Insight into the mechanism and toxicology of nitrofurantoin: a metabolomics approach

Abstract

Safety and effectiveness are the two ends of the balance in drug development that needs to be evaluated. The biotransformation of drugs within a living organism could potentiate biochemical insults in the tissue and compromise the safety of drugs. Nitrofurantoin (NFT) is a cheap clinical antibiotic with a wide array of activities against gram-positive and gram-negative organisms. The NFT scaffold has been utilized to develop other derivates or analogues in the quest to repurpose drugs against other infectious diseases. Several techniques were developed over the years to study the mechanism of NFT metabolism and toxicity, such as voltammetry, chromatographic analysis, protein precipitation, liquid-liquid extraction, etc. Due to limitations in these methods, the mechanism of NFT biotransformation in the cell is poorly understood. Metabolomics has been adopted in drug metabolism to understand the mechanism of drug toxicity and could provide a solution to overcome the limitations of current techniques to determine mechanisms of toxicity. Unfortunately, little or no information regarding the metabolomics approach in NFT metabolism and toxicity is available. Hence, this review highlights the metabolomic techniques that can be adopted in NFT metabolism and toxicological studies to encourage the research community to widely adopt and utilize metabolomics in understanding NFT’s metabolism and toxicity.

Keywords:

• Nitrofurantoin
• metabolomics
• toxicity
• metabolites
• drug development

Authors’ contributions

All coauthors participated in the design, literature search, writing, and editing of the review.

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Disclosure statement

No potential conflict of interest was reported by the author(s).

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Data availability statement

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Additional information

Funding

The authors acknowledge the funding from the NRF Grand holder linked bursary CPRR Grant Prof N’Da UID 129324, North-West University (NWU), Potchefstroom, 2357, South Africa.

This work was supported by the National Research Foundation.