Recommendations for laboratory workflow that better support centralised amalgamation of genomic variant data: findings from CanVIG-UK national molecular laboratory survey.

BACKGROUND: National and international amalgamation of genomic data offers opportunity for research and audit, including analyses enabling improved classification of variants of uncertain significance. Review of individual-level data from National Health Service (NHS) testing of cancer susceptibility genes (2002-2023) submitted to the National Disease Registration Service revealed heterogeneity across participating laboratories regarding (1) the structure, quality and completeness of submitted data, and (2) the ease with which that data could be assembled locally for submission. METHODS: In May 2023, we undertook a closed online survey of 51 clinical scientists who provided consensus responses representing all 17 of 17 NHS molecular genetic laboratories in England and Wales which undertake NHS diagnostic analyses of cancer susceptibility genes. The survey included 18 questions relating to 'next-generation sequencing workflow' (11), 'variant classification' (3) and 'phenotypical context' (4). RESULTS: Widely differing processes were reported for transfer of variant data into their local LIMS (Laboratory Information Management System), for the formatting in which the variants are stored in the LIMS and which classes of variants are retained in the local LIMS. Differing local provisions and workflow for variant classifications were also reported, including the resources provided and the mechanisms by which classifications are stored. CONCLUSION: The survey responses illustrate heterogeneous laboratory workflow for preparation of genomic variant data from local LIMS for centralised submission. Workflow is often labour-intensive and inefficient, involving multiple manual steps which introduce opportunities for error. These survey findings and adoption of the concomitant recommendations may support improvement in laboratory dataflows, better facilitating submission of data for central amalgamation

Challenges of biobanking in South Africa to facilitate indigenous research in an environment burdened with human immunodeficiency virus, tuberculosis, and emerging non-communicable diseases

The high burden of infectious diseases and the growing problem of noncommunicable and metabolic disease syndromes in South Africa (SA) forces a more focused research approach to facilitate cutting-edge scientific growth and public health development. Increased SA research on these diseases and syndromes and the collection of associated biospecimens has ensured a plethora of biobanks created by individuals, albeit without the foresight of prospective and collective use by other local and international researchers. As the need for access to high-quality specimens in statistically relevant numbers has increased, so has the necessity for the development of national human biobanks in SA and across the Continent. The prospects of achieving sustainable centralized biobanks are still an emerging and evolving concept, primarily and recently driven by the launch of the H3Africa consortium, which includes the development of harmonized and standardized biobanking operating procedures. This process is hindered by a myriad of complex societal considerations and ethico-legal challenges. Efforts to consolidate and standardize biological sample collections are further compromised by the lack of full appreciation by national stakeholders of the biological value inherent in these collections, and the availability of high quality human samples with well-annotated data for future scientific research and development. Inadequate or nonexistent legislative structures that specifically regulate the storage, use, dispersal, and disposal of human biological samples are common phenomena and pose further challenges. Furthermore, concerns relating to consent for unspecific future uses, as well as access to information and data protection, are all new paradigms that require further consideration and public engagement. This article reviews important fundamental issues such as governance, ethics, infrastructure, and bioinformatics that are important foundational prerequisites for the establishment and evolution of successful human biobanking in South Africa.Web of Scienc

Baobab LIMS: An open source biobank laboratory information management system for resource-limited settings

Philosophiae Doctor - PhDA laboratory information management system (LIMS) is central to the informatics infrastructure that underlies biobanking activities. To date, a wide range of commercial and open source LIMS are available. The decision to opt for one LIMS over another is often influenced by the needs of the biobank clients and researchers, as well as available financial resources. However, to find a LIMS that incorporates all possible requirements of a biobank may often be a complicated endeavour. The need to implement biobank standard operation procedures as well as stimulate the use of standards for biobank data representation motivated the development of Baobab LIMS, an open source LIMS for Biobanking. Baobab LIMS comprises modules for biospecimen kit assembly, shipping of biospecimen kits, storage management, analysis requests, reporting, and invoicing. Baobab LIMS is based on the Plone web-content management framework, a server-client-based system, whereby the end user is able to access the system securely through the internet on a standard web browser, thereby eliminating the need for standalone installations on all machines. The Baobab LIMS components were tested and evaluated in three human biobanks. The testing of the LIMS modules aided in the mapping of the biobanks requirements to the LIMS functionalities, and furthermore, it helped to reveal new user suggestions, such as the enhancement of the online documentation. The user suggestions are demonstrated to be important for both LIMS strengthen and biobank sustainability. Ultimately, the practical LIMS evaluations showed the ability of Boabab LIMS to be used in the management of human biobanks operations of relatively different biobanking workflows

The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) database: open-access data collection in maternal and newborn health

In less-resourced settings, adverse pregnancy outcome rates are unacceptably high. To effect improvement, we need accurate epidemiological data about rates of death and morbidity, as well as social determinants of health and processes of care, and from each country (or region) to contextualise strategies. The PRECISE database is a unique core infrastructure of a generic, unified data collection platform. It is built on previous work in data harmonisation, outcome and data field standardisation, open-access software (District Health Information System 2 and the Baobab Laboratory Information Management System), and clinical research networks. The database contains globally-recommended indicators included in Health Management Information System recording and reporting forms. It comprises key outcomes (maternal and perinatal death), life-saving interventions (Human Immunodeficiency Virus testing, blood pressure measurement, iron therapy, uterotonic use after delivery, postpartum maternal assessment within 48 h of birth, and newborn resuscitation, immediate skin-to-skin contact, and immediate drying), and an additional 17 core administrative variables for the mother and babies. In addition, the database has a suite of additional modules for ‘deep phenotyping’ based on established tools. These include social determinants of health (including socioeconomic status, nutrition and the environment), maternal comorbidities, mental health, violence against women and health systems. The database has the potential to enable future high-quality epidemiological research integrated with clinical care and discovery bioscience

A Two-Level Identity Model To Support Interoperability of Identity Information in Electronic Health Record Systems.

The sharing and retrieval of health information for an electronic health record (EHR) across distributed systems involves a range of identified entities that are possible subjects of documentation (e.g., specimen, clinical analyser). Contemporary EHR specifications limit the types of entities that can be the subject of a record to health professionals and patients, thus limiting the use of two level models in healthcare information systems that contribute information to the EHR. The literature describes several information modelling approaches for EHRs, including so called “two level models”. These models differ in the amount of structure imposed on the information to be recorded, but they generally require the health documentation process for the EHR to focus exclusively on the patient as the subject of care and this definition is often a fixed one. In this thesis, the author introduces a new identity modelling approach to create a generalised reference model for sharing archetype-constrained identity information between diverse identity domains, models and services, while permitting reuse of published standard-based archetypes. The author evaluates its use for expressing the major types of existing demographic reference models in an extensible way, and show its application for standards-compliant two-level modelling alongside heterogeneous demographics models. This thesis demonstrates how the two-level modelling approach that is used for EHRs could be adapted and reapplied to provide a highly-flexible and expressive means for representing subjects of information in allied health settings that support the healthcare process, such as the laboratory domain. By relying on the two level modelling approach for representing identity, the proposed design facilitates cross-referencing and disambiguation of certain demographics standards and information models. The work also demonstrates how it can also be used to represent additional clinical identified entities such as specimen and order as subjects of clinical documentation