Clinical Trial Management System Research Articles

Leveraging Decentralized Clinical Trial Management Systems (dCTMS) to Advance Science: Exploring Challenges Related to the Diffusion of Innovation and Its Execution.

Decentralized clinical trials (DCTs) recently gained attention in research necessary for drug development. While the COVID-19 pandemic proved to be a challenging time in this arena, drug development was a critical area of emphasis in the rapid advancement of vaccines. The DCTs were necessary to allow research activities to occur across many locations. The use of DCTs can profoundly impact reshaping healthcare by enabling participants to partake in clinical trials remotely; however, implementation challenges must be considered as technology expands. A working group of participants was assembled during an interactive learning exercise at the Conv2X conference (2023) to explore challenges related to the diffusion of innovation among key stakeholders. Pain points experienced with using and implementing technologies were identified, and an innovative solution using a blockchain-anchored option was presented. Participants were divided into three stakeholder groups: patients, payers, and pharmaceutical sponsors. After a time of discussion, the groups reconvened for review. Several themes that can be supported by blockchain technology emerged. These include enhanced efficiencies, patient experience, and demographic diversity, as well as data integrity, privacy, security, and cost-effectiveness. Future research might focus on strategies to facilitate the adoption of the idea across key stakeholder groups.

The Korean hip fracture registry study

BackgroundThe purpose of the Korean Hip Fracture Registry (KHFR) Study is to establish a nationwide, hospital-based prospective cohort study of adults with hip fracture to explore the incidence and risk factors of second osteoporotic fractures for a Fracture Liaison Service (FLS) model.MethodsThe KHFR, a prospective multicenter longitudinal study, was launched in 2014. Sixteen centers recruited participants who were treated for hip fracture. The inclusion criteria were patients, who were treated for proximal femur fracture due to low-energy trauma and aged 50 or more at the time of injury. Until 2018, 5,841 patients were enrolled in this study. Follow-up surveys were conducted annually to determine occurrence of second osteoporotic fracture, and 4,803 participants completed at least one follow-up survey.DiscussionKHFR is a unique resource of individual level on osteoporotic hip fracture with radiological, medical, and laboratory information including DXA (dual energy x-ray absorptiometry), bone turnover marker, body composition, and hand grip strength for future analyses for FLS model. Modifiable factors for mortality after hip surgery is planned to be identified with nutritional assessment and multi-disciplinary interventions from hospitalization to follow-ups. The proportions of femoral neck, intertrochanteric, and subtrochanteric fractures were 517 (42.0%), 730 (53.6%), and 60 (4.4%), respectively, from 2014 to 2016, which was similar in other studies. Radiologic definition of atypical subtrochanteric fracture was adopted and 17 (1.2%) fractures among 1,361 proximal femoral fractures were identified. Internal fixation showed higher reoperation rate compared to arthroplasty in unstable intertrochanteric fractures (6.1% vs. 2.4%, p = 0.046) with no significant difference in mortality. The KHFR plans to identify outcomes and risk factors associated with second fracture by conducting a 10-year cohort study, with a follow-up every year, using 5,841 baseline participants.Trial registrationPresent study was registered on Internet-based Clinical Research and Trial management system (iCReaT) as multicenter prospective observational cohort study (Project number: C160022, Date of registration: 22th, Apr, 2016).

Integration of clinical trial development in hematology and oncology fellowship training: Washington university school of medicine experience.

11012 Background: Education in clinical trial design and development is highly variable among Hematology and Medical oncology fellowship programs. The Clinical Trial Development (CTD) program at Washington University in St. Louis (WUSM) is an experiential learning curriculum designed to provide a structured and personalized education to fellows about clinical investigation in Hematology and Oncology. We describe the results of the CTD program and its impact on subsequent academic faculty appointments. Methods: The CTD program was initiated at WUSM in 2002 as a hands-on learning experience for Hematology and Oncology fellows in the design, implementation, evaluation, and publication of clinical trials. Each fellow was required to identify a mentor in their first year of training and propose at least one CTD project, determined as a prospective investigator-initiated clinical trial involving human subjects or materials. Outcome data were collected from an internal registry of fellow CTD projects, Clinical Trials Management System (OnCore), PubMed, ClinicalTrials.gov and e-mail inquiries to fellows and mentors. Descriptive statistics were collected for the characteristics of CTD projects, including the phase of study, site (single center or multicenter), disease subtype, projects that received IRB approval, and projects that resulted in publication. Logistic regression and odds ratios (OR) were also used to assess the association between these characteristics and academic faculty appointments. Results: We included 118 fellows who began fellowship from 2002 to 2021 for this analysis with 16 still in training. Many trials were phase I/II (n = 53; 45%), phase I (n = 34; 29%) and phase II trials (n = 17; 14%) and most trials were single center studies (n = 93; 79%). Disease types of the investigations were evenly distributed between Oncology (n = 60, 51%) or Hematology (n = 58, 49%). Most fellows were successful in obtaining IRB approval for their CTD project (n = 93, 79%) and approximately two thirds of those with IRB approval went on to publish their results in peer-reviewed journals (n = 60, 65%). Forty-five percent of fellows who published their CTD projects were first authors (n = 27) and 38% published in journals with an impact factor of greater than 10. Among the graduating fellows, two-thirds (n = 67, 66%) secured an academic faculty appointment. Fellows with IRB approved CTD projects had significantly higher odds of obtaining an academic faculty appointment (OR 4.96, 95% CI 1.54-15.98, p < 0.05). Conclusions: The CTD program is a well-established clinical investigation program for fellows with a track record of success and impact on subsequent academic faculty appointments. The CTD program is a model that other fellowship programs can emulate for education related to clinical trials.

Development of an integrated and comprehensive clinical trial process management system

BackgroundThe process of initiating and completing clinical drug trials in hospital settings is highly complex, with numerous institutional, technical, and record-keeping barriers. In this study, we independently developed an integrated clinical trial management system (CTMS) designed to comprehensively optimize the process management of clinical trials. The CTMS includes system development methods, efficient integration with external business systems, terminology, and standardization protocols, as well as data security and privacy protection.MethodsThe development process proceeded through four stages, including demand analysis and problem collection, system design, system development and testing, system trial operation, and training the whole hospital to operate the system. The integrated CTMS comprises three modules: project approval and review management, clinical trial operations management, and background management modules. These are divided into seven subsystems and 59 internal processes, realizing all the functions necessary to comprehensively perform the process management of clinical trials. Efficient data integration is realized through extract-transform-load, message queue, and remote procedure call services with external systems such as the hospital information system (HIS), laboratory information system (LIS), electronic medical record (EMR), and clinical data repository (CDR). Data security is ensured by adopting corresponding policies for data storage and data access. Privacy protection complies with laws and regulations and de-identifies sensitive patient information.ResultsThe integrated CTMS was successfully developed in September 2015 and updated to version 4.2.5 in March 2021. During this period, 1388 study projects were accepted, 43,051 electronic data stored, and 12,144 subjects recruited in the First Affiliated Hospital, Zhejiang University School of Medicine.ConclusionThe developed integrated CTMS realizes the data management of the entire clinical trials process, providing basic conditions for the efficient, high-quality, and standardized operation of clinical trials.

Abstract 2068: MCAP Explore: A self-service data exploration and cohort building tool for oncologists

Abstract The goal of the described work was to create a self-service tool for data exploration and cohort creation, facilitating feasibility assessments for research studies and providing insights into the primary clinical and demographic characteristics of the Moffitt patient population. The Moffitt Cancer Analytics Platform (MCAP) was designed to enable seamless end-to-end data lifecycle management, promote data democratization, and reduce data duplication by feeding diverse, typically siloed local data streams into a central data repository. Eight distinct sources including the Moffitt electronic medical record, cancer registry, billing systems and clinical trial management system feed into an Amazon S3-based data lake. Raw data are cleaned, standardized for research use, and stored in the enterprise data warehouse in Snowflake. To date, over 80 distinct tables and 2,200 data elements are captured, representing over 500,000 patients. To provide transparency into these data assets, Moffitt partnered with phData to create a custom tool for data self-service, MCAP Explore. Built on the Sigma cloud analytic platform, Explore is a highly customized interactive workbook that allows the user to filter the total patient population on a broad range of clinical and demographic characteristics to identify cohorts of interest, with applications ranging from research study feasibility assessments to operational oversight of the composition of the patient population and where disparities may exist in disease characteristics, treatment or outcomes. In addition, the user is able to view a broad range of visualizations summarizing the resulting cohort and deep-dive into the specific records available. The features that distinguish Explore from similar tools include: a) the broad range of data domains covered by the available filters (demographics, diagnoses, appointments, labs/vitals, treatment, study enrollment/consent, patient-reported, biospecimens, molecular); b) the ability to apply any number of filters in an arbitrary order, on data that is both one-to-one and many-to-one with the patient, while maintaining important linkages between record types; c) full customization of the product for our oncology-specific use cases, facilitating transparency into the underlying data model and flexibility for future expansion; d) no data being required to leave the Moffitt environment, and de-identification processes governed at an institutional level and applied within Snowflake being automatically inherited within Explore by connection to our institutional Active Directory accounts and Snowflake user roles. We will present detailed examples of tool functionality and describe the underlying data model and design decisions required to accommodate a broad range of complex oncology-specific use cases. In addition, we will present early usage metrics and next steps for expansion into new data domains including imaging. Citation Format: Rachel Howard, Phillip Reisman, Patricia Lewis, Rodrigo Carvajal, Chandan Challa, Mark Ruesink, Joe McFarren, Katrina Johnson, Mukund Sridhar, Kedar Kulkarni, Dana E. Rollison. MCAP Explore: A self-service data exploration and cohort building tool for oncologists [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2068.

Decentralized research technology use in multicenter clinical research studies based at U.S. academic research centers.

During the COVID-19 pandemic, research organizations accelerated adoption of technologies that enable remote participation. Now, there's a pressing need to evaluate current decentralization practices and develop appropriate research, education, and operations infrastructure. The purpose of this study was to examine current adoption of decentralization technologies in a sample of clinical research studies conducted by academic research organizations (AROs). The setting was three data coordinating centers in the U.S. These centers initiated coordination of 44 clinical research studies during or after 2020, with national recruitment and enrollment, and entailing coordination between one and one hundred sites. We determined the decentralization technologies used in these studies. We obtained data for 44/44 (100%) trials coordinated by the three centers. Three technologies have been adopted across nearly all studies (98-100%): eIRB, eSource, and Clinical Trial Management Systems. Commonly used technologies included e-Signature (32/44, 73%), Online Payments Portals (26/44, 59%), ePROs (23/44, 53%), Interactive Response Technology (22/44, 50%), Telemedicine (19/44, 43%), and eConsent (18/44, 41%). Wearables (7/44,16%) and Online Recruitment Portals (5/44,11%) were less common. Rarely utilized technologies included Direct-to-Patient Portals (1/44, 2%) and Home Health Nurse Portals (1/44, 2%). All studies incorporated some type of decentralization technology, with more extensive adoption than found in previous research. However, adoption may be strongly influenced by institution-specific IT and informatics infrastructure and support. There are inherent needs, responsibilities, and challenges when incorporating decentralization technology into a research study, and AROs must ensure that infrastructure and informatics staff are adequate.

Research unit network (RUN) as a learning research system

The clinical research units (CRUs) are one of the main spaces where both translational research and science take place. However, there is a lack of information about both best practices for CRU operations and, ultimately, benchmarks to evaluate CRU performance. The Research Unit Network (RUN) was created with the purpose to enable direct communication and collaboration among CRUs. An online survey was administered to further illustrate the functionality and impact of RUN. Thirty-one individual survey responses (39.2%) were included in the final analysis. The members value RUN monthly meetings (87.1%) as the most useful aspect of this network and CRU budgeting (67.7%) and staffing (61.3%) were the most relevant topics discussed. This is followed by EPIC - Research (58.1%), delegation of authority logs, unit signatures, and policies (51.6%), COVID-19 pandemic response (41.9%), the implementation of clinical trial management system (29.0%), and protocol deviations (19.4%). The intermediate goal of RUN is to identify best practices CRUs are establishing, implementing, and sharing these experiences with the goal to adopt them in different CRUs. The network's long-term goal is to establish standard benchmarks that can be used for evaluating the performance of CRUs across the nation.

Epidemiology and Clinical Characteristics of Hemophilia in Korea - Report of the Korean Bleeding Disorder Registry (KBDR)

Background: Hemophilia is the rare bleeding disorders. To investigate the epidemiology, natural history and medical environment of hemophilia, the patient registry is the pivotal research design. Many developed countries have their own registry data and published valuable clinical data on the bleeding disorders. For now, there was no nationwide bleeding disorder registry except for the data from the registration program of Korea Hemophilia Foundation (KHF). We developed the first registry for the bleeding disorders in Korea with the funding from the Korean Society of Pediatric Hemato-Oncology (KSPHO) and KHF. We reported the initial interim results on the registry at International Conference of Korean Society of Hematology (ICKSH) in Apr 2022. Here we report the follow-up results on the hemophilia from the registry Method: We developed the registry platform using iCReaT(Internet based Clinical Research and Trial management system) operated by National Institute of Health in Korea. The registry was designed as the combined retrospective and prospective study for bleeding disorders. At the first stage we first collected data in retrospective fashion to overview the clinical status and epidemiology of bleedingdisorders in Korea. The data was collected under the approval of Institutional Review Board at each participating institution. Results: As of July 2022, total 625 patients were registered and this is about 1 of thirds of the population of hemophilia in Korea. The current age of this cohort was mean 29.7 ± 19.9, median 26.5 [IQR, 12.7;44.1] years old. Geographic distribution was Seoul (142, 22.7%), Gyunggi (133, 21.3%), Gwangju (101, 16.1%), Chonnam (96, 15.4%), Inchon 53 (8.4%), Ulsan 18 (2.9%) and others. The types of hemophilia were hemophilia A (409, 65.4%), hemophilia B (164, 26.4%), factor 7 deficiency 17 (2.7%), hemophilia C (15, 2.4%), and others. For the severity of hemophilia, 56.7% and 47.0% of hemophilia A and B were severe hemophilia, respectively. In 431 patients, only 50 patients (8%) had genetic variant information. For proportion of prophylaxis, 68.7% of hemophilia A and 51.8% of hemophilia B received prophylaxis. Total 109 patients underwent joint operation for arthropathy. For viral infection, the patients had hepatitis C in 127, hepatitis B in 59 patients and HIV in 4 patients. Conclusion: In this interim analysis of registry, 625 patients were registered. We described the baseline characteristics of hemophilia registry. This registry data will contribute the better understating on the detailed features of hemophilia in Korea and be cornerstone for further clinical studies to improve survival and quality of life of hemophilia.

Re-engineering Clinical Trial Management System Using Blockchain Technology

Re-engineering Clinical Trial Management System Using Blockchain Technology

Re-engineering a Clinical Trial Management System Using Blockchain Technology: System Design, Development, and Case Studies.

BackgroundA clinical trial management system (CTMS) is a suite of specialized productivity tools that manage clinical trial processes from study planning to closeout. Using CTMSs has shown remarkable benefits in delivering efficient, auditable, and visualizable clinical trials. However, the current CTMS market is fragmented, and most CTMSs fail to meet expectations because of their inability to support key functions, such as inconsistencies in data captured across multiple sites. Blockchain technology, an emerging distributed ledger technology, is considered to potentially provide a holistic solution to current CTMS challenges by using its unique features, such as transparency, traceability, immutability, and security.ObjectiveThis study aimed to re-engineer the traditional CTMS by leveraging the unique properties of blockchain technology to create a secure, auditable, efficient, and generalizable CTMS.MethodsA comprehensive, blockchain-based CTMS that spans all stages of clinical trials, including a sharable trial master file system; a fast recruitment and simplified enrollment system; a timely, secure, and consistent electronic data capture system; a reproducible data analytics system; and an efficient, traceable payment and reimbursement system, was designed and implemented using the Quorum blockchain. Compared with traditional blockchain technologies, such as Ethereum, Quorum blockchain offers higher transaction throughput and lowers transaction latency. Case studies on each application of the CTMS were conducted to assess the feasibility, scalability, stability, and efficiency of the proposed blockchain-based CTMS.ResultsA total of 21.6 million electronic data capture transactions were generated and successfully processed through blockchain, with an average of 335.4 transactions per second. Of the 6000 patients, 1145 were matched in 1.39 seconds using 10 recruitment criteria with an automated matching mechanism implemented by the smart contract. Key features, such as immutability, traceability, and stability, were also tested and empirically proven through case studies.ConclusionsThis study proposed a comprehensive blockchain-based CTMS that covers all stages of the clinical trial process. Compared with our previous research, the proposed system showed an overall better performance. Our system design, implementation, and case studies demonstrated the potential of blockchain technology as a potential solution to CTMS challenges and its ability to perform more health care tasks.

Overcoming racial disparities in cancer clinical trial enrollment of Asians and Native Hawaiians

BackgroundAsians and Native Hawaiians are two of the fastest growing minority populations in the United States, however these racial minority groups are severely underrepresented in clinical trials. This study looks at cancer clinical trial accrual among Asians and Native Hawaiians in a community-based network with a mission of increasing minority accrual to studies. MethodsThe University of Hawaii Cancer Center (UHCC) network enrolls patients to treatment and non-treatment cancer studies. Enrollment on studies opened between 2009 and 2013 were obtained from UHCC's clinical trial management system. Incidence of cancer by race was acquired from the Hawaii Tumor Registry. Enrollment fractions were compared for the most common races in the state: White, Asian (specifically Chinese, Filipino, Japanese), and Native Hawaiian. ResultsWhites comprised the largest proportion of cancer patients and participants in trials. Asians and Native Hawaiians were enrolled into cancer clinical trials at the same or higher enrollment fraction compared to Whites. Chinese, Japanese, and Native Hawaiian patients participated in treatment trials significantly more often than Whites (p < 0.05). Similarly, Chinese and Native Hawaiians enrolled in non-treatment trials at a significantly higher rate compared to Whites (p < 0.05). ConclusionsThe UHCC network has instituted many strategies to increase minority accrual that have likely led to Asian and Native Hawaiian patients participating in studies at least as often as White patients. The strategies implemented at UHCC may benefit similar communities with a high number of minority cancer patients.

Re-engineering Clinical Trial Management System Using Blockchain Technology

&nbsp; The annual ConV2X is a leading international health tech symposium driving real world evidence, strategy, research, operations and trends to create a blueprint for a new digital health era. The 2021 symposium&nbsp;featured a scientific program of academic/research presentations in addition to business and industry talks. The research track&nbsp;focused on exploring and sharing developments in blockchain and emerging technologies in health and clinical medicine. Submissions were based on original research, conceptual frameworks, proposed applications, position papers, case studies, and real-world implementation. Selection was based on a peer-review process. Faculty, students, and industry researchers were encouraged to submit abstracts to present&nbsp;ideas before an informed and knowledgeable audience of industry leaders, policy makers, funders, and researchers. This presentation was selected by the scientific review committee. Submission Review Committee Dave Kochalko, CEO of ARTiFACTS Anjum Khurshid, UT Austin Carlos Caldas, UT Engineering Gil Alterovitz, Harvard Medical School Kayo Fujimoto, UT Health Houston Lei Zhang, University of Glasglow Sean Manion, CSciO of ConsenSys Health Vijayakuman Varadarajan, University of South Wales Vikram Dhillon, Wayne State University Yuichi Ikeda, Kyoto University

An integrated approach to improve clinical trial efficiency: Linking a clinical trial management system into the Research Integrated Network of Systems.

Low-accruing clinical trials delay translation of research breakthroughs into the clinic, expose participants to risk without providing meaningful clinical insight, increase the cost of therapies, and waste limited resources. By tracking patient accrual, Clinical and Translational Science Awards hubs can identify at-risk studies and provide them the support needed to reach recruitment goals and maintain financial solvency. However, tracking accrual has proved challenging because relevant patient- and protocol-level data often reside in siloed systems. To address this fragmentation, in September 2020 the South Carolina Clinical and Translational Research Institute, with an academic home at the Medical University of South Carolina, implemented a clinical trial management system (CTMS), with its access to patient-level data, and incorporated it into its Research Integrated Network of Systems (RINS), which links study-level data across disparate systems relevant to clinical research. Within the first year of CTMS implementation, 324 protocols were funneled through CTMS/RINS, with more than 2600 participants enrolled. Integrated data from CTMS/RINS have enabled near-real-time assessment of patient accrual and accelerated reimbursement from industry sponsors. For institutions with bioinformatics or programming capacity, the CTMS/RINS integration provides a powerful model for tracking and improving clinical trial efficiency, compliance, and cost-effectiveness.

The Successful Synchronized Orchestration of an Investigator-Initiated Multicenter Trial Using a Clinical Trial Management System and Team Approach: Design and Utility Study

BackgroundAs the cost of clinical trials continues to rise, novel approaches are required to ensure ethical allocation of resources. Multisite trials have been increasingly utilized in phase 1 trials for rare diseases and in phase 2 and 3 trials to meet accrual needs. The benefits of multisite trials include easier patient recruitment, expanded generalizability, and more robust statistical analyses. However, there are several problems more likely to arise in multisite trials, including accrual inequality, protocol nonadherence, data entry mistakes, and data integration difficulties.ObjectiveThe Biostatistics & Data Science department at the University of Kansas Medical Center developed a clinical trial management system (comprehensive research information system [CRIS]) specifically designed to streamline multisite clinical trial management.MethodsA National Institute of Child Health and Human Development–funded phase 3 trial, the ADORE (assessment of docosahexaenoic acid [DHA] on reducing early preterm birth) trial fully utilized CRIS to provide automated accrual reports, centralize data capture, automate trial completion reports, and streamline data harmonization.ResultsUsing the ADORE trial as an example, we describe the utility of CRIS in database design, regulatory compliance, training standardization, study management, and automated reporting. Our goal is to continue to build a CRIS through use in subsequent multisite trials. Reports generated to suit the needs of future studies will be available as templates.ConclusionsThe implementation of similar tools and systems could provide significant cost-saving and operational benefit to multisite trials.Trial RegistrationClinicalTrials.gov NCT02626299; https://tinyurl.com/j6erphcj

FIMED: Flexible management of biomedical data

Background and objectives: In the last decade, clinical trial management systems have become an essential support tool for data management and analysis in clinical research. However, these clinical tools have design limitations, since they are currently not able to cover the needs of adaptation to the continuous changes in the practice of the trials due to the heterogeneous and dynamic nature of the clinical research data. These systems are usually proprietary solutions provided by vendors for specific tasks. In this work, we propose FIMED, a software solution for the flexible management of clinical data from multiple trials, moving towards personalized medicine, which can contribute positively by improving clinical researchers quality and ease in clinical trials.Methods: This tool allows a dynamic and incremental design of patients’ profiles in the context of clinical trials, providing a flexible user interface that hides the complexity of using databases. Clinical researchers will be able to define personalized data schemas according to their needs and clinical study specifications. Thus, FIMED allows the incorporation of separate clinical data analysis from multiple trials.Results: The efficiency of the software has been demonstrated by a real-world use case for a clinical assay in Melanoma disease, which has been indeed anonymized to provide a user demonstration. FIMED currently provides three data analysis and visualization components, guaranteeing a clinical exploration for gene expression data: heatmap visualization, clusterheatmap visualization, as well as gene regulatory network inference and visualization. An instance of this tool is freely available on the web at https://khaos.uma.es/fimed. It can be accessed with a demo user account, “researcher”, using the password “demo”.Conclusion: This paper shows FIMED as a flexible and user-friendly way of managing multidimensional clinical research data. Hence, without loss of generality, FIMED is flexible enough to be used in the context of any other disease where clinical data and assays are involved.

The Multiple Myeloma Research Consortium (MMRC): A Model For Accelerating Development Of Novel Therapies For Multiple Myeloma

The Multiple Myeloma Research Consortium (MMRC): A Model For Accelerating Development Of Novel Therapies For Multiple Myeloma

Development of a Good Clinical Practice inspection checklist to assess clinical trial sites in Vietnam

BackgroundAssessing the capacity of a healthcare institution to conduct and manage clinical research studies is challenging, especially in developing countries where resources are limited. The objective of this study was...

Decreased enrollment of patients with advanced lobular breast cancer compared to ductal breast cancer in interventional clinical trials.

1092 Background: Response Evaluation Criteria in Solid Tumors (RECIST) criteria are often used to measure tumor response in cancer trials, especially in the stage IV setting. However, RECIST requires measurable disease, which is less common in invasive lobular breast carcinoma (ILC) of the breast, a diffusely growing tumor type, compared to invasive ductal carcinoma (IDC). We examined the prevalence of RECIST in breast cancer clinical trials, and whether there are differential trial enrollment rates by histology and stage. Methods: We analyzed the clinicaltrials.gov database to evaluate the proportion of interventional, stage IV clinical trials that require measurable disease as inclusion criteria or outcome measures. We then performed an institutional cohort study comparing the proportion of patients in the University of California, San Francisco (UCSF) OnCore clinical trials management system (CTMS) to the UCSF Cancer Registry between 2000-2018, stratified by histology and stage. We hypothesized that the proportion of patients with ILC in the CTMS would be significantly lower than in the cancer registry. Results: There were 146 actively-recruiting, interventional clinical trials for stage IV breast cancer that were identified in our search on clinicaltrials.gov. Overall, 108 (74%) required measurable disease for study participation. The UCSF Cancer Registry included 8,679 patients, while the UCSF OnCore CTMS included 1,511 patients (Table). In those with early stage disease, where RECIST is not typically used, there was no difference in the proportion of ILC patients enrolled in clinical trials versus in the cancer registry. However, among those with stage IV disease, there was a significantly lower proportion of patients with ILC in the CTMS than in the cancer registry (9.2% versus 17.9%, p = 0.005). In contrast, patients with stage IV IDC were overrepresented in the clinical trials database compared to the cancer registry. Conclusions: Patients with metastatic ILC were significantly less likely to be enrolled in clinical trials than those with metastatic IDC. This decreased enrollment may be due to the widespread use of RECIST, and further investigation is needed to ensure equity in access to clinical trials.[Table: see text]

Construction of data remote monitoring and auditing system for clinical trials

Clinical trial management system is independently developed by our hospital, which basically realized the whole process management and data collection of clinical trials. Based on the platform, the functional architecture of data remote monitoring and auditing was established. By desensitizing and encrypting of data, the project and subject hologram were visualized to facilitate to review of data. The data remote monitoring and auditing cloud platform adopts the B/S architecture pattern. Users register to apply for an account through the cloud platform, and access to the account via HTTPS security protocol. The authorized users were able to view the relevant items online to ensure the secure data transmission and easy operating. The electronic management of data is the direction of future efforts. By compliance with laws and regulations, the remote monitoring/auditing can be realized, and the data security and personal privacy can be ensured with the application of information technology. In this paper, the feasibility of remote monitoring/auditing mode is explored, specific technical schemes and system functions are suggested, and the realization scenarios are conceived in case of major public health emergencies.

Abstract 3382: MatchMiner: An open-source computational platform for genomically-driven matching of cancer patients to precision medicine clinical trials

Abstract To facilitate interpretation of complex tumor sequencing data and clinical trial genomic eligibility criteria, we developed MatchMiner, an open-source platform to computationally match cancer patients to precision medicine clinical trials based on clinical and genomic features. MatchMiner supports two distinct workflows: (1) patient-centric mode, in which an oncologist can find clinical trial matches for a specific patient, and (2) trial-centric mode, in which a clinical trial investigator can identify and recruit patients for a specific trial. MatchMiner has been operational at Dana-Farber Cancer Institute since early 2017. There are currently 275+ trials curated in the system and genomic data from 26,000+ patients. Over 80% of living patients match to at least one open clinical trial, with an average of 6 trial matches per patient. At least 98 patients have enrolled on a clinical trial as a result of MatchMiner. To enable computational matching, we developed clinical trial markup language (CTML), a structured format to encode detailed information about a trial. CTML utilizes boolean logic to define clinical (e.g. cancer type), demographic (e.g. age) and genomic (e.g. specific mutations, copy number alterations, structural variants or mutational signatures) eligibility, which can be applied to individual arms of a trial. MatchMiner is an open-source two-tier web application with a Python-based REST API server and an AngularJS front-end. MatchMiner utilizes Security Assertion Markup Language (SAML)-based authentication and is fully HIPAA-compliant when hosted behind a secure institutional firewall. MatchMiner ingests clinical and genomic data, and connects to existing clinical systems, including clinical trial management systems for real-time trial status. We recently refactored the core matching algorithm (the matchengine), which improves upon the original matchengine in several ways: (1) increased granularity in reporting the reason for a match; (2) can match all patients/trials or individual patients/trials; (3) easily extensible to match based on additional data types. The MatchMiner open-source software package is available through GitHub (https://github.com/dfci/matchminer). We are committed to supporting MatchMiner as an open-source software; to our knowledge, at least five cancer centers are implementing MatchMiner at their own institutions. In summary, we have defined a standard for encoding clinical trial information in a structured and computable form, and we have developed an open-source computational trial matching platform to support patient-specific trial identification as well as trial-specific patient recruitment. We are actively collaborating with clinical groups at Dana-Farber Cancer Institute and other institutions to understand the role of MatchMiner in their clinical workflows, and we are committed to continuing to evolve MatchMiner to meet clinical needs. Citation Format: Tali Mazor, Rachel B. Keller, Priti Kumai, James Lindsay, Eric Marriott, Andrea Ovalle, Ethan Siegel, Joyce Yu, Michael Hassett, Ethan Cerami. MatchMiner: An open-source computational platform for genomically-driven matching of cancer patients to precision medicine clinical trials [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3382.