| Literature DB >> 35571023 |
C Victor Jongeneel1, Maritha J Kotze2, Archana Bhaw-Luximon3, Faisal M Fadlelmola4, Yasmina J Fakim5, Yosr Hamdi6,7, Samar Kamal Kassim8, Judit Kumuthini9, Victoria Nembaware10, Fouzia Radouani11, Nicki Tiffin12,13, Nicola Mulder12,13.
Abstract
Genomics policy development involves assessing a wide range of issues extending from specimen collection and data sharing to whether and how to utilize advanced technologies in clinical practice and public health initiatives. A survey was conducted among African scientists and stakeholders with an interest in genomic medicine, seeking to evaluate: 1) Their knowledge and understanding of the field. 2) The institutional environment and infrastructure available to them. 3) The state and awareness of the field in their country. 4) Their perception of potential barriers to implementation of precision medicine. We discuss how the information gathered in the survey could instruct the policies of African institutions seeking to implement precision, and more specifically, genomic medicine approaches in their health care systems in the following areas: 1) Prioritization of infrastructures. 2) Need for translational research. 3) Information dissemination to potential users. 4) Training programs for specialized personnel. 5) Engaging political stakeholders and the public. A checklist with key requirements to assess readiness for implementation of genomic medicine programs is provided to guide the process from scientific discovery to clinical application.Entities:
Keywords: Africa; Pathology-supported genomics; capacity development; genomic medicine; infrastructure; precision medicine stakeholders; readiness checklist; translational research
Year: 2022 PMID: 35571023 PMCID: PMC9091728 DOI: 10.3389/fgene.2022.769919
Source DB: PubMed Journal: Front Genet ISSN: 1664-8021 Impact factor: 4.599
FIGURE 1Map showing the countries from which responses were received, including the total number of respondents within the country (dark orange) and out of these, the number who are currently or planning to implement genomic medicine activities (light orange).
Checklist with key requirements to assess readiness of African countries prior to implementation of genomic medicine programs.
| Key elements | Processes required | Readiness assessment |
|---|---|---|
| Patient selection: Clinical facilities for patient counselling, screening, treatment and monitoring | Informed consent of participants, obtain relevant previous pathology/other test results from health records, data translation into an adaptable report, genetic counselling | Clinical infrastructure for patient enrollment, collection and analysis of biosamples linked to patient data to enable treatment recommendations and monitoring of clinical outcome |
| Sample selection: Sample collection, processing and storage facilities, data acquisition tools to prevent operational fragmentation | Sample type selection (e.g., blood, saliva, biopsy) and metadata collection, sample transfer and preparation applying good clinical practice | Biorepositories for sample preparation and storage to enable retrieval and re-analysis of patient samples, acquisition and storage of metadata including clinical data from different sources |
| Data generation: Genetic testing, genomics data generation and storage | DNA/RNA extraction or direct swab-specimen application, quality control, data generation through genetic testing or omics technologies | Data generation instruments for generation of results on portable devices (point-of-care/other genotyping tests) and/or large scale (microarrays, high-throughput sequencing) |
| Data analysis: Data storage, curation, analysis and interpretation by assessing clinical relevance of genetic findings | Data processing, analysis, variant classification, identification of actionable gene variant(s), analytical validation using gold standard methodology, alignment of clinical characteristics with familial vs. lifestyle risk and/or treatment response | Data and computing infrastructures for acquiring and storage of genomic data and to enable efficient and secure transfer of data, complex software environment for running research-informed pipelines to enable analysis and interpretation of high throughput genomic data, integrated data systems for analysis, interpretation and report generation, and AI to facilitate clinical decision making |
| Knowledge databases: Up to date information on genotype-phenotype links and evidence for actionability | Compare variants with reference and disease datasets and prior evidence, extract additional clinically relevant data (e.g., medication use, comorbidities) for clinical interpretation | Reference genomics datasets for relevant populations, sufficient evidence for actionability based on data generated in-country and reported in other patients with similar clinical phenotypes based on well-established scientific literature |
| Research facilities: Increase knowledge on genomics in African populations, enable translation of results | Data generation and sharing for research translation, gain collective knowledge for precision medicine applications, validation and transition to clinical application | Data generation and sharing capability, research infrastructure, facilities for transitioning to applied research involving feasibility and proof of principle studies on assay validation, clinical utility and health economics to enable up-scaling for clinical translation and implementation |
| Training: Genomic medicine training programs for healthcare professionals and support personnel | Training to develop a multi-disciplinary service delivery team, case-based learning to achieve learning objectives | Training facilities and curricula for new degrees and professional development courses, online platforms to practice implementation ideas (e.g. pathology-supported genomics) |
| Regulatory framework: Policy development for governing relevant activities, informed by standard operating procedures (SOPs) and instructions for use (IFUs) | Data and sample governance policy, informed consent documents and tracking, material transfer and data sharing agreements, participant engagement and intellectual property disclosure to authorities | Genomic medicine framework with data and sample governance, and ethical oversight, long-term participant engagement to close the gap between expectation and reality |