Considerations on Digitizing Biomedical Research Infrastructures in Low- and Middle-Income Countries

Abstract

The emergence of biomedical research infrastructures during the last three decades has been central to the development of personalized medicine and genomic research, and the amount of knowledge, expertise, and experience accumulated during that time is significant. Indeed, research infrastructures, such as genomics (and other “-omics”) facilities, imaging facilities, and biobanks, have become key actors in the biomedical research fields, allowing for the high-throughput analysis of samples and data, the preservation of biological samples long after their collection and the digital availability of the information for research purposes.[1] To be able to handle and act upon the increasing amounts of data generated, biomedical research infrastructures are becoming more technologically advanced with the implementation of digital health innovations, particularly in high-income countries (HICs). However, because of the rapid pace of change and digital growth, low- and middle-income countries (LMICs) require more resources to develop their infrastructures.[2] In that context, digital technologies have the potential to usher research infrastructures into a new digital era and help LMICs handle the technical, financial, legal, ethical, and geographic challenges associated with their development and implementation. This brief report presents the key considerations on technical challenges and opportunities emerging within LMICs in their quest to transition their biomedical research infrastructures into the digital age.A literature search was conducted using the snowballing method, also called the citation tracking method.[3] At first, a set of papers was identified using the following keywords: LMICs, digitalization, biobanking, challenges, opportunities, and research infrastructures. These papers were identified on Google Scholar to avoid bias associated with individual publishers, then the reference lists of the selected articles were used to identify new papers. This methodology is less extensive than a systematic review, so this report cannot be considered a detailed view of the field, which would require a systematic approach.Digitalization is currently penetrating all fields of modern science and has consequently become a critical aspect of modern research infrastructure operations. Digital technologies, such as digital medical records, digital imaging, genomic sequencing or surveillance, staff scheduling, supply chain, and logistics, have been deployed in several LMICs, and exist at different stages of operational readiness.[3] In addition, biobanks have gained importance in the last few years due to increased requirements for research-ready, high-quality biological samples available at scale. Indeed, the processing and storage of biological samples with reliable and extensive preanalytical history play a key role for reproducibility in scientific research. Furthermore, because of the ever-increasing demand for samples highlighted by the increase in the global market value of the demand for human biospecimens between 2009 and 2015, which went from 750 to 2250 million USD,[4] particular attention is paid to sample acquisition and preparation to guarantee the highest possible sample quality. Similarly, genomic sequencing facilities have proliferated across many different locations, as evidenced by the increasing national genome or international genome projects[5] and the international federated research infrastructures.[6]This points to the role that digitalization can play, for instance, in the integration of multiple data sources linking clinical records to physical samples and downstream, experimentally derived data. Moreover, digitalization allows for the integration of research activities with the automation of the technical processes, such as retrieval, quality control, treatment, and analysis of physical samples and/or data.[1] Thus, digitalization could simplify biological data integration by providing access to a broad range of information from different databases to the end user. Connecting multiple databases to and implementing information management systems or middleware software is complex.[1]Although establishing biomedical research infrastructures and infrastructure networks has been a mainstay of national investment programs for a few HICs, the emerging LMIC picture provides a different perspective. This difference is worth considering in detail because LMIC specificities, such as infrastructure, financial, governance, population, and disease burden pressures, might drive further innovation in digital health (Table 1). Specifically, for LMICs, significant difficulties in establishing research infrastructures have been reported for different regions,[2] indicating regulatory and ethical dilemmas as well as difficulties associated with integrating digital technology into routine practices. LMICs still face tremendous difficulties in the implementation of digitalization, in part because of a lack of reliable technical infrastructure, such as continuous electricity supply, internet access, and reliable, high-speed internet access for data-demanding tasks.[2] Furthermore, limited financial and human resources mean investing in staff training and equipment is sometimes not possible. This issue is amplified by the departure of trained staff to more developed nations.[7] In addition, data privacy and security remain a major concern because regulations to protect patient data and ensure privacy and security and national or international data sharing are often limited.[2,8]These challenges can simultaneously become the catalyst in identifying and taking advantage of opportunities not necessarily evident in HICs. Indeed, various publications report the successful implementation of digital projects. For example, how different laboratories and government agencies in Indonesia could come together on a single digital platform due to the COVID-19 pandemic. This infrastructure that will now serve the routine surveillance and research of other infectious disease outbreaks.[9] A similar holistic view was adopted in India, as the National Digital Health Ecosystem (NHDE) was launched in 2020. NHDE is intended as a multilayered ecosystem incorporating “Digital Health Infrastructure, Digital Health Data Hubs, Building Blocks, Standards and Regulations, and an Institutional Framework.”[10] In another instance, in Rwanda, the Zipline project involved using drones to transport blood from storage units to hospitals since October 2016, addressing the complex landscape and lack of transportation infrastructure locally. Zipline's autonomous drones, linked with a digital procurement backbone, are now integral to Rwanda's medical supply infrastructure. This allows for a significant decrease in transportation costs and time, consequently improving healthcare provision.[11] Moreover, in Sierra Leone, the open-source electronic health record (EHR) platform OpenMRS-Ebola was developed and deployed in 2015 during the height of the West African Ebola epidemic as large-scale Ebola treatment centers (ETC) emerged. This EHR system was deployed at Save the Children's Kerry Town ETC and allowed for recording essential parameters, including vital signs, symptoms, laboratory results, and data for analysis and was designed for clinicians to have access to comprehensive and detailed patient information very quickly.[2,12]However, despite the increasing list of successful digital health implementations, the common overall approach remains fragmented (i.e., not part of a national or regional initiative) and unable to capitalize on potential synergies. In response to this disconnected picture, digital health guidelines and recommendations have been published to streamline health policies and further support digital health implementations in the future.[13]Biomedical research infrastructures continue to use widespread digitalization, especially as analytical technologies continue to develop. Digitalization offers a plethora of opportunities for biomedical research infrastructures to increase the scope of their activity and enhance their effectiveness and global reach. For instance, implementing secure digital environments that can integrate data from multiple databases allows for better management and tracking of large volumes of data while decreasing the potential for errors. Indeed, digital technologies are powerful tools that have the potential to provide high-quality services. Although digitalization is full of potential, the implementation complexities outlined provide a significant barrier, in particular, within LMICs. For example, in LMICs, digital health initiatives encounter financial, operational, and social challenges, which work additively against a complex background of competing priorities. The existing success stories prove that digitizing healthcare research infrastructures within LMICs is possible; however, this requires a stable environment for implementation with strong infrastructure, stakeholder support, and a legal and ethical framework for digital health through policies and regulations.

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