Exploiting Distributed, Heterogeneous and Sensitive Data Stocks while Maintaining the Owner’s Data Sovereignty

Profile of the multicenter cohort of the German Cancer Consortium's Clinical Communication Platform

Treatment concepts in oncology are becoming increasingly personalized and diverse. Successively, changes in standards of care mandate continuous monitoring of patient pathways and clinical outcomes based on large, representative real-world data. The German Cancer Consortium's (DKTK) Clinical Communication Platform (CCP) provides such opportunity. Connecting fourteen university hospital-based cancer centers, the CCP relies on a federated IT-infrastructure sourcing data from facility-based cancer registry units and biobanks. Federated analyses resulted in a cohort of 600,915 patients, out of which 232,991 were incident since 2013 and for which a comprehensive documentation is available. Next to demographic data (i.e., age at diagnosis: 2.0% 0-20 years, 8.3% 21-40 years, 30.9% 41-60 years, 50.1% 61-80 years, 8.8% 81+ years; and gender: 45.2% female, 54.7% male, 0.1% other) and diagnoses (five most frequent tumor origins: 22,523 prostate, 18,409 breast, 15,575 lung, 13,964 skin/malignant melanoma, 9005 brain), the cohort dataset contains information about therapeutic interventions and response assessments and is connected to 287,883 liquid and tissue biosamples. Focusing on diagnoses and therapy-sequences, showcase analyses of diagnosis-specific sub-cohorts (pancreas, larynx, kidney, thyroid gland) demonstrate the analytical opportunities offered by the cohort's data. Due to its data granularity and size, the cohort is a potential catalyst for translational cancer research. It provides rapid access to comprehensive patient groups and may improve the understanding of the clinical course of various (even rare) malignancies. Therefore, the cohort may serve as a decisions-making tool for clinical trial design and contributes to the evaluation of scientific findings under real-world conditions.

Outbound Data Legality Analysis in CPTPP Countries under the Environment of Cross-Border Data Flow Governance

The governance of cross-border data flows around the digital economy, data security, and data sovereignty has become a crucial global governance issue. This paper evaluates the legitimacy of data exit rules of CPTPP countries based on machine learning algorithm models under the perspective of cross-border data flow governance. In this study, four machine learning algorithms, namely, logistic regression, decision tree, random forest, and GBDT, are used to build an outbound data assessment and evaluation model. The confusion matrix is used to classify the outbound data legitimacy dichotomously. The recall, precision, and F1 scores are evaluated to compare the empirical results of each model. Based on this, a logistic regression-based outbound data risk scoring model is introduced to quantify the outbound data risk at a deeper level and to classify the outbound data risk level for the reference of regulators to make more scientific and reasonable decisions. The experimental results show that the machine learning models can meet the needs and applications of practical work and make accurate predictions of outbound data risks.

The DKTK EXLIQUID consortium – exploiting liquid biopsies to advance cancer precision medicine for molecular tumor board patients

Testing for genetic alterations in tumor tissue allows clinicians to identify patients who most likely will benefit from molecular targeted treatment. EXLIQUID – exploiting liquid biopsies to advance cancer precision medicine – investigates the potential of additional non-invasive tools for guiding therapy decisions and monitoring of advanced cancer patients. The term “liquid biopsy” (LB) refers to non-invasive analysis of tumor-derived circulating material such as cell-free DNA in blood samples from cancer patients. Although recent technological advances allow sensitive and specific detection of LB biomarkers, only few LB assays have entered clinical routine to date. EXLIQUID is a German Cancer Consortium (DKTK)-wide joint funding project that aims at establishing LBs as a minimally-invasive tool to analyze molecular changes in circulating tumor DNA (ctDNA). Here, we present the structure, clinical aim, and methodical approach of the new DKTK EXLIQUID consortium. Within EXLIQUID, we will set up a multicenter repository of high-quality LB samples from patients participating in DKTK MASTER and local molecular tumor boards, which use molecular profiles of tumor tissues to guide targeted therapies. We will develop LB assays for monitoring of therapy efficacy by the analysis of tumor mutant variants and tumor-specific DNA methylation patterns in ctDNA from these patients. By bringing together LB experts from all DKTK partner sites and exploiting the diversity of their particular expertise, complementary skills and technologies, the EXLIQUID consortium addresses the challenges of translating LBs into the clinic. The DKTK structure provides EXLIQUID a unique position for the identification of liquid biomarkers even in less common tumor types, thereby extending the group of patients benefitting from non-invasive LB testing. Besides its scientific aims, EXLIQUID is building a valuable precision oncology cohort and LB platform which will be available for future collaborative research studies within the DKTK and beyond.

The journey to establishing an IT-infrastructure within the German Biobank Alliance

Background

Biobanks ensure the long-term storage and accessibility of biospecimens and corresponding data sets. Thus, they form the foundation for many research projects which may contribute to improving medical care. With the establishment of the German Biobank Node and Alliance, expertise in biobanking is bundled and strengthened. An important component within this research infrastructure is the set-up of an information technology (IT) network for allowing feasibility requests across individual biobanks.

Objective

We aim to describe relevant aspects that have shaped the journey to interconnect biobanks, to enhance their visibility within the research-community, to harmonize data, and to enable feasibility searches to support access to available data and biosamples.

Methods

To achieve this task, we resorted to a wide variety of methods: we ran a requirement analysis, decided on the mode of operation for the federated team of IT-developers and on the development approach itself, took related national and international initiatives into account, and concluded with evaluations of the developed software artefacts and the operation of the entire chain of applications.

Results

We drew an IT framework including all heterogeneous data aspects derived from our requirement analysis and developed a comprehensive IT infrastructure. The successful implementation benefited from a smooth interaction of a federated IT team distributed across all participating sites that was even able to manage a major technology change mid-project. Authentication and project management services from associated partners could be integrated and the graphic user interface for an intuitive search tool for biospecimens was designed iteratively. The developed code is open source to ensure sustainability and the local implementation is concluded and functioning. The evaluation of the components was positive.

Conclusions

The entire project had given ample opportunity for challenges, predictable and unpredictable—from the mode of operation to changing some of the initial ideas. We learned our lessons concerning personnel, budget planning and technical as well as manual monitoring as well as some requirements arising only during the process of the project. Nevertheless, we can here report a success story of a network infrastructure, highly agile and much easier in local installation than initially anticipated.

BBMRI-ERIC Negotiator: Implementing Efficient Access to Biobanks

Various biological resources, such as biobanks and disease-specific registries, have become indispensable resources to better understand the epidemiology and biological mechanisms of disease and are fundamental for advancing medical research. Nevertheless, biobanks and similar resources still face significant challenges to become more findable and accessible by users on both national and global scales. One of the main challenges for users is to find relevant resources using cataloging and search services such as the BBMRI-ERIC Directory, operated by European Research Infrastructure on Biobanking and Biomolecular Resources (BBMRI-ERIC), as these often do not contain the information needed by the researchers to decide if the resource has relevant material/data; these resources are only weakly characterized. Hence, the researcher is typically left with too many resources to explore and investigate. In addition, resources often have complex procedures for accessing holdings, particularly for depletable biological materials. This article focuses on designing a system for effective negotiation of access to holdings, in which a researcher can approach many resources simultaneously, while giving each resource team the ability to implement their own mechanisms to check if the material/data are available and to decide if access should be provided. The BBMRI-ERIC has developed and implemented an access and negotiation tool called the BBMRI-ERIC Negotiator. The Negotiator enables access negotiation to more than 600 biobanks from the BBMRI-ERIC Directory and other discovery services such as GBA/BBMRI-ERIC Locator or RD-Connect Finder. This article summarizes the principles that guided the design of the tool, the terminology used and underlying data model, request workflows, authentication and authorization mechanism(s), and the mechanisms and monitoring processes to stimulate the desired behavior of the resources: to effectively deliver access to biological material and data.

ViBiBa: Virtual BioBanking for the DETECT multicenter trial program - decentralized storage and processing

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ViBiBa is an open-source sample banking tool.

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ViBiBa was purpose built for liquid biopsy specimen.

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ViBiBa allows for decentralized storage while promoting collaboration.

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ViBiBa's plugin support requires no change in existing data structures.

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ViBiBa empowers translational research projects and cohort formation.

Background

Liquid Biopsy (LB) in the form of e.g., circulating tumor cells (CTCs) is a promising non-invasive approach to support current therapeutic cancer management. However, the proof of clinical utility of CTCs in informing therapeutic decision-making for e.g., breast cancer in clinical trials and associated translational research projects is facing the issues of low CTC positivity rates and low CTC numbers – even in the metastasized situation. To compensate for this dilemma, clinical CTC trials are designed as large multicenter endeavors with decentralized sample collection, processing and storage of products, making data management highly important to enable high-quality translational CTC research.

Aim

In the DETECT clinical CTC trials we aimed at developing a custom-made, browser-based virtual database to harmonize and organize both decentralized processing and storage of LB specimens and to enable the collection of clinically meaningful LB sample.

Methods

ViBiBa processes data from various sources, harmonizes the data and creates an easily searchable multilayered database.

Results

An open-source virtual bio-banking web-application termed ViBiBa was created, which automatically processes data from multiple non-standardized sources. These data are automatically checked and merged into one centralized databank and are providing the opportunity to extract clinically relevant patient cohorts and CTC sample collections.

Summary

ViBiBa, which is a highly flexible tool that allows for decentralized sample storage of liquid biopsy specimens, facilitates a solution which promotes collaboration in a user-friendly, federalist and highly structured way. The source code is available under the MIT license from https://vibiba.com or https://github.com/asperciesl/ViBiBa

Enabling External Inquiries to an Existing Patient Registry by Using the Open Source Registry System for Rare Diseases: Demonstration of the System Using the European Society for Immunodeficiencies Registry

BACKGROUND

The German Network on Primary Immunodeficiency Diseases (PID-NET) utilizes the European Society for Immunodeficiencies (ESID) registry as a platform for collecting data. In the context of PID-NET data, we show how registries based on custom software can be made interoperable for better collaborative access to precollected data. The Open Source Registry System for Rare Diseases (Open-Source-Registersystem für Seltene Erkrankungen [OSSE], in German) provides patient organizations, physicians, scientists, and other parties with open source software for the creation of patient registries. In addition, the necessary interoperability between different registries based on the OSSE, as well as existing registries, is supported, which allows those registries to be confederated at both the national and international levels.

OBJECTIVE

Data from the PID-NET registry should be made available in an interoperable manner without losing data sovereignty by extending the existing custom software of the registry using the OSSE registry framework.

METHODS

This paper describes the following: (1) the installation and configuration of the OSSE bridgehead, (2) an approach using a free toolchain to set up the required interfaces to connect a registry with the OSSE bridgehead, and (3) the decentralized search, which allows the formulation of inquiries that are sent to a selected set of registries of interest.

RESULTS

PID-NET uses the established and highly customized ESID registry software. By setting up a so-called OSSE bridgehead, PID-NET data are made interoperable according to a federated approach, and centrally formulated inquiries for data can be received. As the first registry to use the OSSE bridgehead, the authors introduce an approach using a free toolchain to efficiently implement and maintain the required interfaces. Finally, to test and demonstrate the system, two inquiries are realized using the graphical query builder. By establishing and interconnecting an OSSE bridgehead with the underlying ESID registry, confederated queries for data can be received and, if desired, the inquirer can be contacted to further discuss any requirements for cooperation.

CONCLUSIONS

The OSSE offers an infrastructure that provides the possibility of more collaborative and transparent research. The decentralized search functionality includes registries into one search application while still maintaining data sovereignty. The OSSE bridgehead enables any registry software to be integrated into the OSSE network. The proposed toolchain to set up the required interfaces consists of freely available software components that are well documented. The use of the decentralized search is uncomplicated to use and offers a well-structured, yet still improvable, graphical user interface to formulate queries.

A Federated Online Search Tool for Biospecimens (Sample Locator): Usability Study

BACKGROUND

The German Biobank Alliance (GBA) aims to establish a cross-site biobank network. For this endeavor, the so-called Sample Locator, a federated search tool for biospecimens and related data, has been developed, forming the heart of its information technology (IT) infrastructure.

OBJECTIVE

To ensure the sustainable use of such a tool, we included researchers as participants in an end user-based usability evaluation.

METHODS

To develop a prototype ready for evaluation, we needed input from GBA IT experts. Thus, we conducted a 2-day workshop with 8 GBA IT team members. The focus was on the respective steps of a user-centered design process. With the acquired knowledge, the participants designed low-fidelity mock-ups. The main ideas of these mock-ups were discussed, extracted, and summarized into a comprehensive prototype using Microsoft PowerPoint. Furthermore, we created a questionnaire concerning the usability of the prototype, including the System Usability Scale (SUS), questions on negative and positive aspects, and typical tasks to be fulfilled with the tool. Subsequently, the prototype was pretested on the basis of this questionnaire with researchers who have a biobank background. Based on this preliminary work, the usability analysis was ultimately carried out with researchers and the results were evaluated.

RESULTS

Altogether, 27 researchers familiar with sample requests evaluated the prototype. The analysis of the feedback certified a good usability, given that the Sample Locator prototype was seen as intuitive and user-friendly by 74% (20/27) of the participants. The total SUS score by the 25 persons that completed the questionnaire was 80.4, indicating good system usability. Still, the evaluation provided useful advice on optimization potential (eg, offering a help function).

CONCLUSIONS

The findings of this usability analysis indicate that the considerations regarding a user-friendly application that have been made in the development process so far strongly coincide with the perception of the study participants. Nevertheless, it was important to engage prospective end users to ensure that the previous development is going in the desired direction and that the Sample Locator will be used in the future. The user comments and suggestions for improvement will be considered in upcoming iterations for refinement.

Liquid materials for biomedical research: a highly IT-integrated and automated biobanking solution

Various information technology (IT) infrastructures for biobanking, networks of biobanks and biomaterial management are described in the literature. As pre-analytical variables play a major role in the downstream interpretation of clinical as well as research results, their documentation is essential. A description for mainly automated documentation of the complete life-cycle of each biospecimen is lacking so far. Here, the example taken is from the University Medical Center Göttingen (UMG), where the workflow of liquid biomaterials is standardized between the central laboratory and the central biobank. The workflow of liquid biomaterials from sample withdrawal to long-term storage in a biobank was analyzed. Essential data such as time and temperature for processing and freezing can be automatically collected. The proposed solution involves only one major interface between the main IT systems of the laboratory and the biobank. It is key to talk to all the involved stakeholders to ensure a functional and accepted solution. Although IT components differ widely between clinics, the proposed way of documenting the complete life-cycle of each biospecimen can be transferred to other university medical centers. The complete documentation of the life-cycle of each biospecimen ensures a good interpretability of downstream routine as well as research results.

Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC

Background  High-quality clinical data and biological specimens are key for medical research and personalized medicine. The Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to facilitate access to such biological resources. The accompanying ADOPT BBMRI-ERIC project kick-started BBMRI-ERIC by collecting colorectal cancer data from European biobanks.

Objectives  To transform these data into a common representation, a uniform approach for data integration and harmonization had to be developed. This article describes the design and the implementation of a toolset for this task.

Methods  Based on the semantics of a metadata repository, we developed a lexical bag-of-words matcher, capable of semiautomatically mapping local biobank terms to the central ADOPT BBMRI-ERIC terminology. Its algorithm supports fuzzy matching, utilization of synonyms, and sentiment tagging. To process the anonymized instance data based on these mappings, we also developed a data transformation application.

Results  The implementation was used to process the data from 10 European biobanks. The lexical matcher automatically and correctly mapped 78.48% of the 1,492 local biobank terms, and human experts were able to complete the remaining mappings. We used the expert-curated mappings to successfully process 147,608 data records from 3,415 patients.

Conclusion  A generic harmonization approach was created and successfully used for cross-institutional data harmonization across 10 European biobanks. The software tools were made available as open source.

Usage control architecture options for data sovereignty in business ecosystems

Purpose

Current business challenges force companies to exchange critical and sensitive data. The data provider pays great attention to the usage of their data and wants to control it by policies. The purpose of this paper is to develop usage control architecture options to enable data sovereignty in business ecosystems.

Design/methodology/approach

The architecture options are developed following the design science research process. Based on requirements from an automotive use case, the authors develop architecture options. The different architecture options are demonstrated and evaluated based on the case study with practitioners from the automotive industry.

Findings

This paper introduces different architecture options for implementing usage control (UC). The proposed architecture options represent solutions for UC in business ecosystems. The comparison of the architecture options shows the respective advantages and disadvantages for data provider and data consumer.

Research limitations/implications

In this work, the authors address only one case stemming from the German automotive sector.

Practical implications

Technical enforcement of data providers policies instead of relying on trust to support collaborative data exchange between companies.

Originality/value

This research is among the first to introduce architecture options that provide a technical concept for the implementation of data sovereignty in business ecosystems using UC. Consequently, it supports the decision process for the technical implementation of data sovereignty.

Modern Information Technology for Cancer Research: What's in IT for Me? An Overview of Technologies and Approaches

Information technology (IT) can enhance or change many scenarios in cancer research for the better. In this paper, we introduce several examples, starting with clinical data reuse and collaboration including data sharing in research networks. Key challenges are semantic interoperability and data access (including data privacy). We deal with gathering and analyzing genomic information, where cloud computing, uncertainties and reproducibility challenge researchers. Also, new sources for additional phenotypical data are shown in patient-reported outcome and machine learning in imaging. Last, we focus on therapy assistance, introducing tools used in molecular tumor boards and techniques for computer-assisted surgery. We discuss the need for metadata to aggregate and analyze data sets reliably. We conclude with an outlook towards a learning health care system in oncology, which connects bench and bedside by employing modern IT solutions.

MIRACUM: Medical Informatics in Research and Care in University Medicine

INTRODUCTION

This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g. OHDSI, PCORnet, eMerge, RD-Connect) MIRACUM is a consortium of academic and hospital partners as well as one industrial partner in eight German cities which have joined forces to create interoperable data integration centres (DIC) and make data within those DIC available for innovative new IT solutions in patient care and medical research.

OBJECTIVES

Sharing data shall be supported by common interoperable tools and services, in order to leverage the power of such data for biomedical discovery and moving towards a learning health system. This paper aims at illustrating the major building blocks and concepts which MIRACUM will apply to achieve this goal.

GOVERNANCE AND POLICIES

Besides establishing an efficient governance structure within the MIRACUM consortium (based on the steering board, a central administrative office, the general MIRACUM assembly, six working groups and the international scientific advisory board), defining DIC governance rules and data sharing policies, as well as establishing (at each MIRACUM DIC site, but also for MIRACUM in total) use and access committees are major building blocks for the success of such an endeavor.

ARCHITECTURAL FRAMEWORK AND METHODOLOGY

The MIRACUM DIC architecture builds on a comprehensive ecosystem of reusable open source tools (MIRACOLIX), which are linkable and interoperable amongst each other, but also with the existing software environment of the MIRACUM hospitals. Efficient data protection measures, considering patient consent, data harmonization and a MIRACUM metadata repository as well as a common data model are major pillars of this framework. The methodological approach for shared data usage relies on a federated querying and analysis concept.

USE CASES

MIRACUM aims at proving the value of their DIC with three use cases: IT support for patient recruitment into clinical trials, the development and routine care implementation of a clinico-molecular predictive knowledge tool, and molecular-guided therapy recommendations in molecular tumor boards.

RESULTS

Based on the MIRACUM DIC release in the nine months conceptual phase first large scale analysis for stroke and colorectal cancer cohorts have been pursued.

DISCUSSION

Beyond all technological challenges successfully applying the MIRACUM tools for the enrichment of our knowledge about diagnostic and therapeutic concepts, thus supporting the concept of a Learning Health System will be crucial for the acceptance and sustainability in the medical community and the MIRACUM university hospitals.

[Registries for rare diseases : OSSE - An open-source framework for technical implementation]

Meager amounts of data stored locally, a small number of experts, and a broad spectrum of technological solutions incompatible with each other characterize the landscape of registries for rare diseases in Germany. Hence, the free software Open Source Registry for Rare Diseases (OSSE) was created to unify and streamline the process of establishing specific rare disease patient registries. The data to be collected is specified based on metadata descriptions within the registry framework's so-called metadata repository (MDR), which was developed according to the ISO/IEC 11179 standard. The use of a central MDR allows for sharing the same data elements across any number of registries, thus providing a technical prerequisite for making data comparable and mergeable between registries and promoting interoperability.With OSSE, the foundation is laid to operate linked patient registries while respecting strong data protection regulations. Using the federated search feature, data for clinical studies can be identified across registries. Data integrity, however, remains intact since no actual data leaves the premises without the owner's consent. Additionally, registry solutions other than OSSE can participate via the OSSE bridgehead, which acts as a translator between OSSE registry networks and non-OSSE registries. The pseudonymization service Mainzelliste adds further data protection.Currently, more than 10 installations are under construction in clinical environments (including university hospitals in Frankfurt, Hamburg, Freiburg and Münster). The feedback given by the users will influence further development of OSSE. As an example, the installation process of the registry for undiagnosed patients at University Hospital Frankfurt is described in more detail.

Strategien zur Vernetzung von Biobanken

Hintergrund

Nicht selten benötigt ein medizinisches Forschungsvorhaben mehr biologisches Material, als in einer einzigen Biobank verfügbar ist. Daher unterstützt eine Vielzahl von Strategien das Auffinden potentieller Forschungspartner mit passenden Proben, auch ohne dass diese zuvor in einer zentralisierten Sammlung zusammengeführt werden müssen.

Ziel

Der vorliegende Beitrag beschreibt die Klassifizierung verschiedener Strategien zur Vernetzung von Biomaterialbanken, speziell zur Probensuche, sowie eine IT-Infrastruktur, die diese Ansätze kombiniert.

Material und Methoden

Bestehende Strategien lassen sich nach drei Kriterien klassifizieren: a) Granularität der Probendaten: grobe Daten auf Bankebene (Katalog) vs. feingranulare Daten auf Probenebene, b) Speicherort der Probendaten: zentrale (zentraler Suchdienst) vs. dezentrale Datenhaltung (föderierte Suchdienste) und c) Automatisierungsgrad: automatisch (abfragebasiert, föderierter Suchdienst) vs. halbautomatisch (anfragebasiert, dezentrale Suche). Alle genannten Suchdienste setzen eine Datenintegration voraus; dabei helfen Metadaten bei der Überwindung semantischer Heterogenität.

Ergebnisse

Der „Common Service IT“ in BBMRI-ERIC („Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium“) vereint einen Katalog, die dezentrale Suche und Metadaten in einer integrierten Plattform, um Forschern vielseitige Werkzeuge zur Suche nach passendem Probenmaterial zu geben und bei den Biobankern gleichzeitig ein hohes Maß an Datenhoheit zu bewahren.

Diskussion

Trotz ihrer Unterschiede schließen sich die vorgestellten Strategien zur Vernetzung von Biomaterialbanken gegenseitig nicht aus. Vielmehr lassen sie sich in gemeinsamen Forschungsinfrastrukturen sinnvoll ergänzen und sie können sogar voneinander profitieren.