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A complex game of hide and seek: the search for new antifungals.

ABSTRACT: Fungal infections directly affect millions of people each year. In addition to the invasive fungal infections of humans, the plants and animals that comprise our primary food source are also susceptible to diseases caused by these eukaryotic microbes. The need for antifungals, not only for our medical needs, but also for use in agriculture and livestock causes a high demand for novel antimycotics. Herein, we provide an overview of the most commonly used antifungals in medicine and agriculture. We also present a summary of the recent progress (from 2010-2016) in the discovery/development of new agents against fungal strains of medical/agricultural relevance, as well as information related to their biological activity, their mode(s) of action, and their mechanism(s) of resistance.

SUBMITTER: Ngo HX

PROVIDER: S-EPMC5067021 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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A complex game of hide and seek: the search for new antifungals.

Ngo Huy X HX Garneau-Tsodikova Sylvie S Green Keith D KD

MedChemComm 20160517 7

Fungal infections directly affect millions of people each year. In addition to the invasive fungal infections of humans, the plants and animals that comprise our primary food source are also susceptible to diseases caused by these eukaryotic microbes. The need for antifungals, not only for our medical needs, but also for use in agriculture and livestock causes a high demand for novel antimycotics. Herein, we provide an overview of the most commonly used antifungals in medicine and agriculture. W ...[more]

PMID: 27766140

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Project description:An important element of precision medicine is the ability to identify, for a specific therapy, those patients for whom benefits of that therapy meaningfully exceed the risks. To achieve this goal, treatment effect usually is examined across subgroups defined by a variety of factors, including demographic, clinical, or pathologic characteristics or by molecular attributes of patients or their disease. Frequently such subgroups are defined by the measurement of biomarkers. Even though such examination is necessary when pursuing this goal, the evaluation of treatment effect across a variety of subgroups is statistically fraught due to both the danger of inflated false-positive error rate from multiple testing and the inherent insensitivity to how treatment effects differ across subgroups.Pre-specification of subgroup analyses with appropriate control of false-positive (i.e. type I) error is recommended when possible. However, when subgroups are specified by biomarkers, which could be measured by different assays and might lack established interpretation criteria, such as cut-offs, it might not be possible to fully specify those subgroups at the time a new therapy is ready for definitive evaluation in a Phase 3 trial. In these situations, further refinement and evaluation of treatment effect in biomarker-defined subgroups might have to take place within the trial. A common scenario is that evidence suggests that treatment effect is a monotone function of a biomarker value, but optimal cut-offs for therapy decisions are not known. In this setting, hierarchical testing strategies are widely used, where testing is first conducted in a particular biomarker-positive subgroup and then is conducted in the expanded pool of biomarker-positive and biomarker-negative patients, with control for multiple testing. A serious limitation of this approach is the logical inconsistency of excluding the biomarker-negatives when evaluating effects in the biomarker-positives, yet allowing the biomarker-positives to drive the assessment of whether a conclusion of benefit could be extrapolated to the biomarker-negative subgroup.Examples from oncology and cardiology are described to illustrate the challenges and pitfalls. Recommendations are provided for statistically valid and logically consistent subgroup testing in these scenarios as alternatives to reliance on hierarchical testing alone, and approaches for exploratory assessment of continuous biomarkers as treatment effect modifiers are discussed.

Dataset Information

A complex game of hide and seek: the search for new antifungals.

Publications

A complex game of hide and seek: the search for new antifungals.

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