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ABSTRACT

The increasing number of drugs used in HIV patient treatment and the mutations associated with drug resistance make the inference of drug resistance a complex task that demands computational systems. Furthermore, the software development/update can generate an extra level of complexity in the process drug resistance analysis. An alternative to handle the complexity of drug resistance and software development is to use a formal representation of involved processes, such as process algebra. This allows mathematical reasoning about the analysis process, a precise description of system behavior, more advanced computational approaches, as concurrent/parallel execution and (semi) automatic software development. The first contribution of this research is a mapping of drug resistance algorithms rules into expressions of process algebra which facilitates the computational manipulation of theses rules. The second contribution is the HIVdag (HIV Drug Analysis Generator) system. This software supports the definition, generation and analyses of genotypic drug resistance tests based on process algebra expressions. Therefore, the users can easily create/update their own drug resistance algorithms any time and independent of software development.

REFERENCES

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INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES

General Terms:
Algorithms, Design, Experimentation, Languages, Management

Keywords:
HIV, NPDL, drug resistance, genotypic drug resistance testing, mutation analysis, process algebra