial powers to the lower courts. The two most important Layer-2 networks today are Polkadot ³⁹ and Polygon. ²⁴⁹

Layer-2 solutions form the technological basis for the recent rapid growth of blockchain-based financial instruments previously offered only by centralized institutions such as banks, stock exchanges or organized stockbrokers. These instruments include lending and borrowing, trading derivatives, providing insurance against transactional risks, and earning interest on the crypto assets working in an analogy to standard saving accounts. They are also known generically as ‘Decentralized Finance’ (DeFi) and they, too, were made possible by the rise of DApps, and the transaction speed offered by Layer-2 solutions.

Interoperability-oriented solutions

In addition to scalability, third generation blockchains attempted to resolve other complicated problems relating to second-generation blockchains. Those problems can be identified as interoperability between different blockchain networks, privacy protection, and data management.

The two most important solutions with goals directly related to interoperability issues are Cosmos ²⁵⁰ and NeoX. ²⁵¹ Cosmos blockchain architecture assumes the existence of several independent networks referred to as Zones, which are connected to the Hub, as the central blockchain is known. The separate blockchain Zones are then plugged into an ecosystem called the Cosmos Network.

NeoX also implements cross-chain interoperability by allowing its participants to exchange transactions between different chains in a fully transactional mode; in other words, the entire multi-chain transaction either succeeds or it fails completely.

The Polkadot Layer-2 blockchain mentioned Section “Multilayered Blockchains” also has interoperability high on its list of goals. “Related to Polkadot is another interesting third-generation project: Kusama”. ²⁵² Called by its creators a “canary network”, ²⁵³ mostly for its experimental character and test-bed like applications, the Kusama Network introduced the concept of “parachains”. A parachain is “an application-specific data structure that is globally coherent and verifiable”. ²⁵⁴ As such, it usually takes the form of a layer-1 blockchain, but it can take other forms providing trusted computation. Kusama allows for the creation of an ecosystem with many different parachains, providing full interoperability with new and existing blockchains, such as Ethereum.

Privacy-focused projects

Privacy is another complicated blockchain technology problem. Traditional blockchain networks expose all their transactions and are completely transparent, meaning that their participants can be identified indirectly, at the very least, and tracked. Of course, there is a fundamental trade-off between protecting privacy as a fundamental value and protecting against cybercrime, including confidence tricks, internet fraud, and ransomware. However, some aspects of privacy can be addressed by the application of the pair-wise decentralized identifiers, Verifiable Claims, which are part of Self-Sovereign Identity (SSI) ²⁵⁵ solutions, and zero-knowledge proofs (ZKPs), ²⁵⁶ all of which are implementable as blockchain-based solutions. Some prominent examples in that domain are CoinJoin, ¹⁸⁰ a privacy protection technology used by Dash ²⁵⁷ (a fork from Bitcoin), Monero ²⁵⁸ (using advanced ring signature technology), and Zcash, ²⁵⁹ which uses ZKPs. ²⁵⁶ A ZKP is a cryptographic technique by which one side can prove the truth of a fact to a second side without disclosing the details of that fact.

As regards SSI solutions, one of the most prominent blockchains is offered by the Sovrin Foundation ²⁶⁰ and its global digital identity network, which is based on the Hyperledger Indy framework. The standardization and advocacy group in that domain is the Decentralized Identity Foundation. ²⁵⁵

Data management on blockchains

Finally, some third generation blockchains focused on data management. In a nutshell, they tried to offer a solution to another complicated problem, namely, data storage on a blockchain. For some applications of the technology, it is highly desirable to be able to store a significant amount of data using the on-chain mode. It is also desirable to store ‘structured’ data instead of the binary ‘blobs’ of the first-generation blockchains or the string-serialized data structures of the second generation.

A prominent example of this kind of solution is BigchainDB ²⁶¹ from MongoDB, the authors of the popular key-value database of the same name. BigchainDB offers on-chain structured data storage with all the attributes of blockchains, in other words, data integrity, confirmability, non-repudiation, and high availability. Other companies pursuing on-chain data storage solutions include Storj, ²⁶² Swarm, ²⁶³ Sia, ²⁶⁴ FlureeDB, ²⁶⁵ and GraphChain; ^{266 , 267} these are similar solutions based on modern semantic graph databases.

The future of blockchain technology: is the fourth generation coming?

In the light of the current development of the third generation blockchains, it seems somewhat speculative to write about the next generation, particularly when the real and long-lasting benefits of today’s solutions still lie ahead of us. Nonetheless, this does not stop numerous authors from forging a vision of a future fourth generation, where all the previous challenges will finally be resolved and “trust in easy-to-consume ways” ²⁶⁸ will be enabled, “accelerating the formation, operation, and reconfiguration of business networks”. ²⁶⁸ From the technology perspective, there are predictions about the vital role of Artificial Intelligence in the fourth generation blockchains. ^{269 , 270 , 271} There are new initiatives that have already been dubbed “fourth generation” blockchains. One of the more interesting is Multiversum, ²⁷² which claims to “achieve syntony between IT security and cryptocurrencies universes”. ²⁷³ Hydrus7, which is “built with robust advancements in a more structured and scalable manner with the help of AI, ML, Data Compression in Blocks, sharding, ²⁷⁴ and many other cutting-edge technologies”, ²⁷⁵ is another. There are initiatives based on the concept of meta-tokens. For example, MetaMUI ²⁷⁶ defines meta-token as a “collateralized asset-backed metamorphic digital asset that can change the shape based on usage.” Assuming these ideas materialize, we should indeed soon see the onset of fourth generation blockchains. However, it is still hard to judge whether we are indeed witnessing the birth of the fourth generation blockchains or if we are only seeing clever marketing narratives at work. Despite these uncertainties, there is an extremely interesting development of blockchain-related technologies, which could lead to a much stronger and more resilient ecosystem of distributed computing. It is worth mentioning technologies such as MPC (Multi-Party Computation), which is based on the most advanced cryptographic algorithms, and which allows for the deployment of secure privacy-preserving solutions. MPC ²⁷⁷ technology is a base for the most advanced custody solutions, which help people and organizations to manage their private keys in the most secure way and which may have application to other cases described in this white paper.

The impact of quantum computing

There is little doubt that another important, incoming information technology revolution will assuredly accelerate the development of blockchain technology. This revolution will happen because of the rise of practical quantum computing and quantum information technologies.

Until recently, quantum computing technology (QCT) was relatively unknown to the public. It has now become a topic of current popular interest because of the potential capability of quantum computers to deliver an unprecedented increase in computational power. Work on the hardware, software, and algorithms for this new reality of computing is now proceeding at full speed in academic and commercial environments. For obvious reasons, we cannot provide an overview of those efforts here. We can, however, refer readers to an excellent publication from the National Academies Press (NAP), Quantum Computing. Progress and Prospects. ²⁷⁸ The primary purpose in devoting some space in this paper to QCT is because of its potential threat to the one of the foundations of blockchain technology, cryptography and cryptographic standards and algorithms.

One of the most remarkable features of quantum computing is that the first, most essential algorithms invented for that domain were related to cryptography. More precisely, they could be classified as crypto analytical algorithms as their application for breaking or weakening most existing modern cryptographic algorithms was straightforward. Shor’s algorithm ²⁷⁹ guarantees polynomial time integer factorization, making it possible to break existing asymmetric ciphers in a reasonable time. Grover’s algorithm, known as the quantum search algorithm or function inversion algorithm, can weaken both symmetric ciphers and some hashing algorithms. In short, the rise of quantum computing could bring an existential risk to existing cryptography. This risk is recognized and adequately addressed by organizations responsible for the security of ciphers. The U.S. National Institute of Standards and Technology issued a clear warning in 2016. ²⁸⁰ Soon after, it initiated a standardization process for what is known as post-quantum cryptography. ²⁸¹ This branch of cryptography is also known as quantum safe. It is defined as a set of rules and classic, non-quantum, cryptographic algorithms are assumed to be secure against cryptanalytic attacks by quantum computing algorithms.

Alongside quantum-safe classic cryptography, there has been enormous progress in the complementary field known as quantum cryptography, a branch of cryptography that uses quantum mechanical properties of matter to create cryptographic protocols. ²⁸² The best-known protocol of quantum cryptography is Quantum Key Distribution (QKD). ²⁸³ It allows for the provably secure sharing of secret keys that can be used to encrypt and decrypt messages. There are ongoing debates as to whether the QKD protocol can provide the proper protection from possible attacks and if post-quantum cryptography is the right choice. ²⁸⁴

The risks posed by quantum computing will also impact the further development of blockchain technology significantly. Cryptography, and asymmetric cryptography in particular, forms the foundation upon which blockchains are built. Quantum computing introduces a substantial threat by making asymmetric algorithms vulnerable to attacks, which could potentially lead to the discovery of users’ private keys, thus posing an existential risk to the stability of blockchains. Furthermore, since this form of cryptography is crucial for secure communication between blockchain nodes, their integrity is also at risk.

There is plenty of literature which both addresses the dangers and indicates possible solutions. ^{285 , 286 , 287} However, despite some isolated attempts, until recently blockchain developers’ communities are showing no significant interest in redefining the way new systems are built to deliver quantum resistance.

Quantum information technologies, along with post-quantum algorithms endorsed by NIST, have the potential to not only increase the security of blockchain systems but also to help them overcome the limitations that are common to blockchains and other distributed systems. This topic, among others, is detailed by Imran Bashir in a dedicated chapter titled “Quantum Consensus” in his book “Blockchain Consensus.” ²⁸⁸

When it comes to blockchain security, the earliest and most serious attempt was delivered by a team behind The Quantum Resistant Ledger (QRL) project. ²⁸⁹ The QRL has developed, and now runs, a blockchain system which uses post-quantum algorithms to ensure its quantum safety. David Chaum, widely recognized as the person who invented digital cash, runs an innovative blockchain platform called XX network, ²⁹⁰ which claims to be quantum safe. XX network uses post-quantum cryptography to achieve quantum safety. Another project declaring quantum-safe operations using post-quantum crypto is the QAN Platform. ²⁹¹

Quantum Blockchains, ^{291 , 292} a startup launched in 2020, is building the foundations for the future of blockchains using quantum cryptography. ²⁹³ The project recently introduced what the company calls QSB – Quantum Secured Blockchain, built on the three pillars of quantum-resistant cryptography: Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), and Quantum Random Number Generation (QRNG). Their white paper, which describes the implementation, has recently been made available. ²⁹⁴

Closing comments on blockchain development

In closing this section on the status and future development of blockchain technology, it should be clear that the pace of invention has been rapid and that three distinct generations of blockchain technology can already be identified – all this despite the short history of running blockchain platforms. Each generation has been technically more advanced than its predecessor and has allowed for qualitatively different applications, from the cryptocurrencies of the first generation, through the smart contracts of the second, to the third, where we arrived at decentralized finance and a variety of other applications.

We are now creating an entirely new digital assets economy and a multiplicity of applications for use cases going beyond the crypto economy. The direction in which technology is advancing is opening new opportunities for “non-cryptocurrency” cases. For example, applying the layer-2 paradigm means that it is now acceptable to launch brand new child chains ‘pegged’ to the main net of a respected network such as Ethereum. A child chain of this kind can be designed for special applications such as digital credentials, attribution, supply chain and the internet of things (IoT), ²⁹⁵ to name but a very few. The difference that layer-2 makes is that, should a dispute arise, authenticated claims can be submitted to the parent chain to decide the outcome. This makes the solution independent without isolating it from the bigger ecosystem of trust. Similarly, the interoperability-oriented blockchain solutions applied in ‘non-crypto’ applications offer much more freedom to developers while guaranteeing compatibility between different chains.

Finally, third-generation projects devoted to digital identity and on-chain data management offer additional functionalities for new kinds of projects that were unavailable in the early blockchain systems, such as the possibility of storing essential data right on the chain and allowing them to replicate across the entire network.

While it is hard to predict the future of such a volatile domain of technology, there is also no doubt that the innovative solutions reducing the risk of quantum computers will bring yet another wave of solutions that will only strengthen the position of blockchain technology in the modern digital world.

Four take-home points on blockchain technology

Finally, we would like to give you four take-home points on the key aspects of blockchain technology to remember, separate from how that technology can be applied to the scientific workflow:

1. Blockchain is not cryptocurrency. Do not let cryptocurrency scandals deter you from learning more about the technology.

2. Blockchain is a potential disruptor for all industries, especially where third party intermediaries are involved. Everyone should take this technology seriously and potentially consider using it to their advantage. But…

3. Blockchain is not a solution in search of a problem; while worth exploring, implementation is not for everyone or for every business challenge. Do your homework first!

4. Blockchain has been built on prior technologies, many of which are still essential. It is important to know what has gone before and to continue to build upon the strongest technologies.

Below are also two highly relevant quotes whose individual messages need to be carefully balanced within the context of this paper. These are:

“We are stuck with technology when what we really want is just stuff that works”. ³⁰⁵

And

“We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run”. ³⁰⁶

Given the summary above, a word of advice to the reader – do not underestimate the potential of blockchain technology in the long run. Since this technology was selected as one of IUPAC’s Top 10 Emerging Technologies in Chemistry in 2021, we hope to continue to monitor blockchain’s adoption in chemistry and the emergence of new uses cases and update this white paper in the not-too-distant future. And if, in the meantime you want to learn more about the technology at a more formal level, we refer you to a list of “The Best Universities for Blockchain and Cryptography in the World” that was updated by EduRank in February 2024 ³⁰⁷ and a list of reading material in Appendix B Please, do not hesitate to reach out to us with questions, to discuss your own blockchain experience, or to provide input as to what you would like to learn more about this technology. We very much look forward to hearing from you, and our contact information is below.