Blockchain for applications of clinical trials: Taxonomy, challenges, and future directions

IET CommunicationsVolume 16, Issue 20 p. 2371-2393 REVIEWOpen Access Blockchain for applications of clinical trials: Taxonomy, challenges, and future directions Lei Hang, Corresponding Author Lei Hang [email protected] orcid.org/0000-0002-9336-9274 Business School, Shanghai Normal University Tianhua College, Shanghai, China Correspondence Lei Hang, Business School, Shanghai Normal University Tianhua College, Shanghai 201815, China. Email: [email protected] Chun Chen, Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China. Email: [email protected] Contribution: Methodology, Project administration, Writing - original draftSearch for more papers by this authorChun Chen, Corresponding Author Chun Chen [email protected] Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China Correspondence Lei Hang, Business School, Shanghai Normal University Tianhua College, Shanghai 201815, China. Email: [email protected] Chun Chen, Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China. Email: [email protected] Contribution: Formal analysis, Writing - review & editingSearch for more papers by this authorLinchao Zhang, Linchao Zhang orcid.org/0000-0001-8547-9273 Department of Computer Engineering, Jeju National University, Jeju, KoreaSearch for more papers by this authorJun Yang, Jun Yang Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaSearch for more papers by this author Lei Hang, Corresponding Author Lei Hang [email protected] orcid.org/0000-0002-9336-9274 Business School, Shanghai Normal University Tianhua College, Shanghai, China Correspondence Lei Hang, Business School, Shanghai Normal University Tianhua College, Shanghai 201815, China. Email: [email protected] Chun Chen, Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China. Email: [email protected] Contribution: Methodology, Project administration, Writing - original draftSearch for more papers by this authorChun Chen, Corresponding Author Chun Chen [email protected] Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China Correspondence Lei Hang, Business School, Shanghai Normal University Tianhua College, Shanghai 201815, China. Email: [email protected] Chun Chen, Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China. Email: [email protected] Contribution: Formal analysis, Writing - review & editingSearch for more papers by this authorLinchao Zhang, Linchao Zhang orcid.org/0000-0001-8547-9273 Department of Computer Engineering, Jeju National University, Jeju, KoreaSearch for more papers by this authorJun Yang, Jun Yang Department of Otorhinolaryngology Head and Neck Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaSearch for more papers by this author First published: 27 August 2022 https://doi.org/10.1049/cmu2.12488Citations: 1 Funding information: Shanghai Chenguang Plan, Grant/Award Number: 21CGB08 AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Patient enrollment, data sharing, and data privacy are enormous medical challenges for clinical trial studies. In recent years, blockchain technology has drawn the attention of various researchers and institutes. As a new and innovative distributed ledger technology, blockchain can be critical to addressing these challenges, thus making clinical research transparent and building public trust fairly and openly. However, the existing literature lacks a comprehensive survey on the adoption of blockchain in clinical trials. To fill the research void, this paper presents a punctilious taxonomy of blockchain technology in clinical trials according to the literature. This taxonomy comprises decentralized scenarios, decentralized practices, blockchain types, deployment methods, and consensus algorithms. The results show that blockchain technology can cover all aspects of the clinical trial study in a decentralized, secure, transparent manner. Besides, some open research challenges of blockchain are categorized into three groups: technical challenges, security challenges, and organizational challenges. Moreover, some recent blockchain projects, micro applications in clinical trials, and several research areas or technologies for future research and development are discussed. 1 INTRODUCTION The clinical trial is an important part of drug development, and a means to ensure drug efficacy and safety [1]. During the trial, researchers collect data from the subject at preset intervals, including vital signs, changes in symptoms, and side effects caused by the study medicine. In general, the clinical trial requires collaboration among several parties, including regulatory agencies, pharmaceutical companies, clinical sites, and most importantly, the participants [2-4]. In addition, each participant in a clinical study contributes a unique set of capabilities to support the infrastructure of the clinical trial. As shown in Figure 1, the current workflow of clinical trials consists of different, independent activities [5]. In this paradigm, data is collected from disparate sources (smart devices, clinical trial sites), processed, and analyzed according to the preferences of each organization. FIGURE 1Open in figure viewerPowerPoint The current process for clinical trials It is believed that around 10% of clinical research cannot be replicated [6]. The high mistake rate is most likely caused by human error, fraud, or misbehaviour. Typical errors in data collecting and transcription may directly impact the quality of the data collected in clinical studies [7]. Data inconsistency in clinical trials can lead to the imprecision medicine problem [8]. Due to these concerns, more supervision requirements are required, raising the regulatory burden of document inspection. Under the existing system for clinical trials, assessing data quality is not a simple task. It is not easy to find data exceptions in a timely manner, and business domain and data modelling expertise are required to maintain a reasonable degree of data quality [9]. Currently, domestic and international drug clinical trial supervision consists mainly of post-monitoring, and there is a time gap in the supervision of data quality management and operational planning requirements. Blockchain is a decentralized, verifiable, and tamper-resistant electronic ledger suitable for application domains where collaboration between multiple participants and data transparency are equally important in the network. In 2008, Satoshi Nakamoto established blockchain as the public record for the digital currency Bitcoin [10]. From the introduction of cryptocurrencies to distributed ledger systems and mobile apps, this technology is being embraced across all industries, and its use has become a significant plus for businesses. As the technology improves, different applications beyond financial and banking services have been investigated [11-14]; the healthcare business could benefit from its adoption [15-23]. For instance, blockchain-based models for electronic medical records have been suggested to enable individuals to exert more control over their medical data and improve data exchange across platforms [24-26]. Furthermore, blockchain technology has been used in forestalling pandemics [27] and remote patient monitoring [28]. The features of blockchain technology, such as data transparency and traceability, have accelerated the reformation of current healthcare institutions, including health data interchange and patient follow-up through transaction trace [29]. Utilizing blockchain technology to manage clinical trial databases shows great potential for enhancing research in pharmaceutical industries. Besides, blockchain can disrupt the clinical trial industry while diminishing the use of legacy data management platforms [30-32]. Blockchain technology could directly address the present issues with clinical trials and improve the management of clinical trials by regulatory bodies and research institutes. Besides, it could enhance the underlying technology of clinical trial research, ultimately boosting the credibility of clinical studies. In clinical trials, a Peer-to-Peer (P2P) network is created using blockchain technology to record data interactions throughout clinical trials, enable data exchange, and make trial data visible and immutable [33-35]. The smart contract [36], which functions as a decentralized program that lives on the blockchain, can automate these procedures. For example, it could fulfil numerous functions concurrently, such as automating the business logic of an application without involving third parties, assuring data provenance, producing immutable audit trails, and imposing duties on an action if specific rules are satisfied [37]. Tools using blockchain technology can automatically link and distribute healthcare data to other researchers and clinics. As a result of the immutability of blockchain records, auditing and data verification are facilitated. The integrity of immutable clinical trial data stored on a blockchain can inspire more faith, resulting in safer medications and increased public confidence in scientific research. Figure 2 describes the process of a clinical trial based on blockchain technology. Unlike the current process of clinical trials shown in Figure 1, the data among different stakeholders is transparent and accessible. The blockchain preserves a complete, up-to-date history of all trial-related data, including the clinical protocol, visit history, subject info etc., which would track the enrolled subject during the clinical trial study. The data lake serves as an isolated data repository, known as off-chain storage. The blockchain network consists of trusted validating peers, and each peer holds a copy of the ledger for the network to maintain the consistence of the distributed ledger. The clinical director can access the trial-related data through any network peer where their information is preserved. This is realized by specifying the access control policy in the smart contract, which is deployed into the entire blockchain network to ensure data privacy and security. All the end users and blockchain interactions are encrypted with a digital signature to ensure the system's security. FIGURE 2Open in figure viewerPowerPoint Blockchain-based process for clinical trials Table 1 outlines and compares the proposed survey with recent, state-of-the-art reviews of using blockchain in the healthcare sector. The development of blockchain technology is still in its infancy, though previous studies have validated it in several use cases in the healthcare sector. The current literature lacks a comprehensive survey on the adoption of blockchain technology in clinical trials. To fill this gap, we review the state-of-the-art of blockchain technology in clinical trials and explain the key concepts that enable blockchain technology to enhance the process and management of clinical trials. Some recent blockchain projects and micro applications in clinical trials are discussed, as well as the open challenges and future research directions. TABLE 1. Summary of related surveys in the healthcare sector Ref Problem Statements Blockchain Services Open Challenges Research Directions Theme of Work [15] Inaccurate information, speculations, and uncertainties about the potential utility of blockchain in the healthcare industry 1. Electronic Medical Record (EMR) 2. Pharmaceutical supply chain 3. Biomedical research and education 4. Remote patient monitoring (RPM) 5. Health insurance claims 6. Health data analytics 1. Interoperability 2. Security and privacy 3. Scalability 4. Speed 5. Patient engagement 1. More prototypes 2. Open standards Use cases for the application of blockchain in healthcare, limitations, and areas for future research [16] Unrealistic proposals and ideas and current literature provide a little overview of applications EMR N/A 1. More technical details 2. Compliance of blockchain systems with current health data laws and standards Examples of utilizing blockchain to improve processes and services in healthcare, health sciences, and health education [17] N/A 1. Healthcare data sharing systems 2. Blockchain platform for clinical trials and precision medicine 3. Healthcare data gateway 1. Scalability 2. Interoperability and security 1. Conduct with real-world datasets 2. Realm of Identity verification Blockchain applications in healthcare, research challenges, research opportunities [18] It is crucial to identify those issues and challenges of the Internet of Things (IoT)s and blockchain technology in the healthcare sector 1. Drug traceability 2. RPM 3. EMR 1. Interoperability 2. Security 3. Scalability and Storage Requirement Handling 4. Lack of Standardization 5. Hesitation and lack of trust 6. Data ownership and accountability N/A The applicability and challenges of IoT and Blockchain in the medical sector [19] Previous surveys focus on the adoption of blockchain in healthcare applications and lack discussion of other important aspects of blockchain 1. Drug traceability 2. EMR 3. Clinical trials and precision medicine 4. Consistent permissions 5. Telehealth systems 6. Health insurance claims 7. Medical billing systems 1. Scalability 2. Navigate regulation uncertainty 3. Interoperability 4. Irreversibility and quantum computing 5. Tokenization 6. Data accuracy 7. Culture adoption and blockchain developers 1. Moving toward the IoT-based healthcare systems 2. Interoperability with legacy systems 3. Blockchain policies 4. Secure smart contracts 5. Performance bottlenecks Blockchain features, advantages, opportunities, recent case studies, open challenges in healthcare data management [20] Current literature provides a little overview of blockchain applications that have been developed, tested, and deployed 1. EMR 2. Data sharing 3. Data security and identity management 4. Financial and records 5. Pharmaceuticals 6. Public health 7. Organ transplant 1. Technical challenges 2. Organizational challenges 3. Drivers for adoption 4. Government regulations More research in real-case applications A literature review to find out the pivotal roles blockchain technology play in solving some of the most critical and challenging issues facing the healthcare industry [21] Lack of bibliometric studies of blockchain technology in the industry of healthcare 1. Telecare medical information system (TMIS) 2. E-health system 1. Scalability 2. Blockchain size 3. Interoperability and standardization 4. Organization skill 1. User authentication 2. Authorization and access control 3. Secure search Address the gap between the healthcare industry and blockchain technologies by evaluating previous activities [22] N/A EMR access 1. User and attribute revocation 2. Data privacy 3. Scalability 4. Blockchain latency N/A An extensive survey on blockchain-based access control methods in the healthcare domain [23] N/A 1. EMR 2. Clinical trials 3. Medical supply chains 4. Medical product integrity Lack of expertise N/A A brief overview of blockchain technology applications in healthcare This Survey Current literature lacks a comprehensive survey on the adoption of blockchain in clinical trials 1. Patient recruitment 2. Consent traceability 3. Persistent monitoring 4. Data management 5. Data analytics 1. Technical challenges 2. Security challenges 3. Organizational challenges 1. Combination with Artificial Intelligence (AI) and big data 2. Promotion of unified data standards 3. Integration of regulators and industry associations A comprehensive survey of the blockchain technology for clinical trials, blockchain services, taxonomy, projects, challenges, and future research directions The key contributions of this paper are highlighted as follows: Providing a detailed review of the state-of-the-art blockchain technology in clinical trials fulfils the research gap in the current works. Overviewing the issues in current clinical trial research. Discussing many characteristics and premier advantages of blockchain solutions in clinical practice and the underlying concepts. Presenting a thematic taxonomy to evaluate the role of blockchain in clinical trials regarding trial-related scenarios and practices, blockchain type, and consensus protocol. Highlighting ongoing efforts to use blockchain technology in clinical trials. Identifying, enumerating, and discussing several crucial challenges and future research directions toward using blockchain technology in clinical trials. The remainder of this paper is structured as follows: Section 2 elaborates on phases of current clinical trials. Section 3 overviews the issues in current clinical trials. Section 4 describes the taxonomy of blockchain in clinical trials. The development trend of blockchain applications in clinical trials is discussed in Section 5. Some recent micro blockchain applications in clinical trials are reviewed in Section 6. Section 7 outlines some open research challenges using blockchain technology in clinical trials. Section 8 highlights future research directions, and finally, Section 9 concludes the survey. 2 PHASES OF CLINICAL TRIALS Human participants are used in clinical trials to determine if a drug is useful and what negative effects it may produce. The trials collect information on a treatment whose efficacy in treating a particular ailment has not yet been established. A drug being evaluated in a clinical study is an experimental drug [38]. Before a novel treatment can be utilized in a clinical trial, it must undergo preclinical testing. All in vitro (test-tube or laboratory) research and animal experiments include preclinical testing. To determine preliminary efficacy, toxicity, and pharmacokinetics, several doses of the test medication or an in-vitro substrate are administered to animals [39, 40]. In different rounds of clinical trials, new drugs and therapies are evaluated for their ability to combat freshly discovered or existing pathologies. These clinical trial stages are the measures scientists take to test the effectiveness of novel drugs or therapies on a limited sample of patients. As represented in Figure 3, a new treatment goes through several phases. Each phase has a different purpose: phase 1 trials test if a new treatment is safe and look for the best way to give the treatment. Phase 1 trials usually include less than 100 patients divided into small groups. Doctors also look for signs that the disease responds to the new treatment; Phase 2 trials test if one type of disease responds to the new treatment, 100–300 patients usually join a phase 2 trial. If the new treatment works, doctors may go on to study in a phase 3 trial; Phase 3 trials test if a new treatment is better than a standard treatment. Phase 3 trials may include 300–3000 patients worldwide; Phase 4 trials find more information about long-term benefits and side effects. FIGURE 3Open in figure viewerPowerPoint Current phases of the clinical trial [41] Table 2 details the roles and responsibilities of stakeholders in clinical trials. US Food and Drug Administration (FDA), Institutional Review Board (IRB), Sponsor, Contract Research Organization (CRO), Principal Investigator (PI), Clinical Research Coordinator (CRC), and the subject are the parties participating in a clinical trial system. The current approach for clinical trials is centred on the sponsor, and the CRO monitors and controls the process. TABLE 2. Responsibilities of clinical trial stakeholders [42] Stakeholder Responsibilities FDA 1. To develop a regulatory structure that all clinical trials must follow 2. To assure the availability of medications that meet national standards for safety, quality, and effectiveness. 3. To terminate an ongoing trial if there are serious Good Clinical Practice (GCP) violations IRB 1. Approve the clinical trial protocols, which explain the participants eligible for the clinical trial, the schedule of tests and procedures, the drugs and doses to be tested, the duration of the research, the study's goals, and other information. 2. Ensure that the study is ethical, that participants have provided informed permission, that they are aware of the risks, and that researchers take the necessary precautions to safeguard patients from damage. Sponsor 1. Companies, research institutes, and other groups responsible for a drug's development 2. Show the FDA the findings of preclinical animal testing and what they intend to undertake for human testing CRO 1. To examine administration and management 2. To qualify, select, and initiate of a site 3. To manage the database PI 1. To create the trial's conceptual framework 2. To compose and submit the clinical trial protocol for IRB clearance. 3. Patient recruitment and management of the informed consent procedure CRC 1. To provide care under the clinical trial protocol 2. To analyze and interpret, among other things, laboratory data, Electrocardiographs (ECGs), and adverse occurrences 3. Maintain a record of how each patient reacts to therapy and note any adverse effects Subject 1. To provide the permission form 2. To comprehend the function of the IRB in safeguarding patient health 3 ISSUES IN CURRENT CLINICAL TRIALS A continual and effective flow of medical advances is essential for meeting society's rising medical demands. Ongoing study indicates that drug development costs increase by 9% annually [43]. There are issues with all facets of drug clinical trials, including preparation before clinical trials, protecting subjects' rights and interests, and implementing, recording, and managing clinical trial samples. This section discusses several issues in current clinical trial research. Data reliability In recent years, there have been some cases of clinical trial fraud at home and abroad, mainly involving data fraud and selective publication, which have caused public bias against clinical trials. In a survey of researchers in clinical drug trials, about 17% reported being aware of data tampering or falsification [44]. For instance, in July 2014, Science reported that Japanese researchers falsified data in the antihypertensive drug Diovan clinical trial. Data integrity, standardization, and authenticity are essential requirements for clinical trials. The problems of integrity and standardization are mainly due to data missing, which is insufficient to judge the validity and safety. The authenticity problems involve fraud, including the fabrication, tampering, concealing of data, and the inability to trace the original data. Irregular informed consent process Clinical trials cannot be separated from the participation of patients. However, the informed consent process in previous clinical trials was not rigorous, and some patients participating in clinical trials were not clear about the process and content of the trial. The FDA pointed out in the research report that nearly 10% of the trials had defects in implementing informed consent, such as expanding the scope of information acquisition and modifying informed consent without permission. Article 25 to 32 of the Declaration of Helsinki [45] stipulates that subjects in clinical trials must obtain consent from the subjects. Researchers must inform the clinical trial objectives, methods, risks, and other contents. In practice, the number of tested patients is large, and the number of phase 4 clinical trial subjects is more than 2000. It is a significant workload to obtain informed consent, and informed consent is not a one-time but a repeated cycle process. Therefore, it is urgent to adopt a new method to improve the efficiency of informed consent in clinical trials. Data traceability The FDA only collects clinical trial data management reports from clinical trial sponsors but cannot participate in clinical trial data inspection in real-time to detect potential data quality management problems [46]. Data forgery and human input errors may occur between multiple drug clinical trial centres and sponsors or between sponsors and government-related regulatory agencies. In the current drug clinical trial system, the inspection and verification of data by the relevant government supervision institutions are delayed significantly. The efficiency of reviewing different drug clinical trial data needs to be further improved. Several eClinical technologies have arisen in the last decade to streamline trial operations and data administration. Existing fully-integrated and comprehensive eClinical systems are only available to major pharmaceutical companies since they are prohibitively costly. For authorities that have difficulty monitoring research data, there is no easy and safe way to see the complex network of data exchange, no real-time access to results once they are made, and no simple way to track historical data [47, 48]. Thus, the FDA recognized a lack of traceability as one of the clinical research's most serious data problems [49]. Data accessibility Accessibility of patient data is another significant issue in the current clinical trials business since it includes several specialty parties and spans organizational and national lines. Participants in clinical trials operate in relative isolation, using their software systems, data formats, procedures, and organizations. Patient data are often spread across many private systems with no connection or collaboration, making it incredibly difficult to recruit participants for clinical studies [50]. Even worse, when scientists recruit enough patients to launch a clinical trial, patients' medical conditions for that particular therapy may continue to be a problem, resulting in flawed research with false positives and hazardous mistakes. 4 TAXONOMY OF BLOCKCHAIN TECHNOLOGY IN CLINICAL TRIALS This section overviews some essential characteristics that enable blockchain technology to transform conventional clinical trials. As shown in Figure 4, these characteristics are summarized and categorized into a tree-based structure according to existing literature. The taxonomy of blockchain technology in clinical trials comprises decentralized scenarios, decentralized practices, blockchain types, deployment methods, and consensus algorithms. The relevant literature in clinical trials analyzed in this section is summarized in Table 3. The conceptual diagram of the blockchain-based clinical trial platform is briefly presented in Figure 5. The physical layer consists of a variety of devices for gathering vital signals from patients. These devices allow for objectively measuring intervention effects in clinical and distant settings. The service layer's modular architecture makes the blockchain network easier to maintain and expand. This layer incorporates many properties of blockchain technology as separate modules, including P2P protocol, certificate authority, event hub, and consensus. The distributed ledger is a decentralized storage system for replicating and sharing data throughout the network. The smart contract specifies the business logic for all clinical trial-related processes, such as subject management. Various APIs encapsulate the functions defined in the smart contract. By contacting these APIs, other smart devices and apps could interface with the network. The application layer explains how the end user is presented with the blockchain's services. The user group consists of users with various responsibilities, such as the CRA, who may conduct audit inquiries on clinical trial data. The blockchain network is accessible through responsive web apps or native applications on mobile devices such as smartphones and tablets. The following sections explain each category in detail. FIGURE 4Open in figure viewerPowerPoint Taxonomy of blockchain technology in clinical trials TABLE 3. Summary of recent blockchain research in clinical trials Ref Description Benefits Research Challenges [51] -Use a generic model for the digitization of clinical trials -Assure data integrity and traceability -Preserve user's privacy N/A [53] -Public blockchain setting for clinical trial recruitment -Broadcast recruitment to all participating clinical sites and specific patients -Data visible to all users in the chain N/A [54] -Multiple smart contracts to regulate trial-related operations -Optimize the recruitment process N/A [55] -Combine blockchain with IoT technologies -Safeguard both the patients' and the Clinical Research Institute's interests N/A [56] -Explore the use of mobile computing and blockchain technology in participant recruitment and data sharing -Facilitate a patient-centred data stewardship model N/A [60] -Time step each stage throughout the patient's consent collection -Help with