Lengauer Thomas, Sing Tobias
Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany.
Nat Rev Microbiol. 2006 Oct;4(10):790-7. doi: 10.1038/nrmicro1477.
Highly active antiretroviral therapy (HAART), in which three or more drugs are given in combination, has substantially improved the clinical management of HIV-1 infection. Still, the emergence of drug-resistant variants eventually leads to therapy failure in most patients. In such a scenario, the high diversity of resistance-associated mutational patterns complicates the choice of an optimal follow-up regimen. To support physicians in this task, a range of bioinformatics tools for predicting drug resistance or response to combination therapy from the viral genotype have been developed. With several free and commercial software services available, computational advice is rapidly gaining acceptance as an important element of rational decision-making in the treatment of HIV infection.
高效抗逆转录病毒疗法(HAART),即联合使用三种或更多药物,已显著改善了HIV-1感染的临床管理。然而,耐药变异株的出现最终导致大多数患者治疗失败。在这种情况下,耐药相关突变模式的高度多样性使最佳后续治疗方案的选择变得复杂。为了在这项任务中为医生提供支持,已经开发了一系列用于从病毒基因型预测耐药性或联合治疗反应的生物信息学工具。随着有几种免费和商业软件服务可供使用,计算建议作为HIV感染治疗中合理决策的一个重要因素正迅速获得认可。