PubMed · 5174935
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Bertrand. 1965. [Notes on current problems in nursing].. https://pubmed.ncbi.nlm.nih.gov/5174935/
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PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.
HIV-1 group M strains are usually subtyped based on gag and/or env gene sequences. In our lab, part of the pol gene sequence was available in order to determine the genotypic anti-HIV drug resistance profile. To estimate the prevalence of the different HIV-1 subtypes in patients visiting the University Hospitals in Leuven in 1999 and for whom a genotypic drug resistance test was needed, we tried to use the pol sequence for subtyping. Recombination was investigated by similarity plots and bootscanning and subtyping was performed by phylogenetic analysis. The overall region spanning the entire protease and 747 nucleotides of the reverse transcriptase proved very suitable for subtyping, although there was a low phylogenetic signal at the beginning of the reverse transcriptase (nucleotides 0-250), as we demonstrated by likelihood mapping. Of the 41 samples analyzed, 21 belonged to subtype B. Of the other 20 non-B strains, 9 belonged to subtype C, 2 to subtype D and 1 to subtype A, G, H and J, respectively, 3 were CRF_02 (Circulating Recombinant Form), 1 was recombinant with a novel breakpoint and 1 sample was untypable. Although subtype B is still the most prevalent subtype in Belgium, it seems to be responsible for only half of the infections in this study. We could also document that the prevalence of subtype C is high in the Belgian native patients, especially among the heterosexually infected population. This could possibly be an indication for an epidemic spread of HIV-1 subtype C in Belgium, as for one third of these patients, no link to an endemic region could be found. The other non-B subtypes and the recombinants are mainly introduced by immigrants or by Belgian citizens traveling abroad.
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