Medico-legal issues relating to pharmacogenomics and the development of personalised medicine in the context of HIV and AIDS in South Africa
Bibliographic record
Abstract
The principle of pharmacogenetics and pharmacogenomics (PGx) in health research is not new. However, pursuance thereof has regained momentum in the 21st century. Despite the apparent demand to respond to adverse drug reactions (ADRs), both the national and international medico-legal frameworks have struggled to determine the place of PGx within the scientific and medical arena. It is against such a background that the study sought to explore the medico-legal issues relating to pharmacogenomics and the development of personalised medicine in the context of the human immunodeficiency virus (HIV) and the acquired immunodeficiency syndrome (AIDS) in South Africa. The methodology employed in this thesis involves a critical and comparative examination of the international instruments and their monopolistic influences on the multinational pharmaceutical conglomerates (also known as “Big-Pharma”) regarding the manufacturing of antiretroviral drugs (ARVs). PGx, which relies on genetic variability, facilitates the development of personalised medicine where adverse drug reactions (ADRs) may be minimised. Currently, PGx in the South African context, and, in respect to people living with HIV, is approached in a fragmented manner. The South African approach to genomic research is caught between the provisions of section 27 of the Constitution’s debate concerning the availability of health resources, the protection of individuals and communities, as well as competing human rights issues. Biobanks, necessary for PGx to develop, are increasingly required to store large genetic information for purposes of interpretation and evaluation of ADRs associated with the ARVs. Since genes are personal identifiers, data privacy has started to dominate the international genomic research arena and therefore, invokes added complexities relating to informed consent. Drawing on the English and the Canadian approaches to PGx, the thesis identifies some useful principles and practices for the South African genomic research context. With the need for the implementation of PGx becoming critical, the South African legislator should waste no further time to regulate PGx in a manner to allow the development of personalised medicine so that clinicians are able to make an expeditious clinical decision before the prescription of medication and treatment, most urgently so in the context of HIV and AIDS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.030 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".