App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden.

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74-0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model.

Launch of an Infrastructure for Health Research: BBMRI-ERIC.

Biobanking and BioMolecular resources Research Infrastructure (BBMRI)- European Research Infrastructure Consortium (ERIC) is the largest infrastructure launched in Europe in health research. By nature it is a distributed infrastructure, in which biological samples and data are hosted by the European Member States biobanks. As of today, BBMRI-ERIC consists of 19 European Member States and 1 international organization, the International Agency for Research on Cancer. This means that BBMRI-ERIC has a population of >500 million individuals in Europe. BBMRI-ERIC is a truly Pan-European Research Infrastructure for health research. Given that BBMRI-ERIC is set up to become a key source for users in both academic and scientific institutions as well as in the pharmaceutical and life science industries, it contributes directly to the Innovation Union concept. It is pan-European because BBMRI-ERIC already shows an excellent geographic and regional coverage all over Europe involving countries from South, East, West, North, and Central Europe. BBMRI-ERIC is a service-driven infrastructure for the European Member States, driven by science. The BBMRI-ERIC Directory consists of 100 million samples and a roadmap for better-defined quality in European biobanks for improving reproducibility and reliability of the biological sample and data.

Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health.

The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.

E-Science technologies in a workflow for personalized medicine using cancer screening as a case study.

OBJECTIVE: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings. MATERIALS AND METHODS: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences. RESULTS: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform. DISCUSSION AND CONCLUSION: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.

Toward Global Biobank Integration by Implementation of the Minimum Information About BIobank Data Sharing (MIABIS 2.0 Core).

Biobanks are the biological back end of data-driven medicine, but lack standards and generic solutions for interoperability and information harmonization. The move toward a global information infrastructure for biobanking demands semantic interoperability through harmonized services and common ontologies. To tackle this issue, the Minimum Information About BIobank data Sharing (MIABIS) was developed in 2012 by the Biobanking and BioMolecular Resources Research Infrastructure of Sweden (BBMRI.se). The wide acceptance of the first version of MIABIS encouraged evolving it to a more structured and descriptive standard. In 2013 a working group was formed under the largest infrastructure for health in Europe, Biobanking and BioMolecular Resources Research Infrastructure (BBMRI-ERIC), with the remit to continue the development of MIABIS (version 2.0) through a multicountry governance process. MIABIS 2.0 Core has been developed with 22 attributes describing Biobanks, Sample Collections, and Studies according to a modular structure that makes it easier to adhere to and to extend the standard. This integration standard will make a great contribution to the discovery and exploitation of biobank resources and lead to a wider and more efficient use of valuable bioresources, thereby speeding up the research on human diseases. Many within the European Union have accepted MIABIS 2.0 Core as the "de facto" biobank information standard.

BBMRI-ERIC: the novel gateway to biobanks. From humans to humans.

BBMRI-ERIC, the Biobanking and BioMolecular Resources Research Infrastructure-European Research Infrastructure Consortium, is a new form of umbrella organization for biobanking in Europe. For rare and common diseases alike, it aims at providing fair access to quality-controlled human biological samples and associated biomedical and biomolecular data. Such access enables basic mechanisms underlying diseases to be studied, which is indispensable for the development of new biomarkers and drugs. In the context of the European Research Area (ERA), biobanks, which were identified as a particular European strength, contribute to Europe's cohesion policy through capacity-building in the BBMRI-ERIC member countries.

Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research.

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.

The EuPA Biobank Initiative: Meeting the future challenges of biobanking in proteomics & systems medicine.

In this News & Reviews Discussion, the recently launched EuPA (European Proteomics Association) Biobank Initiative is introduced in the context of current and future challenges in biobanking. The purpose of the initiative is to provide a forumand knowledge platform for integrating the extensive experiences collected by the EuPA community, and link it to the European and international biobanking communities at large. The specific impact of providing a forum and easy access to this type of information to the EuPA community is the potential of improving the quality of future sample collections and biobanks, the quality of the research produced from these sample collections, as well as the output and productivity from existing biobanks. The underutilization of biobanks has recently been identified as an emerging issue of biobankingworldwide. Measures to improve our ability to locate and access appropriate sample collections for a wide range of research purposes may enhance both the scientific quality and biobank sustainability, thereby contributing to the important task of moving our research beyond basic findings and mere publications, into clinical practice. BIOLOGICAL SIGNIFICANCE: This manuscript is intended as a Discussion piece, and represents a recollection of the presentation under the "EuPA Initiative" session at HUPO/EuPA 2014 in Madrid. The launch of the EuPA (European Proteomics Association) Biobank Initiative in the context of current and future challenges in biobanking is discussed. The purpose of the initiative is to provide a forum and knowledge base for integrating the extensive experiences collected by the EuPA community, and link it to the European and international biobanking communities at large. The specific impact of providing a forumand easy access to this type of information to the EuPA community is the potential of improving the quality of future sample collections and biobanks, the quality of the research produced from these sample collections, aswell as the output and productivity fromexisting biobanks. The underutilization of biobanks has recently been identified as a challenge to the well-being and economic sustainability of biobanking worldwide. Measures to improve our ability to localize and access appropriate sample collections for validation studies and other research purposes is thus of benefit bothto scientific quality and biobank sustainability, thereby contributing to the important task of moving our research beyond basic findings and mere publications, into clinical practice. This article is part of a Special Issue entitled: HUPO 2014.

BBMRI-ERIC as a resource for pharmaceutical and life science industries: the development of biobank-based Expert Centres.

Biological resources (cells, tissues, bodily fluids or biomolecules) are considered essential raw material for the advancement of health-related biotechnology, for research and development in life sciences, and for ultimately improving human health. Stored in local biobanks, access to the human biological samples and related medical data for transnational research is often limited, in particular for the international life science industry. The recently established pan-European Biobanking and BioMolecular resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to improve accessibility and interoperability between academic and industrial parties to benefit personalized medicine, disease prevention to promote development of new diagnostics, devices and medicines. BBMRI-ERIC is developing the concept of Expert Centre as public-private partnerships in the precompetitive, not-for-profit field to provide a new structure to perform research projects that would face difficulties under currently established models of academic-industry collaboration. By definition, Expert Centres are key intermediaries between public and private sectors performing the analysis of biological samples under internationally standardized conditions. This paper presents the rationale behind the Expert Centres and illustrates the novel concept with model examples.

Toward a common language for biobanking.

To encourage the process of harmonization, the biobank community should support and use a common terminology. Relevant terms may be found in general thesauri for medicine, legal instruments or specific glossaries for biobanking. A comparison of the use of these sources has so far not been conducted and would be a useful instrument to further promote harmonization and data sharing. Thus, the purpose of the present study was to investigate the preference of definitions important for sharing biological samples and data. Definitions for 10 terms -[human] biobank, sample/specimen, sample collection, study, aliquot, coded, identifying information, anonymised, personal data and informed consent-were collected from several sources. A web-based questionnaire was sent to 560 European individuals working with biobanks asking to select their preferred definition for the terms. A total of 123 people participated in the survey, giving a response rate of 23%. The result was evaluated from four aspects: scope of definitions, potential regional differences, differences in semantics and definitions in the context of ontologies, guided by comments from responders. Indicative from the survey is the risk of focusing only on the research aspect of biobanking in definitions. Hence, it is recommended that important terms should be formulated in such a way that all areas of biobanking are covered to improve the bridges between research and clinical application. Since several of the terms investigated here within can also be found in a legal context, which may differ between countries, establishing what is a proper definition on how it adheres to law is also crucial.

Developing a semantically rich ontology for the biobank-administration domain.

BACKGROUND: Biobanks are a critical resource for translational science. Recently, semantic web technologies such as ontologies have been found useful in retrieving research data from biobanks. However, recent research has also shown that there is a lack of data about the administrative aspects of biobanks. These data would be helpful to answer research-relevant questions such as what is the scope of specimens collected in a biobank, what is the curation status of the specimens, and what is the contact information for curators of biobanks. Our use cases include giving researchers the ability to retrieve key administrative data (e.g. contact information, contact's affiliation, etc.) about the biobanks where specific specimens of interest are stored. Thus, our goal is to provide an ontology that represents the administrative entities in biobanking and their relations. We base our ontology development on a set of 53 data attributes called MIABIS, which were in part the result of semantic integration efforts of the European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). The previous work on MIABIS provided the domain analysis for our ontology. We report on a test of our ontology against competency questions that we derived from the initial BBMRI use cases. Future work includes additional ontology development to answer additional competency questions from these use cases. RESULTS: We created an open-source ontology of biobank administration called Ontologized MIABIS (OMIABIS) coded in OWL 2.0 and developed according to the principles of the OBO Foundry. It re-uses pre-existing ontologies when possible in cooperation with developers of other ontologies in related domains, such as the Ontology of Biomedical Investigation. OMIABIS provides a formalized representation of biobanks and their administration. Using the ontology and a set of Description Logic queries derived from the competency questions that we identified, we were able to retrieve test data with perfect accuracy. In addition, we began development of a mapping from the ontology to pre-existing biobank data structures commonly used in the U.S. CONCLUSIONS: In conclusion, we created OMIABIS, an ontology of biobank administration. We found that basing its development on pre-existing resources to meet the BBMRI use cases resulted in a biobanking ontology that is re-useable in environments other than BBMRI. Our ontology retrieved all true positives and no false positives when queried according to the competency questions we derived from the BBMRI use cases. Mapping OMIABIS to a data structure used for biospecimen collections in a medical center in Little Rock, AR showed adequate coverage of our ontology.

The validity of self-initiated, event-driven infectious disease reporting in general population cohorts.

BACKGROUND: The 2009/2010 pandemic influenza highlighted the need for valid and timely incidence data. In 2007 we started the development of a passive surveillance scheme based on passive follow-up of representative general population cohorts. Cohort members are asked to spontaneously report all instances of colds and fevers as soon as they occur for up to 9 months. Suspecting that compliance might be poor, we aimed to assess the validity of self-initiated, event-driven outcome reporting over long periods. METHODS: During two 8 week periods in 2008 and 2009, 2376 and 2514 cohort members in Stockholm County were sent one-week recall questionnaires, which served as reference method. RESULTS: The questionnaires were completed by 88% and 86% of the cohort members. Whilst the false positive proportion (1-specificity) in the reporting was low (upper bound of the 95% confidence interval [CI] ≤ 2% in each season), the false negative proportion (failure to report, 1-sensitivity) was considerable (60% [95% CI 52%-67%] in each season). Still, the resulting epidemic curves for influenza-like illness compared well with those from existing General Practitioner-based sentinel surveillance in terms of shape, timing of peak, and year-to-year variation. This suggested that the error was fairly constant. CONCLUSIONS: Passive long-term surveillance through self-initiated, event-driven outcome reporting underestimates incidence rates of common upper respiratory tract infections. However, because underreporting appears predictable, simple corrections could potentially restore validity.

Workshop on laboratory protocol standards for the Molecular Methods Database.

Management of data to produce scientific knowledge is a key challenge for biological research in the 21st century. Emerging high-throughput technologies allow life science researchers to produce big data at speeds and in amounts that were unthinkable just a few years ago. This places high demands on all aspects of the workflow: from data capture (including the experimental constraints of the experiment), analysis and preservation, to peer-reviewed publication of results. Failure to recognise the issues at each level can lead to serious conflicts and mistakes; research may then be compromised as a result of the publication of non-coherent protocols, or the misinterpretation of published data. In this report, we present the results from a workshop that was organised to create an ontological data-modelling framework for Laboratory Protocol Standards for the Molecular Methods Database (MolMeth). The workshop provided a set of short- and long-term goals for the MolMeth database, the most important being the decision to use the established EXACT description of biomedical ontologies as a starting point.

The Swedish cervical cytology biobank: sample handling and storage process.

The Swedish Cervical Cytology Biobank (SCCB) is the first national initiative of a prospective repository for liquid-based gynecological cell samples (LBC) from women participating in organized cervical cancer screening programs. Development and implementation of a nationally standardized method for the handling and long-term storage of cervical cell samples has been a primary goal for the Swedish hub of The Biobanking and Molecular Resource Infrastructure (BBMRI.se, www.bbmri.se). The sample handling protocol was developed through i) review of the literature on biobanking processes, ii) wide consultation within the academic community, and iii) various verification assays in collaboration with the clinical cytology laboratories. A general quality management system, covering all aspects of sample handling and storage, has been established. BBMRI.se financed the development and implementation of SCCB. The protocol established in the pilot project in Stockholm is now being implemented in other counties in Sweden, and during this year, more than 120,000 LBC samples will be processed for biobanking nationwide. SCCB is embedded in a comprehensive cytology diagnostic registry and will be linked with the national cancer registry to constitute a nearly inexhaustible resource for performance of fundamental and applied biologic research.