Decentralized Clinical Trials and Opportunities with Artificial Intelligence

Swati Dhar
Parexel International LLC, Chicago, USA
Correspondence to: dharswat@gmail.com

DOI: https://doi.org/10.70389/PJAI.100008

Additional information

• Ethical approval: N/a
• Consent: N/a
• Funding: No industry funding
• Conflicts of interest: N/a
• Author contribution: Swati Dhar – Conceptualization, Writing – original draft, review and editing
• Guarantor: Swati Dhar
• Provenance and peer-review:
  Commissioned and externally peer-reviewed
• Data availability statement: N/a

Keywords: Decentralized clinical trials, Artificial intelligence in clinical trials, Blockchain technology in clinical trials, Patient recruitment and retention, Remote monitoring tools.

Peer Review
Received: 10 November 2024
Revised: 27 November 2024
Accepted: 2 December 2024
Published: 28 December 2024

Clinical Trials—Evolution, Current Models, and Limitations

Developing safe, efficient therapies and expanding medical knowledge depend heavily on clinical trials. Clinical trials are defined as human subjects’ research studies that evaluate the safety, effectiveness, and possible adverse effects of novel interventions, such as medications, surgeries, and behavioral therapies. These studies are subject to strict ethical and scientific regulations that are enforced by the U.S. Food and Drug Administration (FDA) and international health authorities.^1,2

Phases of Clinical Trials

• Phase I: This phase evaluates safety and dosing in a small group of healthy volunteers or patients.
• Phase II: Phase II trials involve more participants and focus on efficacy and side effects.
• Phase III: Phase III trials are larger and compare the new intervention against current standards or placebos. These trials often provide the evidence required for regulatory approval.
• Phase IV: Conducted post-approval, Phase IV trials gather information on long-term effectiveness, risks, and benefits in a larger, diverse population.

The goals and designs of clinical trials vary greatly, and each type has a specific function in the research and drug development process. Typical formats consist of the following.

Interventional Trials

These studies evaluate particular interventions on subjects, usually contrasting a novel treatment with an established standard or a placebo. One well-known example is randomized controlled trials (RCTs), in which participants are randomized to either the treatment or control groups to reduce bias and guarantee high validity.³

Observational Trials

Observational studies don’t use experimental therapies like interventional trials do. Over time, participants are observed by researchers, who gather unhindered data on particular health consequences. The long-term consequences of medicines, risk factors, and disease development are all better understood and attributed to these studies.⁴

Adaptive Trials

Adaptive trials modify key trial aspects (e.g., sample size, randomization) based on interim results. This flexible design can increase efficiency, speed, and the relevance of findings.⁵

Pragmatic Trials

Designed to evaluate effectiveness in real-world settings, pragmatic trials involve broad eligibility criteria and often have fewer restrictions, thereby offering insights into how treatments work in routine clinical practice.⁶ A clinical trial’s design is fundamental to its validity and scientific rigor. In addition to having different applications, benefits, and drawbacks, different designs also provide distinctive insights. The research topic, the goals of the study, and the trial’s practical limitations all play a role in choosing the best design. Here, some popular clinical trial designs and their advantages and disadvantages are discussed below.

Randomized Controlled Trials

Overview: Because of its reputation for reducing bias, RCTs are the gold standard in clinical research. The intervention under test or a control (such as a placebo or conventional treatment) is given to participants at random in an RCT. By reducing confounding variables, this randomization makes claims on causality more certain.⁷

Benefits

• Reduces Bias: Blinding and randomization lessen selection and observation biases, increasing the validity of findings.
• High Internal Validity: RCTs offer compelling proof that an intervention causes results.
• Regulatory Acceptance: Regulatory authorities generally accept RCTs as offering high-level evidence because of their meticulous design.⁸

Drawbacks

• Cost and Complexity: Conducting RCTs, particularly large, multicenter trials, can be costly and time-consuming.
• Ethical Restrictions: In extreme or life-threatening situations, it may be morally problematic to use a control group, which is typically a placebo.
• Limited Generalizability: RCT results may not transfer well to larger, real-world populations because of stringent eligibility requirements.⁹

Crossover Trials

To minimize carryover effects, participants in a crossover trial receive many therapies in a sequential order, separated by a “washout period.” This design enables each participant to act as their own control and is very helpful for researching therapies for chronic diseases.¹⁰

Benefits

• Decreased Variability: Crossover trials can lower variability and possibly need fewer participants by letting participants serve as their own controls.
• Effective Use of Resources: Compared to parallel RCTs, fewer participants and resources are frequently needed.

Drawbacks

• Risk of Carryover Effects: Results may be impacted by lingering effects from prior treatments, even during washout periods.
• Unsuitable for Some Conditions: In general, crossover trials are not useful for curative or acute therapies if the disease may alter over time.¹¹

Cluster-Randomized Trials

Overview: Rather than randomly assigning participants to groups, or “clusters,” cluster-randomized trials (CRTs) do so. For instance, it is possible to randomly assign different towns or hospitals to various interventions, which is especially helpful for public health initiatives.¹²

Benefits

• Effective for Group-Level Interventions: CRTs are perfect for organizational or community-level interventions.
• Minimizes Contamination: CRTs lessen the possibility of contamination between intervention and control groups by randomly assigning clusters.¹³

Drawbacks

• Complex Statistical Analysis: To take intra-cluster correlation into account, CRTs need certain statistical techniques.
• Greater Sample Size Requirements: Compared to individual randomization methods, CRTs may need a larger sample size in order to reach enough statistical power.

Adaptive Trials

Overview: Based on interim data analyses, adaptive trials are adaptable and permit changes to the trial’s protocols (such as sample size, dosage, or treatment groups). The goal of this strategy is to improve participant ethics and efficiency.¹⁴

Benefits

• Enhanced Efficiency: By permitting modifications in the middle of a study, adaptive designs can lead to quicker findings.
• Ethical Benefits: Ineffective treatments can be discontinued early, and more participants can benefit sooner if effective treatments are identified early.¹⁵

Drawbacks

• Risk of Bias: If not properly managed, frequent interim evaluations and adjustments raise the possibility of bias.
• Regulatory Complexity: Because adaptive trials are adaptable, they are subject to regulatory scrutiny, and trial design needs to be carefully pre-specified.¹⁶

Non-Inferiority Trials

Non-inferiority studies seek to ascertain whether a novel treatment is not, by a certain margin, inferior to an established treatment. When a placebo is unethical and the objective is to demonstrate that the novel intervention is “good enough,” this design is frequently employed.¹⁷

Benefits

• Non-inferiority trials, which do not employ a placebo, enable comparison to conventional treatments, making them ethical for severe conditions.
• Encourages Gradual Progress
• Beneficial for assessing therapies that might be simpler to administer or have fewer adverse effects.¹⁸

DrawbacksComplex Analysis

• It can be challenging to determine non-inferiority margins and understand findings.
• Risk of Misinterpretation
• Careful analysis is necessary to prevent drawing false conclusions, as results indicating non-inferiority may not imply that the treatment is superior.¹⁹

Clinical Trial Design—The Problems with RCTs

While RCTs are the gold standard in the world of clinical trials, much appreciated by the medical community and the regulatory agencies for their scientific rigor and statistical power accounting for reliable outcomes, the complexity of recruiting, retention, and conducting such studies due to cost, availability of defined study populations, and the inability to complete such studies within appreciable timelines are major hurdles. These impediments have enabled the development of “master protocols” or overarching studies that can spread across multiple interventional studies based on a defined biomarker or disease entity.^20,21 Master clinical protocols (MCPs) are novel trial designs that enable the assessment of several diseases, therapies, or subpopulations characterized by biomarkers under a single overall study framework. With the emergence of customized medicine, MCPs provide a strong foundation for effectively addressing challenging research topics. Platform, umbrella, and basket trials are the three main categories of master protocols; each is designed to meet particular research goals and target audiences.

Umbrella Trials

These studies concentrate on a particular disease or health condition while investigating several targeted treatments depending on subpopulations within that illness that have been identified by biomarkers. Because molecular profiling can reveal unique genetic variants within a single cancer type, this design is very common in oncology.²²

Benefits

• Precision Medicine: Targeted therapy research is supported by umbrella studies that match medications to certain biomarkers within a disease, improving therapeutic efficacy and minimizing needless exposure to unsuccessful treatments.²³
• Operational Efficiency: By testing several treatments in a single trial infrastructure, resources can be streamlined and fewer trials are required.²⁴

Drawbacks

• Complex Design and Analysis: Managing several treatment arms and subgroups calls for intricate statistical analysis and trial design.
• Recruitment Challenges: Biomarker-based subgrouping can limit eligible participants, especially if the biomarker is rare, potentially prolonging trial recruitment timelines.²⁵

Basket Trials

Overview: Basket trials assess a single treatment for a number of illnesses or ailments, usually those that have a common genetic mutation or biomarker. Basket studies, as opposed to umbrella trials, evaluate a single medicine across several indications by concentrating on a therapeutic target rather than a particular illness.²⁶

Benefits

• Broad Applicability: When a mutation or biomarker is present in several malignancies or disease states, basket trials can be very helpful for rare diseases or disorders.
• Improved Access: Basket studies offer therapy access to a variety of patient groups by enrolling individuals from many disease areas with a shared biomarker, which may hasten patient accrual.²⁷

Disadvantages

• Heterogeneity of Diseases: Differences in disease biology between indications may lead to variable treatment responses, complicating data interpretation.
• Limited Generalizability: A positive result in one subset of a basket trial may not generalize to all indications, particularly if disease mechanisms differ.

Platform Trials

Overview: Platform studies allow for the addition or removal of treatment arms in response to interim data, and they assess several medicines for a single condition. In an ongoing, eternal study structure, this adaptive design enables researchers to effectively evaluate several experimental medicines versus a control group or standard-of-care.²⁸

Benefits

• Adaptive Flexibility: Platform trials allow treatment arms to be added or removed with ease, keeping the trial up to date and in line with new scientific findings.²⁹
• Enhanced Efficiency and Cost Savings: By avoiding the need for different trial setups, sharing infrastructure and control groups across many arms lowers the overall cost and time needed to test new medicines.³⁰

Drawbacks

Statistical and Regulatory Complexity: Because platform trials are adaptive, they are subject to extra regulatory scrutiny and need careful statistical preparation to account for Type I error across several treatment comparisons.³¹

Risk of Resource Burden: Although effective, the intricacy of overseeing several concurrent arms may present logistical and operational difficulties, particularly when it comes to synchronizing data among several treatment groups.

Benefits of Master Protocols

• Accelerated Drug Development: MCPs are made to speed up testing and development by enabling researchers to assess several interventions or targets in a single framework, which reduces recovery time^.32
• Optimized Resource Use: MCPs reduce resource costs and increase data gathering by utilizing centralized trial infrastructure and shared control groups, which is especially advantageous in rare diseases or small patient populations.^33,34
• Benefits for Ethics: MCPs eliminate the need for numerous control groups, which may expose fewer individuals to placebo. This is particularly helpful for critical illnesses for which there are few effective treatments.³⁵

General Drawbacks of Master Protocols

• Complexity and Setup Cost: While MCPs can save resources once they’re up and running, they require complex statistical frameworks, biomarker testing, and trial designs, which can raise setup costs.
• Difficulties in Interpreting Data: Using several arms, biomarkers, or illnesses in a single procedure might make statistical analysis more difficult and necessitate sophisticated approaches to properly interpret the results.
• Enhanced Regulatory Scrutiny: Because of their unique structure and adaptability, MCPs are frequently the focus of thorough regulatory review, which may cause delays in the start of studies and the need for continuing management.

Limitations and Drawbacks of Traditional Clinical Trials

Time and Cost: Clinical trials, particularly Phase III studies, are time-consuming and costly procedures that can take years to finish. These temporal and financial ­constraints frequently limit access and postpone the release of promising therapies by limiting trial participation to well-funded institutions or organizations.³⁶

Patient Recruitment and Retention: It might be difficult to find and keep participants, especially in uncommon conditions where there are fewer eligible patients. Furthermore, the rigorous character of certain studies may cause participant dropouts, which may compromise statistical power and the reliability of results.³⁷

Risk and Ethical Issues: It might be difficult to strike a balance between scientific rigor and ethical issues in trials when volunteers might get placebos or suffer negative side effects. Withholding potentially beneficial therapies raises ethical concerns, especially in life-threatening illnesses.³⁸

Generalizability: The fact that many clinical trials are carried out in well-regulated environments with stringent inclusion and exclusion standards may restrict their applicability to populations in the real world. Although pragmatic trial designs are still uncommon, this constraint has encouraged their usage.³⁹

Risk of Bias and Confounding: Even with randomization, confounding variables can still affect some trials, especially in observational research. Furthermore, the medical literature may still be skewed by publication bias, which occurs when only good results are reported.⁴⁰

Some solutions to existing issues with traditional clinical trials can be addressed by DCTs.

DCTs and Their Modalities

Clinical investigations carried out fully or in part outside of conventional research facilities are known as decentralized clinical trials, or DCTs. DCTs use remote technology and resources to engage participants wherever they are, in contrast to traditional clinical trials that typically require participants to travel to a central location (such as a hospital or clinical research facility) for each study-related activity.⁴¹ This change is intended to facilitate real-world, continuous data gathering, ease logistical difficulties, and make participation simpler and more accessible (Figure 1).

Important Elements of DCTs

DCTs usually use a number of cutting-edge techniques to interact with participants and collect data, such as:

• Telemedicine and Virtual Visits: Study staff can communicate with participants remotely for enrollment, follow-up, and even some assessments using video calls or phone consultations.
• Wearable Sensors and Devices: Wearable sensors and devices such as heart rate monitors, glucose meters, and fitness trackers can automatically record health data. This eliminates the need for in-person visits by enabling researchers to collect continuous, real-time data on participants’ vital signs, physical activity, and other metrics.
• Mobile Health Apps and Electronic Patient-Reported Outcomes (ePROs): Using a smartphone or other electronic device, participants can record their own data, report symptoms, and respond to questionnaires through mobile apps and ePROs.
• Home Health Services: Mobile health professionals can come to research participants’ homes to conduct physical examinations, take blood samples, or give study drugs.
• Direct-to-Patient Drug Delivery: Instead of requiring participants to come to the trial location for every dose or cycle, medications or other study-related materials are frequently sent straight to their homes.

Benefits of DCTs

The DCT approach has several benefits.

• Enhanced Accessibility: People from a variety of social, economic, and geographic backgrounds can participate more easily in DCTs since they eliminate the need for travel and in-person visits. Higher levels of satisfaction and reduced dropout rates are frequently the results of allowing patients to participate in studies with less interference with their daily life.
• Cost and Time Efficiency: DCTs can speed up participant recruiting and trial execution while lowering the administrative and logistical expenses related to physical facilities.
• Real-World Data Gathering: Ongoing, remote data gathering offers significant information about how therapies function in actual settings, which is crucial for assessing lifestyle impacts and long-term effects.

Challenges of DCTs

Notwithstanding their advantages, DCTs have some drawbacks.

• Data Security and Privacy: As our reliance on digital tools grows, safeguarding patient information and upholding confidentiality become crucial issues. Digital literacy and access to dependable internet are prerequisites for participation, as is the ability to use digital platforms, which can be difficult for some groups to access.
• Regulatory and Compliance Issues: As it relates to data accuracy, patient safety, and the legitimacy of remotely gathered data, regulatory bodies are still modifying their rules to allow DCTs.
• Data Integration and Quality: It can be difficult for researchers to manage massive amounts of data from several sources (such as wearables, ePROs, and electronic health records (EHRs)) while maintaining consistent quality and interoperability.

Table 1 summarizes some of the DCTs currently listed on clinicaltrials.gov.

Table 1:   A detailed summary and current status of some of the DCTs currently listed on clinicaltrials.gov.
NCT Number	Study Title	Study URL	Study Status	Conditions	Interventions	Sponsor	Collaborators	Study Type
NCT06609174	AI-SCREENDCM Decentralized Clinical Trial—Pilot Study	https://clinicaltrials.gov/study/NCT06609174	NOT_YET_RECRUITING	Cardiomyopathy	DIAGNOSTIC_TEST: KardiaRx ECG Screening	Mayo Clinic		INTERVENTIONAL
NCT05419869	Pilot Decentralized Trial	https://clinicaltrials.gov/study/NCT05419869	COMPLETED	Major Depressive Disorder	DRUG: ALTO-100 PO Tablet	Alto Neuroscience		INTERVENTIONAL
NCT04471623	Decentralized Trial in Atrial Fibrillation Patients	https://clinicaltrials.gov/study/NCT04471623	COMPLETED	Atrial Fibrillation	BEHAVIORAL: Use of DeTAP App and Home Devices	Stanford University		INTERVENTIONAL
NCT02357537	Decentralized Dietary UC Pilot Trial	https://clinicaltrials.gov/study/NCT02357537	UNKNOWN	Colitis, Ulcerative	BEHAVIORAL: Combined Anti-inflammatory Diet (CAID)	Transparency Life Sciences		INTERVENTIONAL
NCT04701177	Digitally-enhanced, Decentralized, Multi-omics Observational Cohort	https://clinicaltrials.gov/study/NCT04701177	ENROLLING_BY_INVITATION	Presymptomatic Disease, Mild Cognitive Impairment, Memory Loss (Excluding Dementia), Cognitive Change, Dementia, Alzheimer Disease, Parkinson’s Disease and Parkinsonism	DIAGNOSTIC_TEST: AltoidaML	Greece 2021 Committee	Ionian University, Greek Alzheimer’s Association and Related Disorders	OBSERVATIONAL
NCT06587204	Understanding Decentralized Trial Engagement and Clinical Impediments Through Digital Efforts (UDECIDE) Among Unrepresented Groups with Poor Cardiovascular and Cardiometabolic Health	https://clinicaltrials.gov/study/NCT06587204	NOT_YET_RECRUITING	Heart Diseases	OTHER: Control Group, BEHAVIORAL: Decentralized Group, BEHAVIORAL: Digital Literacy Navigation Group, BEHAVIORAL: Social Care Navigation Group	University of Miami		INTERVENTIONAL
NCT06005805	A Study To Evaluate the Feasibility of the Decentralized Clinical Trial in South Korea	https://clinicaltrials.gov/study/NCT06005805	COMPLETED	Functional Dyspepsia	DIETARY_SUPPLEMENT: Mastic gum, BEHAVIORAL: Dietary modification	Seoul National University Hospital		INTERVENTIONAL
NCT05801731	A Decentralized Study on Dietary Influences on Cognitive Functions	https://clinicaltrials.gov/study/NCT05801731	COMPLETED	Glucose Metabolism, Cognitive Function	OTHER: Intervention, OTHER: Control	Institute for Human Development and Potential (IHDP), Singapore		INTERVENTIONAL
NCT04862143	Pilot Decentralized Clinical Trial in Men and Pre and Post-menopausal Women With Breast Cancer and a Specific Mutation (PIK3CA) Treated With Alpelisib in Combination With Fulvestrant	https://clinicaltrials.gov/study/NCT04862143	TERMINATED	Advanced Breast Cancer	DRUG: Alpelisib, DRUG: Fulvestrant, DRUG: Goserelin	Novartis Pharmaceuticals		INTERVENTIONAL
NCT06262113	A Decentralized Clinical Trial to Promote Evidence-Based Care for Underserved Patients With Neurofibromatosis 1	https://clinicaltrials.gov/study/NCT06262113	NOT_YET_RECRUITING	Neurofibromatosis 1	OTHER: Letters about NF1 Care (Content Type 1), OTHER: Letters about NF1 Care (Content Type 2)	Massachusetts General Hospital	Patient-Centered Outcomes Research Institute	INTERVENTIONAL
NCT06507566	Evaluating Technologies for Point-of-Care Blood Collections by Patients	https://clinicaltrials.gov/study/NCT06507566	RECRUITING	Healthy	DEVICE: Tasso+â,¢	Resilience Government Services, Inc.	ICON Government and Public Health Solutions, Inc, Joint Program Executive Office Chemical, Biological, Radiological, and Nuclear Defense Enabling Biotechnologies	INTERVENTIONAL
NCT06240754	Enasidenib for Patients With Clonal Cytopenia of Undetermined Significance and Mutations in IDH2A Decentralized Trial	https://clinicaltrials.gov/study/NCT06240754	RECRUITING	Clonal Cytopenia of Undetermined Significance, CCUS Clonal Cytopenia of Undetermined Significance	DRUG: Enasidenib	Washington University School of Medicine	Bristol-Myers Squibb, Damon Runyon Cancer Research Foundation	INTERVENTIONAL
NCT06374043	Decentralized N = 1 Study: A Feasible Approach to Evaluate Individual Therapy Response to Dapagliflozin.	https://clinicaltrials.gov/study/NCT06374043	COMPLETED	Diabetes Mellitus, Type 2, Diabetes Mellitus Type 2 With Proteinuria, Diabetes Mellitus, Diabetes, Diabetes Complications, Albuminuria, Chronic Kidney Diseases, Chronic Kidney Disease, Due to Type 2 Diabetes Mellitus, CKD, Proteinuria	DRUG: Dapagliflozin 10 mg Tab, DRUG: Placebo, DEVICE: Withings BPM Connect, DEVICE: Withings Body+, DIAGNOSTIC_TEST: Hem-Col Capillary Blood Collection Device, DEVICE: MEMS (Medication Electronic Monitoring System) Cap, BEHAVIORAL: Questionnaire: participants’ perspectives toward remote data collection	University Medical Center Groningen	AstraZeneca	INTERVENTIONAL
NCT04748445	Acute Respiratory Illness Surveillance (AcRIS) With Mobile Application in a Low-Interventional Decentralized Study.	https://clinicaltrials.gov/study/NCT04748445	COMPLETED	Healthy	DIAGNOSTIC_TEST: SARS-CoV-2/Influenza/RSV RT-PCR	Pfizer		OBSERVATIONAL
NCT05432466	Clinical Trial to Compare the Efficacy of Celiprolol to Placebo in Patients With Vascular Ehlers-Danlos Syndrome	https://clinicaltrials.gov/study/NCT05432466	RECRUITING	Vascular Ehlers-Danlos Syndrome	DRUG: ACER-002 (celiprolol) 200 mg BID, DRUG: Placebo BID	Acer Therapeutics Inc.		INTERVENTIONAL
NCT04325464	A Remote, 9-week Insomnia Treatment Trial to Collect Real World Data for a Digital Therapeutic	https://clinicaltrials.gov/study/NCT04325464	ACTIVE_NOT_RECRUITING	Chronic Insomnia	DEVICE: PEAR-003A	Pear Therapeutics, Inc.		INTERVENTIONAL
NCT05047016	Study to Evaluate the Dynamic Consent Model Based on the Blockchain-based Clinical Trial Platform METORY	https://clinicaltrials.gov/study/NCT05047016	UNKNOWN	COVID-19 Pneumonia	OTHER: Virtual investigational product	Seoul National University Hospital		INTERVENTIONAL
NCT05340309	Subcutaneous Atezolizumab for the Treatment of Non-small Cell Lung Cancer	https://clinicaltrials.gov/study/NCT05340309	RECRUITING	Lung Non-Small Cell Carcinoma, Stage II Lung Cancer AJCC v8, Stage IIA Lung Cancer AJCC v8, Stage IIB Lung Cancer AJCC v8, Stage III Lung Cancer AJCC v8, Stage IIIA Lung Cancer AJCC v8, Stage IIIB Lung Cancer AJCC v8, Stage IIIC Lung Cancer AJCC v8, Stage IV Lung Cancer AJCC v8, Stage IVA Lung Cancer AJCC v8, Stage IVB Lung Cancer AJCC v8	BIOLOGICAL: Atezolizumab and Recombinant Human Hyaluronidase, OTHER: Survey Administration	University of Southern California	National Cancer Institute (NCI), Genentech, Inc.	INTERVENTIONAL
NCT04885803	Vitamin D Absorbance Study—Clinical Trial of the Absorbance of Nano Liquid D3	https://clinicaltrials.gov/study/NCT04885803	COMPLETED	Vitamin D Deficiency	DIETARY_SUPPLEMENT: Softgel Vitamin D3, DIETARY_SUPPLEMENT: Nano Liquid Vitamin D3, DIAGNOSTIC_TEST: 25(OH)D Blood Serum Test, OTHER: Placebo Control	Inspired Life Medical, Inc.		INTERVENTIONAL
NCT02832063	Clinical Trial in Subjects With Mild to Moderate Acne Vulgaris	https://clinicaltrials.gov/study/NCT02832063	COMPLETED	Acne Vulgaris	BIOLOGICAL: B244, BIOLOGICAL: Placebo	AOBiome LLC		INTERVENTIONAL
NCT00554567	Utilization of HIV Clinical Services in Rural India	https://clinicaltrials.gov/study/NCT00554567	COMPLETED	HIV Infections, Sexually Transmitted Infections	BEHAVIORAL: HIV Testing and Care Services	Institute of Health Management, Pachod, India	Johns Hopkins University	INTERVENTIONAL
NCT05377242	Curcumin, Resveratrol, and Stinging Nettle as Treatments for GWI	https://clinicaltrials.gov/study/NCT05377242	RECRUITING	Gulf War Illness	DIETARY_SUPPLEMENT: Curcumin, DIETARY_SUPPLEMENT: Resveratrol, DIETARY_SUPPLEMENT: Stinging Nettle	University of Alabama at Birmingham	Congressionally Directed Medical Research Programs	INTERVENTIONAL
NCT05891197	A Biomarker Screening Protocol for Participants With Solid Tumors	https://clinicaltrials.gov/study/NCT05891197	RECRUITING	Triple Negative Breast Cancer, Non-small Cell Lung Cancer, Non Small Cell Lung Cancer, Non Small Cell Lung Cancer Metastatic, Non-Small Cell Carcinoma of Lung, TNM Stage 4, Advanced Breast Cancer, Advanced Lung Carcinoma, NSCLC, NSCLC, Recurrent, NSCLC Stage IV, Relapsed Cancer, Relapse/Recurrence, Recurrent Breast Cancer, Recurrent NSCLC, Platinum-resistant Ovarian Cancer, Ovarian Cancer, Primary Peritoneal Carcinoma, Fallopian Tube Cancer, Endometrial Cancer, Endometrioid Tumor, High Grade Serous Carcinoma, Ovarian Epithelial Cancer		Lyell Immunopharma, Inc.	ICON plc	OBSERVATIONAL
NCT06306300	Safety and Efficacy of Decentralized HCV Treatment vs Standard-of-Care in Rio de Janeiro (Brazil)	https://clinicaltrials.gov/study/NCT06306300	RECRUITING	Hepatitis C	DRUG: Specialist—Epclusa 400 Mg–100 Mg Tablet, DRUG: Non-specialist—Epclusa 400 Mg–100 Mg Tablet	Oswaldo Cruz Foundation	Conselho Nacional de Desenvolvimento CientÃfico e Tecnológico	INTERVENTIONAL
NCT05520073	A Pilot Study to Evaluate the Effects of Lactobacillus Supplements	https://clinicaltrials.gov/study/NCT05520073	COMPLETED	Feasibility Studies	DIETARY_SUPPLEMENT: Lactobacillus plantarum, DIETARY_SUPPLEMENT: Vitamin C	Seoul National University Hospital		INTERVENTIONAL
NCT06346886	HTN App for HTN Control and Cardiovascular Health Among African-Americans	https://clinicaltrials.gov/study/NCT06346886	NOT_YET_RECRUITING	Hypertension	BEHAVIORAL: FAITH! HTN app	Mayo Clinic	Miami Heart Research Institute Inc.	INTERVENTIONAL
NCT06185985	Open-label Safety and Efficacy of SPN-812 (Viloxazine Extended-release Capsule) in Adults With ADHD and Mood Symptoms	https://clinicaltrials.gov/study/NCT06185985	RECRUITING	Attention-Deficit/Hyperactivity Disorder	DRUG: SPN-812	Supernus Pharmaceuticals, Inc.		INTERVENTIONAL
NCT06324110	Evaluating the Impact of Centralized Interventions on Lung Cancer Screening Adherence in Community Settings, ACCELL Trial	https://clinicaltrials.gov/study/NCT06324110	ENROLLING_BY_INVITATION	Lung Carcinoma	OTHER: Electronic Health Record Review, OTHER: Interview, BEHAVIORAL: Patient Navigation	Fred Hutchinson Cancer Center	National Cancer Institute (NCI)	INTERVENTIONAL
NCT05946551	Treatment of Long CoronaVirus Disease (COVID) (TLC) Feasibility Trial	https://clinicaltrials.gov/study/NCT05946551	TERMINATED	COVID-19	DRUG: Cetirizine, DRUG: Famotidine, DRUG: Cetirizine Placebo, DRUG: Famotidine Placebo	Emory University	CURE Drug Repurposing Collaboratory (CDRC)	INTERVENTIONAL
NCT05349019	A Natural History Study of Patients With G2019S LRRK2 Parkinson’s Disease	https://clinicaltrials.gov/study/NCT05349019	TERMINATED	Patients With Parkinson’s Disease (PD) Caused by the p.Gly2019Ser (G2019S) Pathogenic Mutation of the Leucine-Rich Repeat Kinase 2 (LRRK2) Gene	OTHER: Observational	Escape Bio, Inc.	Momentum Pharma, Science 37	OBSERVATIONAL
NCT06157099	Atorvastatin for Preventing Disease Metastasis in Patients With Resected High-Risk Stage IIA, IIB, or IIIA Melanoma	https://clinicaltrials.gov/study/NCT06157099	RECRUITING	Clinical Stage IIA Cutaneous Melanoma AJCC v8, Clinical Stage IIB Cutaneous Melanoma AJCC v8, Pathologic Stage IIIA Cutaneous Melanoma AJCC v8	DRUG: Atorvastatin, DRUG: Placebo  Administration, PROCEDURE: Computed Tomography, PROCEDURE: Magnetic Resonance Imaging, OTHER: Electronic Health Record Review	OHSU Knight Cancer Institute	Oregon Health and Science University, Kuni Foundation	INTERVENTIONAL
NCT05510934	Shared Care Thyroid Cancer Follow-up Utilizing Thyroid Cancer Assessment Reminder System (TCARS) Study—A Pilot Study.	https://clinicaltrials.gov/study/NCT05510934	RECRUITING	Low-Risk Differentiated Thyroid Cancer	BEHAVIORAL: Shared-care Model	Nova Scotia Health Authority		OBSERVATIONAL
NCT00124085	Asthma in a Decentralized Patient Population: Is Traditional Disease Management Enough?	https://clinicaltrials.gov/study/NCT00124085	COMPLETED	Asthma	BEHAVIORAL: Disease Management, BEHAVIORAL: Disease Management + Educational Home Visits	The University of Texas Health Science Center at San Antonio	South Texas Veterans Health Care System, Brooke Army Medical Center, 59th Medical Wing, TRICARE Southwest, Department of Health and Human Services, Centers for Disease Control and Prevention	INTERVENTIONAL
NCT06567717	Zinc and Nicotinamide Riboside for Idiopathic Pulmonary Fibrosis	https://clinicaltrials.gov/study/NCT06567717	NOT_YET_RECRUITING	Idiopathic Pulmonary Fibrosis	DRUG: Zinc, OTHER: Placebos for Zinc and Nicotinamide riboside, DRUG: Nicotinamide riboside	Cedars-Sinai Medical Center		INTERVENTIONAL
NCT05585827	Online Cognitive Behavioral Therapy for Depressive Symptoms in Parkinson’s Disease	https://clinicaltrials.gov/study/NCT05585827	RECRUITING	Parkinson Disease, Depressive Symptoms, Anxiety	BEHAVIORAL: Online Cognitive Behavioral Therapy	Helse Stavanger HF		INTERVENTIONAL
NCT04923464	A Decentralized Study to Evaluate Physical Activity and Cough Frequency Using Wearable Technology in Cystic Fibrosis	https://clinicaltrials.gov/study/NCT04923464	COMPLETED	Cystic Fibrosis		Vertex Pharmaceuticals Incorporated		OBSERVATIONAL
NCT06397651	A Randomised Controlled Trial to Evaluate the Impact of Complement Theory’s Live 1:1 Exercise Coaching and Personalised Digital Application on Cancer Survivors’ Cost of Care	https://clinicaltrials.gov/study/NCT06397651	RECRUITING	Breast Cancer, Lung Cancer, Prostate Cancer, Colorectal Cancer, Other Cancer	BEHAVIORAL: Complement Theory’s Live 1:1 Exercise Coaching and Personalized Digital Application, BEHAVIORAL: Digital Application with Expert Guidelines on Lifestyle Modification	Complement Theory Inc.		INTERVENTIONAL
NCT02979756	Improve Detection and Management of Gestational Diabetes Through the Primary Health Care Level in Morocco	https://clinicaltrials.gov/study/NCT02979756	COMPLETED	Gestational Diabetes Mellitus in Pregnancy	PROCEDURE: Decentralized GDM Screening and Initial Management	Institute of Tropical Medicine, Belgium	Ecole Nationale de Santé Publique, Rabat, Morocco	INTERVENTIONAL
NCT02420132	Study to Evaluate Home Vision Testing in Participants Who Receive Ranibizumab (Lucentis®)	https://clinicaltrials.gov/study/NCT02420132	COMPLETED	Macular Edema, Macular Degeneration	OTHER: Ranibizumab	Hoffmann-La Roche		OBSERVATIONAL
NCT05668091	A Decentralized, Randomized Phase 2 Efficacy and Safety Study of Nirmatrelvir/Ritonavir in Adults with Long COVID	https://clinicaltrials.gov/study/NCT05668091	COMPLETED	Long COVID	DRUG: Nirmatrelvir, DRUG: Ritonavir, DRUG: Placebo	Harlan M Krumholz	Pfizer	INTERVENTIONAL
NCT05263037	EaseVRx-8w+ for the Treatment of Chronic Lower Back Pain	https://clinicaltrials.gov/study/NCT05263037	ACTIVE_NOT_RECRUITING	Chronic Low-back Pain, Anxiety, Depression	DEVICE: EaseVRx, DEVICE: Sham VR	AppliedVR Inc.		INTERVENTIONAL
NCT05686369	A Decentralized Home-Based Study To Investigate Novel Objective Biomarker Of Gluten-Mediated Symptoms In Celiac Disease Participants (CeDar ROSE Study)	https://clinicaltrials.gov/study/NCT05686369	COMPLETED	Celiac Disease		Chugai Pharmaceutical		OBSERVATIONAL
NCT06094920	Treatment Optimization for Patients With Type 2 Diabetes Using Empagliflozin and Finerenone in a Remote Clinical Trial	https://clinicaltrials.gov/study/NCT06094920	ENROLLING_BY_INVITATION	Diabetes Mellitus Type 2 With Proteinuria, Diabetes Mellitus, Type 2, Diabetes Mellitus, Diabetes, Diabetes Complications, Albuminuria, Chronic Kidney Diseases, Chronic Kidney Disease Due to Type 2 Diabetes Mellitus, Chronic Kidney Disease stage 3, Chronic Kidney Disease stage 4, CKD, CKD Stage 3, CKD Stage 4	DRUG: Empagliflozin 10 MG, DRUG: Finerenone, DEVICE: Withings BPM Connect, DEVICE: Withings Body, DIAGNOSTIC_TEST: PeeSpot Urine Collection Device, DIAGNOSTIC_TEST: Hem-Col Capillary Blood Collection Device, BEHAVIORAL: Questionnaire: participants’ perspectives toward the feasibility of participation in a trial at home with digital technologies	University Medical Center Groningen	Boehringer Ingelheim	INTERVENTIONAL
NCT06618417	Evaluating the Impact of Home-Based Sleep Apnea Diagnostic on Well-Being, Health Behavior, and AF Load in Patients with Atrial Fibrillation Using a Decentralized Platform	https://clinicaltrials.gov/study/NCT06618417	NOT_YET_RECRUITING	Atrial Fibrillation (AF), Sleep Apnea	DEVICE: sleep apnea home-evaluation	Herlev and Gentofte Hospital		INTERVENTIONAL
NCT06115590	Novel Objective Digital Biomarkers for Assessing Sub-clinical Mood Disturbances in the Singaporean Population	https://clinicaltrials.gov/study/NCT06115590	COMPLETED	Mood	DIETARY_SUPPLEMENT: Nutritional supplement	Institute for Human Development and Potential (IHDP), Singapore	OBVIO HEALTH USA, Inc.	INTERVENTIONAL
NCT04584645	A Digital Flu Intervention for People With Cardiovascular Conditions	https://clinicaltrials.gov/study/NCT04584645	COMPLETED	Cardiovascular Diseases, Atrial Fibrillation, Abnormal Heart Rhythms, Cardiac Arrest, Heart Attack, Myocardial Infarction, Coronary Heart Disease, Heart Failure, Stroke, Cerebrovascular Accident	OTHER: Targeted Digital Intervention	Evidation Health	Sanofi Pasteur, a Sanofi Company	INTERVENTIONAL
NCT05775510	Study to Evaluate Neuromodulation Subject Experience With Contemporary Spinal Cord Stimulation (SCS) Modalities for Chronic Pain	https://clinicaltrials.gov/study/NCT05775510	RECRUITING	Pain, Intractable, Pain, Chronic	DEVICE: Commercially Available Neurostimulation Systems	MedtronicNeuro		OBSERVATIONAL
NCT06188247	Pilot-trial Testing Remote Sleep Apnea Evaluation in Patients With Atrial Fibrillation	https://clinicaltrials.gov/study/NCT06188247	RECRUITING	Atrial Fibrillation, Sleep Apnea	DEVICE: NightOwl Home-monitoring	Herlev and Gentofte Hospital		INTERVENTIONAL
NCT05575843	Neurostatus-SMARTCARE in Comparison to Standard Neurostatus-EDSS®	https://clinicaltrials.gov/study/NCT05575843	COMPLETED	Multiple Sclerosis (MS)	OTHER: Neurostatus-SMARTCARE, OTHER: Standard Neurostatus-EDSS	University Hospital, Basel, Switzerland	Novartis Pharma AG, Basel, Switzerland	INTERVENTIONAL
NCT06486428	Small Cell Lung Cancer Community Engagement to Eliminate Research Disparities	https://clinicaltrials.gov/study/NCT06486428	NOT_YET_RECRUITING	Small-cell Lung Cancer		Addario Lung Cancer Medical Institute		OBSERVATIONAL
NCT05166525	Kaiser Permanente Evaluation of Medically Tailored Meals in Adults With Medical Conditions at High Readmission Risk	https://clinicaltrials.gov/study/NCT05166525	COMPLETED	Heart Failure, Chronic Kidney Diseases, Diabetes Mellitus, Type 2	OTHER: Medically tailored meals	Kaiser Permanente		INTERVENTIONAL
NCT06051539	Outcomes and Health Economics of Stroke Using Rhythmic Auditory Stimulation	https://clinicaltrials.gov/study/NCT06051539	RECRUITING	Chronic Stroke	DEVICE: MR-001	MedRhythms, Inc.		INTERVENTIONAL
NCT06312059	Goat or Cow Milk Based Infant Formula GMS	https://clinicaltrials.gov/study/NCT06312059	RECRUITING	Growth	OTHER: Advance Infant Formula Powder, OTHER: “Kendamil Cow milk test product, OTHER:” Kendamil Goat Milk Test Product	Kendal Nutricare Ltd	ObvioHealth	INTERVENTIONAL
NCT06505590	STEpwise Research Program to Promote INGeniouS ONline Supportive Solutions in the Relief of Cancer-related Fatigue (STEPPING-STONe)	https://clinicaltrials.gov/study/NCT06505590	NOT_YET_RECRUITING	Cancer Diagnosis, Moderate or Severe Score of Cancer-related Fatigue (CRF)	DEVICE: Educational Content DEVICE: Educational Material Plus Self-management Program—Self-administered Version, DEVICE: Educational Material Plus Self-management Program—Guided Version with Mental Health Professional	Gustave Roussy, Cancer Campus, Grand Paris	University Hospital, Bordeaux, Institut Bergonié	INTERVENTIONAL
NCT04983017	2021 PMT iAge® Intervention Trial by Edifice Health	https://clinicaltrials.gov/study/NCT04983017	TERMINATED	Chronic Inflammation, Inflammaging	DIETARY_SUPPLEMENT: Dietary Supplement, OTHER: Placebo	Edifice Health		INTERVENTIONAL
NCT05505734	A Comparison of PT027 vs PT007 Used as Needed in Participants With Asthma	https://clinicaltrials.gov/study/NCT05505734	COMPLETED	Asthma	DRUG: BDA MDI, DRUG: AS MDI	Bond Avillion 2 Development LP	Parexel	INTERVENTIONAL
NCT05030441	Ivosidenib for Patients With Clonal Cytopenia of Undetermined Significance and Mutations in IDH1	https://clinicaltrials.gov/study/NCT05030441	RECRUITING	Clonal Cytopenia of Undetermined Significance	DRUG: Ivosidenib	Washington University School of Medicine	Servier Hellas Pharmaceuticals Ltd., Gateway for Cancer Research	INTERVENTIONAL
NCT05725525	A Study of Internet Delivered Parent Child Interaction Therapy	https://clinicaltrials.gov/study/NCT05725525	COMPLETED	Disruptive Behavior	BEHAVIORAL: Remote PCIT Augmented with Wearable Devices	Mayo Clinic		INTERVENTIONAL
NCT04866810	The Effect of Diet and Exercise on ImmuNotherapy and the Microbiome (EDEN)	https://clinicaltrials.gov/study/NCT04866810	RECRUITING	Melanoma	BEHAVIORAL: Intervention Arm, BEHAVIORAL: Control	National Cancer Institute (NCI)		INTERVENTIONAL
NCT06441617	Confirmatory Trial for Alleviating Fatigue in Multiple Sclerosis	https://clinicaltrials.gov/study/NCT06441617	NOT_YET_RECRUITING	Multiple Sclerosis, Fatigue	DEVICE: Online Therapy for Fatigue	Accelerated Cure Project for Multiple Sclerosis	Congressionally Directed Medical Research Programs, United States Department of Defense, Charite University, Berlin, Germany, University Medical Center Goettingen, US Department of Veterans Affairs	INTERVENTIONAL
NCT06439238	Feasibility of Conducting a Pilot Telehealth Study Assessing the Removal of Filter Ventilation on Smoking Behavior and Biomarkers in Menthol Smokers Switched to Non-menthol Cigarettes	https://clinicaltrials.gov/study/NCT06439238	RECRUITING	Smoking	OTHER: Ventilated Non-menthol Cigarettes, OTHER: Minimally Ventilated Non-menthol Cigarettes	University of Minnesota		INTERVENTIONAL
NCT05531019	COVID-19 Sequelae: Treatment and Monitoring. A Dietary Supplement Based on Sea Urchin Eggs With Echinochroma A	https://clinicaltrials.gov/study/NCT05531019	COMPLETED	Long COVID	DIETARY_SUPPLEMENT: Echinochrome A, OTHER: Control	Fernando Saldarini	Universidad Nacional de la Patagonia San Juan Bosco, Ministerio de Ciencia, Tecnologia e Innovación, Argentina, Hospital de Infecciosas Francisco Javier Muniz	INTERVENTIONAL
NCT06218459	A Comparison of Two Brief Interventions for People With Chronic Low Back Pain	https://clinicaltrials.gov/study/NCT06218459	RECRUITING	Low Back Pain	OTHER: Oldpain2go®, OTHER: Jacobson’s progressive relaxation	Teesside University	Norton Physiotherapy, Newcastle University	INTERVENTIONAL
NCT03500172	HIV Treatment Retention Interventions for Women Living With HIV (Siyaphambili Study)	https://clinicaltrials.gov/study/NCT03500172	COMPLETED	HIV-1 Virologic Response	BEHAVIORAL: DTP, BEHAVIORAL: ICM	Johns Hopkins Bloomberg School of Public Health	University of the Western Cape, TB/HIV Care, University of Toronto, University of California, San Francisco, National Institute for Communicable Diseases, South Africa	INTERVENTIONAL
NCT06348147	Dara-RVd Induction for Newly Diagnosed Multiple Myeloma With Autologous Stem Cell Transplantation	https://clinicaltrials.gov/study/NCT06348147	NOT_YET_RECRUITING	Newly Diagnosed Multiple Myeloma, Multiple Myeloma, Autologous Stem Cell Transplantation	BIOLOGICAL: Daratumumab, DRUG: Lenalidomide, DRUG: Bortezomib, DRUG: Dexamethasone	UNC Lineberger Comprehensive Cancer Center		INTERVENTIONAL
NCT06420167	DapagliFLOzin in Renal AL Amyloidosis (FLORAL)	https://clinicaltrials.gov/study/NCT06420167	NOT_YET_RECRUITING	Renal AL Amyloidosis	DRUG: Dapagliflozin	Jeffrey Zonder		INTERVENTIONAL
NCT04644315	A Home-Based Approach Study to Evaluate the Efficacy and Safety of Alectinib in Locally-Advanced or Metastatic ALK-Positive Solid Tumors	https://clinicaltrials.gov/study/NCT04644315	TERMINATED	Neoplasms, Colorectal Neoplasms, Melanoma, Pancreatic Neoplasms, Sarcoma, Ovarian Neoplasms, Brain Neoplasms, Thyroid Neoplasms, Neuroendocrine Tumors, Cholangiocarcinoma, Salivary Gland Neoplasms, Head and Neck Neoplasms, Thyroid Cancer, Papillary, Lymphoma, Large-Cell, Anaplastic, Neoplasms by Site, Respiratory Tract Neoplasms, Thoracic Neoplasms, Respiratory Tract Diseases, Carcinoma, Bronchogenic, Bronchial Neoplasms, Intestinal Neoplasms, Gastrointestinal Neoplasms, Digestive System Neoplasms, Digestive System Diseases, Gastrointestinal Diseases, Colonic Diseases, Intestinal Diseases, Central Nervous System	DRUG: Alectinib	Hoffmann-La Roche		INTERVENTIONAL
NCT06140290	A Sub Study to Evaluate the Study Medication (Etrasimod) Using Wearable Sensors in Healthy Participants	https://clinicaltrials.gov/study/NCT06140290	COMPLETED	Healthy Participants	DRUG: Etrasimod Immediate Release (IR)	Pfizer		INTERVENTIONAL
NCT06162013	The NADAPT Study: A Randomized Double-blind Trial of NAD Replenishment Therapy for Atypical Parkinsonism	https://clinicaltrials.gov/study/NCT06162013	RECRUITING	Progressive Supranuclear Palsy, Multiple System Atrophy, Corticobasal Syndrome	DIETARY_SUPPLEMENT: Nicotinamide Riboside, OTHER: Placebo	Haukeland University Hospital	Oslo universitetssykehus HF, Akershus Universitetssykehus HF, Vestre Viken Hospital Trust, Sykehuset Ostfold, Nevro Arendal AS, Helse Forde, Helse Fonna HF, Universitetssykehuset Nord Norge HF, Helse Møre og Romsdal HF, Nordlandssykehuset HF, Elysium Health	INTERVENTIONAL
NCT03885206	Effectiveness and Clinical Outcomes of Municipal Acute Wards Versus a General Hospital	https://clinicaltrials.gov/study/NCT03885206	COMPLETED	Patient Experience, Medical Emergencies, Mortality, Morbidity, Co-morbidity, Quality of Life	OTHER: Level of Healthcare Services	Ostfold University College	Extrastiftelsen, Akersgatab28, No-0158Oslo, Norway, The National Association for Heart and Lung Disease, Jessheim, Norway, University of Oslo, University Hospital, Akershus, Ostfold Hospital Trust	INTERVENTIONAL
NCT06200350	Personalized Recommendation System for Sport Activities	https://clinicaltrials.gov/study/NCT06200350	ACTIVE_NOT_RECRUITING	Health Behavior	OTHER: Experimental Group, OTHER: Control Group	University of Vigo		INTERVENTIONAL
NCT03594838	Evaluation of HCV Viremia Testing Approaches Among PWID in Georgia	https://clinicaltrials.gov/study/NCT03594838	COMPLETED	Hepatitis C, Chronic	OTHER: HCV Viremia Testing Approaches	Foundation for Innovative New Diagnostics, Switzerland	The National Center for Disease Control and Public Health, Health Research Union	INTERVENTIONAL
NCT03969030	Peer-Educator-coordinated vs Nurse-coordinated ART Refill for Adolescents and Young Adults Living With HIV in Lesotho	https://clinicaltrials.gov/study/NCT03969030	COMPLETED	HIV/AIDS	OTHER: PEBRA model	Amstutz Alain	International AIDS Society (CIPHER grant), Swiss Tropical & Public Health Institute, SolidarMed, Sentebale, University of Basel, University Hospital, Basel, Switzerland, Swiss National Science Foundation	INTERVENTIONAL
NCT02893553	The Effects of Normalizing Blood Pressure on Cerebral Blood Flow in Hypotensive Individuals With Spinal Cord Injury	https://clinicaltrials.gov/study/NCT02893553	COMPLETED	Spinal Cord Injury, Autonomic Dysreflexia, Baroreceptor Integrity, Sympathetic Integrity, Vagal Integrity, Autonomic Integrity, Hypotensive, Cognitive Function, Cerebral Blood Flow, Blood Pressure	DRUG: Midodrine Hydrochloride, DRUG: Pyridostigmine Bromide, DRUG: Mirabegron, OTHER: Placebo	James J. Peters Veterans Affairs Medical Center	Kessler Foundation	INTERVENTIONAL
NCT06597786	A Study of Exercise Therapy in People With Solid Tumor Cancer	https://clinicaltrials.gov/study/NCT06597786	RECRUITING	Solid Tumor Cancer	OTHER: Exercise Therapy	Memorial Sloan Kettering Cancer Center		INTERVENTIONAL
NCT03259373	IMplementation of an RCT to imProve Treatment With Oral AntiCoagulanTs in Patients With Atrial Fibrillation	https://clinicaltrials.gov/study/NCT03259373	UNKNOWN	Atrial Fibrillation, Stroke	BEHAVIORAL: Early Patient-Level and Provider-Level Educational Intervention, BEHAVIORAL: Delayed Provider-Level Educational Intervention	Harvard Pilgrim Health Care	Duke Clinical Research Institute, Clinical Trials Transformation Initiative, Humana Inc., Aetna, Inc., OptumInsight Life Sciences, Inc., Food and Drug Administration (FDA)	INTERVENTIONAL
NCT05058937	A Study to Examine the Clinical Value of Comprehensive Genomic Profiling Performed by Belgian NGS Laboratories: a Belgian Precision Study of the BSMO in Collaboration With the Cancer Centre	https://clinicaltrials.gov/study/NCT05058937	RECRUITING	Solid Tumor, Metastatic Cancer	DIAGNOSTIC_TEST: Comprehensive Genomic Profiling	The Belgian Society of Medical Oncology	Illumina, Inc., OncoDNA, PierianDx	INTERVENTIONAL
NCT05276349	Home-based Remote Digital Monitoring to Assess ALS Progression (Track ALS)	https://clinicaltrials.gov/study/NCT05276349	ACTIVE_NOT_RECRUITING	ALS (Amyotrophic Lateral Sclerosis)		St. Joseph’s Hospital and Medical Center, Phoenix	Emory University, Mitsubishi Tanabe Pharma America Inc.	OBSERVATIONAL
NCT05090150	The SMART ART Study	https://clinicaltrials.gov/study/NCT05090150	RECRUITING	HIV, ART	OTHER: Home delivery of ART, OTHER: Smart Lockers (Pele boxes), OTHER: Best Clinic Practices + Conditional Lottery Incentives, OTHER: Best Clinic Practices	Massachusetts General Hospital	National Institute of Mental Health (NIMH)	INTERVENTIONAL
NCT03321123	MB-CART19.1 in Patients With R/R ALL	https://clinicaltrials.gov/study/NCT03321123	UNKNOWN	Precursor B-Lymphoblastic Lymphoma/Leukaemia Refractory	DRUG: MB-CART19.1	Shanghai Children’s Medical Center	Miltenyi Biomedicine GmbH	INTERVENTIONAL
NCT01710605	Medico-economic Interest of Taking Into Account Circulating Tumor Cells (CTC) to Determine the Kind of First Line Treatment for Metastatic, Hormone-receptors Positive, Breast Cancers	https://clinicaltrials.gov/study/NCT01710605	UNKNOWN	Ductal Infiltrating Metastatic Breast Cancer, Hormone-receptors Positive Breast Cancer	BIOLOGICAL: Circulating Tumor Cells Counting at Baseline	Institut Curie		INTERVENTIONAL
NCT00675389	Impact of Peer Health Workers and Mobile Phones on HIV Care	https://clinicaltrials.gov/study/NCT00675389	COMPLETED	HIV Infections	BEHAVIORAL: Peer Health Workers Intervention, BEHAVIORAL: Peer Health Workers and Mobile Phone Intervention	Johns Hopkins University	Doris Duke Charitable Foundation, MRC/UVRI and LSHTM Uganda Research Unit, National Institute of Allergy and Infectious Diseases (NIAID)	INTERVENTIONAL
NCT06337578	Advances in Telephone-based Cognitive Screening Procedures	https://clinicaltrials.gov/study/NCT06337578	RECRUITING	Amyotrophic Lateral Sclerosis, Alzheimer’s Disease, Lewy Body Dementia, Frontotemporal Degeneration, Cerebrovascular Disorders	BEHAVIORAL: Telephone-based Neuropsychological Assessment—ALS BEHAVIORAL: Telephone-based Neuropsychological Assessment—AD, LBD, FTD and CVD, BEHAVIORAL: Telephone-based and In-person Cognitive Screening—NIs	Istituto Auxologico Italiano		OBSERVATIONAL
NCT06053346	Partners in Wellness: Evaluation of a Pay for Performance Program for High-Utilizers of Mental Health Services	https://clinicaltrials.gov/study/NCT06053346	COMPLETED	Psychotic Disorders, Bipolar Disorder, Substance Use Disorders	BEHAVIORAL: Pay For Performance (PFP), BEHAVIORAL: Usual Care (UC)	Stanford University		INTERVENTIONAL
NCT06554223	The SUSTAIN 2 Study—Sustained HIV Treatment for Adherence After Interruption in Care	https://clinicaltrials.gov/study/NCT06554223	NOT_YET_RECRUITING	Human Immunodeficiency Virus	BEHAVIORAL: SUSTAIN-DSD, OTHER: Enhanced (Guideline-driven) Standard of Care (E-SoC)	Brigham and Women’s Hospital		INTERVENTIONAL
NCT01805752	Optimizing Integrated PMTCT Services in Rural North-Central Nigeria	https://clinicaltrials.gov/study/NCT01805752	COMPLETED	Suspected Damage to Fetus From Viral Disease in the Mother, HIV	OTHER: Task-shifting to Lower-care Providers at PMTCT Sites, OTHER: POC CD4+ Cell Count Testing, OTHER: Integrated Mother-infant Care, OTHER: Prominent Role for Influential Family Members (Male Partners) in Collaboration with CHWs	Vanderbilt University	National Institutes of Health (NIH)	INTERVENTIONAL
NCT05165810	Evaluation of Multiple Interventions to Improve HIV Treatment Outcomes Among People Who Inject Drugs in India	https://clinicaltrials.gov/study/NCT05165810	RECRUITING	HIV Infections	BEHAVIORAL: Same-day ART Initiation [Experimental], BEHAVIORAL: Standard ART Initiation [Usual Care], OTHER: Community-based HIV Care [Experimental], OTHER: Government-based HIV Care [Usual Care], BEHAVIORAL: Enhanced Adherence Support [Experimental], BEHAVIORAL: Routine Adherence Support [Usual Care]	Johns Hopkins University	YR Gaitonde Centre for AIDS Research and Education, National Institute on Drug Abuse (NIDA)	INTERVENTIONAL

The Function of Blockchain Technology in Facilitating DCTs

Blockchain technology is a distributed ledger system that stores data via a decentralized network. It was first created for safe and transparent bitcoin transactions. This structure provides important benefits such as data immutability, transparency, and security. It is frequently made up of a series of encrypted “blocks” of data. Because of these characteristics, blockchain is a great option for enhancing the administration and operation of DCTs, where participant involvement and data integrity are crucial.

An Overview of Blockchain for Security and Data Integrity

Data entries can be made in a permanent, visible, and secure manner thanks to blockchain’s decentralized ledger. Each block is cryptographically connected to the previous one, meaning that any changes to the content must be approved by the network, which helps prevent data manipulation. This feature is useful for DCTs, where data must be continuously collected from remote participants while remaining secure and verifiable. By utilizing private and permissioned blockchains, such as Hyperledger Fabric, researchers can manage access to sensitive data while maintaining the transparency required for regulatory compliance.⁴²

Smart Contracts for Automated Workflows and Dynamic Consent

The blockchain’s self-executing smart contracts make it possible to manage participant consent and trial procedures effectively. By enabling real-time revisions of participant consent preferences in DCTs, these contracts guarantee that researchers can monitor any modifications to study participants’ participation. Furthermore, smart contracts reduce the possibility of human error and improve transparency by automating a variety of trial procedures, such as initiating data-gathering events and carrying out payments. Enhancing patient involvement and streamlining intricate trial logistics depends on this characteristic.^43,44

Improved Regulatory Compliance and Data Privacy

In clinical trials, where patient data privacy is crucial, blockchain technology’s capacity to offer safe, decentralized data storage options is especially crucial. Blockchain’s ledger is supplemented with decentralized storage systems, such as the interplanetary file system, which store large amounts of data off-chain, lowering costs, and improving scalability without sacrificing verifiability. By offering an auditable record of all transactions and data exchanges, blockchain also facilitates regulatory compliance, making it simpler for regulators and researchers to keep an eye on the trial’s progress and guarantee data integrity.⁴⁵

Data Sharing and Interoperability

Blockchain allows for seamless data sharing among various stakeholders—pharmaceutical companies, clinical research organizations, and regulators—by ensuring that all parties have access to the same data version in real time. This lowers data reconciliation mistakes and eliminates the need for middlemen, which is especially beneficial in the decentralized and hybrid trial formats that have become popular during and after the COVID-19 pandemic.⁴⁶

Contributions of AI to improve DCTs

DCTs are being transformed by artificial intelligence (AI), which improves patient experience, data gathering, recruitment, and retention. Here are some effects of AI that are backed up by pertinent research.^47–53

Improved Recruitment and Retention

Locating and keeping participants is one of the major obstacles in clinical trials. AI makes this process easier by sifting through massive datasets to find qualified patients more quickly. AI algorithms can use real-world data from social media, EHRs, and other sources to match patient characteristics with trial needs. This shortens the time needed to enroll patients and increases the accuracy of patient selection. Research has shown that AI-driven tools in recruitment not only optimize efficiency but also mitigate bias in patient selection by expanding the pool of participants across diverse demographics and geographic locations, which is essential for decentralized models that aim to be more inclusive and representative of the general population. In the field of oncology, companies like Tempus have employed AI to better target underserved populations in clinical trials. Using AI to analyze EHRs, Tempus was able to identify minority patients with rare forms of cancer who were otherwise missed by traditional recruitment methods. By matching these patients to appropriate trials, the company was able to improve diversity in cancer research and treatment outcomes. Verily Life Sciences, a subsidiary of Alphabet, has been integrating AI and machine learning into clinical trials, including multilingual and multinational efforts. In their research, AI tools helped translate complex medical information into over 20 languages, making clinical trials more accessible to diverse patient groups globally.

Automated Data Gathering and Monitoring

AI facilitates automated data processing and patient-reported outcome monitoring, which are essential components of decentralized trials that depend on distant data gathering. Clinicians can keep an eye on patients’ health in real time by using AI systems to evaluate data from wearable devices and track parameters like heart rate or physical activity. This results in safer and more successful trials by lowering the need for in-person visits and assisting in the early identification of problems. In large-scale decentralized trials, AI’s contribution to data monitoring is very beneficial in enhancing data integrity and lowering errors. Data processing AI ­analyzes and combines many data sources, including patient-reported outcomes, wearables, and EHRs. Faster insights are made possible by Medable’s platform, which uses AI to harmonize real-time data from many sources in DCTs. For example, it assisted a trial sponsor in handling data from wearable technology and telehealth while cutting down on recruitment time by 50%.

Case Study: Virtual Trials at Pfizer

In order to ensure smooth data integration across digital touchpoints, Pfizer’s REMOTE experiment employed AI-driven technologies to remotely gather and process data from rheumatoid arthritis participants. AI ensures real-time tracking of health parameters by enabling remote patient monitoring using wearable technology and Internet of Things-enabled technologies. Wearable sensors are used by Biofourmis’ AI-powered platform to continuously monitor patient vitals like temperature and heart rate. It assisted in identifying early indicators of decline in a COVID-19 experiment.

Case Study: Wearable Technology Experiments at Novartis

In its multiple sclerosis trials, Novartis employed AI to evaluate wearable data, providing ongoing patient monitoring without frequent clinic visits.

Predictive Modeling: AI aids in trial design optimization by forecasting outcomes like disease progression or patient reactions to therapies. BenevolentAI uses machine learning to forecast patient reactions and possible medication candidates. It recognized baricitinib as a potential COVID-19 therapy during the epidemic.

Case Study: Health Flatiron

AI is used by Flatiron Health to forecast the outcomes of cancer patients based on empirical data, which helps with the design of clinical trials for oncology research. By keeping an unchangeable record, blockchain stops unwanted data changes. Triall uses blockchain integration to protect clinical trial data, guaranteeing the provenance and immutability of each data piece. Without the need for middlemen, trial sponsors can confirm the accuracy of data submissions.

Pfizer and Boehringer Ingelheim as a Case Study

Blockchain technology was employed by both businesses to protect private clinical trial data, guaranteeing that the data would not be changed during the trial.

Protection of Privacy: Blockchain uses decentralized identification and cryptography techniques to protect patient privacy. Embleema gives patients authority over their data while securely sharing and anonymizing information with trial sponsors via blockchain.

Case Study

The MedRec Project at MIT MedRec employs blockchain technology to keep a safe, decentralized patient record repository. To exchange encrypted patient data with researchers while maintaining anonymity, this system was tested for clinical trials.

Transparency and Compliance: Real-time, traceable logs for data sharing and regulatory compliance are made possible by blockchain. To provide auditability for regulatory agencies, IBM and Hyperledger collaborated to develop a blockchain-based system that follows each stage of clinical trials. Blockchain technology was employed by Bayer to guarantee traceable and transparent data sharing during clinical trials. The system improved stakeholder confidence and expedited consent management.

Enhancing Patient Experience: AI also makes the trial process easier for patients by giving them access to chatbots, digital assistants, and applications that provide support, reminders, and direction during the study. It has been demonstrated that this strategy increases participation because it makes participants feel more knowledgeable and connected, both of which are critical for long-term retention. DCTs are a feasible option for people who might not otherwise be able to participate since AI lessens the stress on patients by personalizing interactions and streamlining intricate procedures.

Language and Cultural Adaptation: Real-time translation and cultural contextualization of trial materials, including consent forms and teaching materials, are made possible by AI-powered natural language processing. AI techniques, for instance, might modify information to accommodate regional dialects and idioms, guaranteeing that trial participants comprehend and are at ease with the procedures.

Enhancing Accessibility: By providing user-friendly interfaces and multilingual support, AI-driven platforms, such as Medable’s solutions, simplify virtual trial participation and lower obstacles for participants who do not understand English. For example, in Asia-Pacific, ObvioHealth and Oracle’s partnership made it possible to integrate a variety of data for trials, increasing accessibility across cultural boundaries. U.S. National Institute of Health (NIH) and FDA have worked on initiatives to increase representation in clinical trials. AI systems have been used to identify patients in underrepresented communities, especially in trials for cancer treatments and rare diseases. AI helped predict which communities were most likely to benefit from new treatments and designed culturally sensitive recruitment campaigns, leading to more equitable participation.

Cost and Time Efficiency: AI reduces the logistical and financial obstacles that decentralized trials have historically faced by automating time-consuming processes like data entry and eligibility screening. Clinical trials might be shortened by up to 10% using AI-driven automation, according to research, which would save money and speed up trial results. AI-powered logistics also make trial coordination easier and increase scalability in a decentralized approach where trials take place in multiple locations.

Pfizer conducted a DCT for evaluating the efficacy of its COVID-19 vaccine (BNT162b2). A key feature of this trial was that patients participated remotely, completing health assessments through an app, with no need for frequent site visits.

Key Results:

• Cost Savings: By reducing the need for physical infrastructure and fewer site personnel, Pfizer estimated a significant reduction in operational costs compared to traditional trials.
• Time Reductions: The decentralized nature allowed rapid recruitment and participant retention due to the convenience of home-based data collection. This contributed to faster trial completion and a quicker timeline for results.
• Patient Recruitment and Retention: Virtual enrollment led to higher diversity in the participant pool, with increased retention rates due to convenience. Recruitment was sped up as patients could enroll and participate without traveling to a central site.
• Impact: Pfizer reported a reduction in overall study costs by streamlining patient visits and reducing the need for traditional site visits.

Medable, a technology company specializing in DCTs, collaborated with Novartis on an oncology trial for prostate cancer. The study combined traditional in-clinic visits with remote monitoring using telemedicine, wearable devices, and digital health tools.

Key Results

• Cost Savings: Medable’s platform helped reduce administrative costs, such as site management and patient enrollment efforts, by streamlining data collection and communications. Novartis saw a 20–30% reduction in the costs associated with patient visits and data management.
• Time Reductions: By integrating remote monitoring and virtual visits, the trial was able to speed up patient visits and data collection. This led to an overall reduction in the trial timeline, allowing faster data analysis and regulatory submission.
• Patient Experience: Patients appreciated the flexibility of the DCT model, leading to higher satisfaction and retention. The integration of at-home health monitoring devices meant that fewer in-person visits were required, saving patients time and improving adherence to the protocol.
• Impact: The hybrid model, combining traditional and decentralized methods, demonstrated clear cost savings and improved timelines while maintaining trial integrity and data quality.

Science 37, a leader in fully DCTs, worked with Medtronic on a diabetes-related clinical trial. The trial used telehealth visits, mobile apps for data capture, and home-based clinical testing.

Key Results

• Cost Savings: The trial saw a 40% reduction in site-related costs, including investigator fees and patient recruitment costs. By eliminating travel and the need for on-site clinical operations, Medtronic achieved substantial savings in the overall study budget.
• Time Reductions: The decentralized model enabled the trial to reduce its duration by about 6 months compared to a traditional trial of a similar scope. Remote visits and digital data collection allowed quicker patient enrollment, real-time monitoring, and faster identification of adverse events.
• Scalability and Recruitment: The decentralized model allowed Medtronic to recruit a broader, more geographically diverse patient population, including underserved communities, which improved both recruitment speed and trial representation.
• Impact: The trial demonstrated how a fully decentralized model could reduce operational burdens and significantly improve timelines and patient access.

Verily Life Sciences conducted a hybrid study on diabetes management in collaboration with virtual health platforms. This trial used a combination of home-based glucose monitoring, telemedicine consultations, and digital symptom tracking.

Key Results

• Cost Savings: The trial leveraged remote monitoring and digital tools to reduce costs associated with in-person visits, which are traditionally a significant portion of trial expenses. By eliminating the need for centralized trial sites, the trial saved on overhead, staffing, and patient travel reimbursements.
• Time Reductions: Data collection and analysis were streamlined using wearable devices, allowing for faster data processing and real-time insights. The trial was able to reduce the study duration by 4 months.
• Patient Engagement and Retention: Participants appreciated the ease of monitoring their diabetes from home, and retention rates were higher than in traditional trials. Recruitment was faster due to broader outreach, with patients able to participate from home.
• Impact: The case study highlights how remote health tools not only reduce costs and time but also improve patient engagement and data accuracy.

Eli Lilly ran the EVOLVE-3 trial for a rheumatology drug using a decentralized design with telemedicine and remote monitoring of clinical outcomes. Patients completed assessments via an app, while mobile health professionals visited participants’ homes.

Key Results

• Cost Savings: The use of remote monitoring and home visits saved approximately 25% of the typical costs related to patient recruitment and clinical site management.
• Time Reductions: With fewer in-person visits required, the recruitment process was faster, and the study timeline was shortened by 4 months. Digital tools enabled continuous data collection, reducing gaps and delays.
• Improved Patient Experience: By reducing the burden on patients to travel to clinics, Eli Lilly saw better patient satisfaction and higher completion rates.
• Impact: The study demonstrated that even for complex diseases requiring ongoing treatment and monitoring, a decentralized approach could streamline operations, cut costs, and improve patient retention.

Conclusion

A paradigm change in clinical research, DCTs have the potential to greatly increase the effectiveness, accessibility, and inclusion of trials for a variety of populations. DCTs overcome many of the geographical and logistical constraints that restrict participation in conventional trials by leveraging digital and remote tools. DCTs’ potential is further enhanced by the use of blockchain technology and AI, which adds levels of data protection, integrity, and analytical capability. Trial data is kept in a safe, tamper-proof environment thanks to blockchain’s immutability and transparency, protecting patient privacy and improving regulatory compliance. AI-driven analytics, on the other hand, enable quicker and more precise insights from intricate datasets, promoting in-the-moment decision-making and improving patient outcomes. When combined, these technologies allow for more patient-centered, flexible, and dynamic clinical trials, which eventually speeds up the conversion of research findings into clinical practice. To address obstacles pertaining to data interoperability, regulatory frameworks, and user adoption in the future, cooperation between regulatory agencies, technological developers, and healthcare stakeholders will be crucial. DCTs backed by blockchain and AI have the potential to revolutionize clinical research and help create a more effective, inclusive, and individualized approach to clinical medicine with continued work.

References

1 FDA. Basics About Clinical Trials 2023. Available from: https://www.fda.gov/patients/clinical-trials-what-patients-need-know/basics-about-clinical-trials.
 
2 Subbiah V. The next generation of evidence-based medicine. Nat Med. 2023;29(1):49-58.
https://doi.org/10.1038/s41591-022-02160-z
 
3 Julian H, Sally G. Cochrane Handbook for Systematic Reviews of Interventions: cochrane Book Series. The Cochrane Collaboration. 2008.
 
4 Concato J, Shah N, Horwitz RI. Randomized, controlled trials, observational studies, and the hierarchy of research designs. N Engl J Med. 2000;342(25):1887-92.
https://doi.org/10.1056/NEJM200006223422507
 
5 Bhatt DL, Mehta C. Adaptive designs for clinical trials. N Engl J Med. 2016;375(1):65-74.
https://doi.org/10.1056/NEJMra1510061
 
6 Ford I, Norrie J. Pragmatic trials. N Engl J Med. 2016;375(5):454-63.
https://doi.org/10.1056/NEJMra1510059
 
7 Friedman LM, Furberg CD, DeMets DL, Reboussin DM Granger CB. Fundamentals of Clinical Trials. Springer. 2015.
https://doi.org/10.1007/978-3-319-18539-2
 
8 Hariton E, Locascio JJ. Randomised controlled trials – the gold standard for effectiveness research. Br J Obstetr Gynaecol. 2018;125(13):1716.
https://doi.org/10.1111/1471-0528.15199
 
9 Bothwell LE, Greene JA, Podolsky SH, Jones DS. Assessing the gold standard – lessons from the history of RCTs. N Engl J Med. 2016;374(22):2175-81.
https://doi.org/10.1056/NEJMms1604593
 
10 Nason M, Follmann D. Design and analysis of crossover trials for absorbing binary endpoints. Biometrics. 2010;66(3):958-65.
https://doi.org/10.1111/j.1541-0420.2009.01358.x
 
11 Dwan K, Li T, Altman DG, Elbourne D. CONSORT 2010 statement: Extension to randomised crossover trials. BMJ. 2019;366:l4378.
https://doi.org/10.1136/bmj.l4378
 
12 Hayes RJ, Moulton LH. Cluster Randomised Trials. 2nd Edition. New York: Chapman and Hall/CRC. 2017.
 
13 Donner A, Klar N. Design and Analysis of Cluster Randomization Trials in Health Research. Arnold. 2010.
 
14 Berry DA. Adaptive clinical trials: the promise and the caution. J Clin Oncol. 2011;29(6):606-9.
https://doi.org/10.1200/JCO.2010.32.2685
 
15 Chow SC, Chang M. Adaptive design methods in clinical trials – A review. Orphanet J Rare Dis. 2008;3:11.
https://doi.org/10.1186/1750-1172-3-11
 
16 FDA. Adaptive design clinical trials for drugs and biologics: Guidance for industry. In: CBER, editor. Food and Drug Administration. 2019.
 
17 Piaggio G, Elbourne DR, Altman DG, Pocock SJ, Evans SJ, Group C. Reporting of noninferiority and equivalence randomized trials: an extension of the CONSORT statement. JAMA. 2006;295(10):1152-60.
https://doi.org/10.1001/jama.295.10.1152
 
18 D’Agostino RB, Sr., Massaro JM, Sullivan LM. Non-inferiority trials: Design concepts and issues – The encounters of academic consultants in statistics. Stat Med. 2003;22(2):169-86.
https://doi.org/10.1002/sim.1425
 
19 Mauri L, D’Agostino RB, Sr. Challenges in the design and interpretation of noninferiority trials. N Engl J Med. 2017;377(14):1357-67.
https://doi.org/10.1056/NEJMra1510063
 
20 FDA. Master protocols: Efficient clinical trial design strategies to expedite development of oncology drugs and biologics. In: services UDoHaH, editor. Food and Drug Administration. 2022.
 
21 Elsasser A, Regnstrom J, Vetter T, Koenig F, Hemmings RJ, Greco M, et al. Adaptive clinical trial designs for European marketing authorization: a survey of scientific advice letters from the European Medicines Agency. Trials. 2014;15:383.
https://doi.org/10.1186/1745-6215-15-383
 
22 Woodcock J, LaVange LM. Master protocols to study multiple therapies, multiple diseases, or both. N Engl J Med. 2017;377(1):62-70.
https://doi.org/10.1056/NEJMra1510062
 
23 Hirakawa A, Asano J, Sato H, Teramukai S. Master protocol trials in oncology: review and new trial designs. Contemp Clin Trials Commun. 2018;12:1-8.
https://doi.org/10.1016/j.conctc.2018.08.009
 
24 Redig AJ, Janne PA. Basket trials and the evolution of clinical trial design in an era of genomic medicine. J Clin Oncol. 2015;33(9):975-7.
https://doi.org/10.1200/JCO.2014.59.8433
 
25 Ouma LO, Wason JMS, Zheng H, Wilson N, Grayling M. Design and analysis of umbrella trials: where do we stand? Front Med (Lausanne). 2022;9:1037439.
https://doi.org/10.3389/fmed.2022.1037439
 
26 Janiaud P, Serghiou S, Ioannidis JPA. New clinical trial designs in the era of precision medicine: an overview of definitions, strengths, weaknesses, and current use in oncology. Cancer Treat Rev. 2019;73:20-30.
https://doi.org/10.1016/j.ctrv.2018.12.003
 
27 Burd A, Schilsky RL, Byrd JC, Levine RL, Papadimitrakopoulou VA, Herbst RS, et al. Challenges and approaches to implementing master/basket trials in oncology. Blood Adv. 2019;3(14):2237-43.
https://doi.org/10.1182/bloodadvances.2019031229
 
28 Roustit M, Demarcq O, Laporte S, Barthelemy P, Chassany O, Cucherat M, et al. Platform trials. Therapie. 2023;78(1):29-38.
https://doi.org/10.1016/j.therap.2022.12.003
 
29 Saville BR, Berry SM. Efficiencies of platform clinical trials: a vision of the future. Clin Trials. 2016;13(3):358-66.
https://doi.org/10.1177/1740774515626362
 
30 Park JJH, Sharif B, Harari O, Dron L, Heath A, Meade M, et al. Economic evaluation of cost and time required for a platform trial vs conventional trials. JAMA Netw Open. 2022;5(7):e2221140.
https://doi.org/10.1001/jamanetworkopen.2022.21140
 
31 Pallmann P, Bedding AW, Choodari-Oskooei B, Dimairo M, Flight L, Hampson LV, et al. Adaptive designs in clinical trials: why use them, and how to run and report them. BMC Med. 2018;16(1):29.
https://doi.org/10.1186/s12916-018-1017-7
 
32 Fountzilas E, Tsimberidou AM, Vo HH, Kurzrock R. Clinical trial design in the era of precision medicine. Genome Med. 2022;14(1):101.
https://doi.org/10.1186/s13073-022-01102-1
 
33 Dickson D, Johnson J, Bergan R, Owens R, Subbiah V, Kurzrock R. The master observational trial: a new class of master protocol to advance precision medicine. Cell. 2020;180(1):9-14.
https://doi.org/10.1016/j.cell.2019.12.009
 
34 Di Liello R, Piccirillo MC, Arenare L, Gargiulo P, Schettino C, Gravina A, et al. Master protocols for precision medicine in oncology: Overcoming methodology of randomized clinical trials. Life (Basel). 2021;11(11):1253.
https://doi.org/10.3390/life11111253
 
35 Turner JH. Ethics of pharma clinical trials in the era of precision oncology. Cancer Biother Radiopharm. 2021;36(1):1-9.
https://doi.org/10.1089/cbr.2020.4129
 
36 DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: New estimates of R&D costs. J Health Econ. 2016;47:20-33.
https://doi.org/10.1016/j.jhealeco.2016.01.012
 
37 Gul RB, Ali PA. Clinical trials: The challenge of recruitment and retention of participants. J Clin Nurs. 2010;19(1-2):227-33.
https://doi.org/10.1111/j.1365-2702.2009.03041.x
 
38 JAMA. Ethical principles for medical research and practice. 2024. Available from: https://sites.jamanetwork.com/research-ethics/.
 
39 Loudon K, Treweek S, Sullivan F, Donnan P, Thorpe KE, Zwarenstein M. The PRECIS-2 tool: designing trials that are fit for purpose. BMJ. 2015;350:h2147.
https://doi.org/10.1136/bmj.h2147
 
40 Dwan K, Gamble C, Williamson PR, Kirkham JJ, Reporting Bias G. Systematic review of the empirical evidence of study publication bias and outcome reporting bias – An updated review. PLoS One. 2013;8(7):e66844.
https://doi.org/10.1371/journal.pone.0066844
 
41 FDA. Conducting Clinical Trials with Decentralized Elements. Food and Drug Administration. 2024.
 
42 Maslove DM, Klein J, Brohman K, Martin P. Using blockchain technology to manage clinical trials data: a proof-of-concept study. JMIR Med Inform. 2018;6(4):e11949.
https://doi.org/10.2196/11949
 
43 Lee CA, Chow KM, Chan HA, Lun DP. Decentralized governance and artificial intelligence policy with blockchain-based voting in federated learning. Front Res Metr Anal. 2023;8:1035123.
https://doi.org/10.3389/frma.2023.1035123
 
44 Khan SN, Loukil F, Ghedira-Guegan C, Benkhelifa E, Bani-Hani A. Blockchain smart contracts: applications, challenges, and future trends. Peer Peer Netw Appl. 2021;14(5):2901-25.
https://doi.org/10.1007/s12083-021-01127-0
 
45 Jia W, Xie T, Wang B. A privacy-preserving scheme with multi-level regulation compliance for blockchain. Sci Rep. 2024;14(1):438.
https://doi.org/10.1038/s41598-023-50209-x
 
46 Kasyapa MSB, Vanmathi C. Blockchain integration in healthcare: a comprehensive investigation of use cases, performance issues, and mitigation strategies. Front Digit Health. 2024;6:1359858.
https://doi.org/10.3389/fdgth.2024.1359858
 
47 Hutson M. How AI is being used to accelerate clinical trials. Nature. 2024;627(8003):S2-S5.
https://doi.org/10.1038/d41586-024-00753-x
 
48 Thomas KA, Kidzinski L. Artificial intelligence can improve patients’ experience in decentralized clinical trials. Nat Med. 2022;28(12):2462-3.
https://doi.org/10.1038/s41591-022-02034-4
 
49 Warraich HJ, Tazbaz T, Califf RM. FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine. JAMA. 2024. doi:10.1001/jama.2024.21451
https://doi.org/10.1001/jama.2024.21451
 
50 Cunningham JW, Abraham WT, Bhatt AS, Dunn J, Felker GM, Jain SS, et al. Artificial intelligence in cardiovascular clinical trials. J Am Coll Cardiol. 2024;84(20):2051-62.
https://doi.org/10.1016/j.jacc.2024.08.069
 
51 Goldberg JM, Amin NP, Zachariah KA, Bhatt AB. The introduction of AI into decentralized clinical trials: preparing for a paradigm shift. JACC Adv. 2024;3(8):101094.
https://doi.org/10.1016/j.jacadv.2024.101094
 
52 How artificial intelligence can power clinical development 2023. Available from: https://www.mckinsey.com/industries/life-sciences/our-insights/how-artificial-intelligence-can-power-clinical-development.
 
53 Vayena E, Blasimme A, Sugarman J. Decentralised clinical trials: Ethical opportunities and challenges. Lancet Digit Health. 2023;5(6):e390-e4.
https://doi.org/10.1016/S2589-7500(23)00052-3
 

Cite this article as:
Dhar S. Decentralized Clinical Trials and Opportunities with Artificial Intelligence. Premier Journal of Artificial Intelligence 2024;1:1000077

Export to EndNote Export to Mendeley