Does pharmacogenomics provide an ethical challenge to the utilisation of cost-effectiveness analysis by public health systems?

Pharmacogenomics promotes an understanding of the genetic basis for differences in efficacy or toxicity of drugs in different individuals. Implementation of the outcomes of pharmacogenomic research into clinical practice presents a number of difficulties for healthcare. This paper aims to highlight one of the Unique ethical challenges which pharmacogenomics presents for the utilisation of cost-effectiveness analysis by public health systems. This paper contends that pharmacogenomics provides a challenge to fundamental principles which underlie most systems for deciding which drugs should be publicly subsidised. Pharmacogenomics brings into focus the conflict between equality and utility in the context of using cost-effectiveness analysis to aid distribution of a limited national drug budget.

Environmental contamination of arsenic and its toxicological impact on humans

Inorganic arsenic compounds are known carcinogens. The human epidemiologic evidence of arsenic-induced skin, lung, and bladder cancers is strong. However, the evidence of arsenic carcinogenicity in animals is very limited. Lack of a suitable animal model until recent years has inhibited studies of the mechanism of arsenic carcinogenesis. The toxicity and bioavailability of arsenic depend on its solubility and chemical forms. Therefore, it is critical to be able to measure arsenic speciation accurately and reliably. However, speciation of arsenic in more complex matrices remains a real challenge. There are tens of millions of people who are being exposed to excessive levels of arsenic in the drinking water alone. The source of contamination is mainly of natural origin and the mass poisoning is occurring worldwide, particularly in developing countries. Chronic arsenicosis resulting in cancer and non-cancer diseases will impact significantly on the public health systems in their respective countries. Effective watershed management and remediation technologies in addition to medical treatment are urgently needed in order to avoid what has been regarded as the largest calamity of chemical poisoning in the world.

A Reactive Agent-based Neural Network Car Following Model

This paper presented a novel approach to develop car following models using reactive agent techniques for mapping perceptions to actions. The results showed that the model outperformed the Gipps and Psychophysical family of car following models. The standing of this work is highlighted by its acceptance and publication in the proceedings of the International IEEE Conference on Intelligent Transportation Systems (ITS), which is now recognised as the premier international conference on ITS. The paper acceptance rate to this conference was 67 percent. The standing of this paper is also evidenced by its listing in international databases like Ei Inspec and IEEE Xplore. The paper is also listed in Google Scholar. Dr Dia co-authored this paper with his PhD student Sakda Panwai.