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Unveiling the therapeutic promise of natural products in alleviating drug-induced liver injury: Present advancements and future prospects.

Deepti SinghMohammad Afsar KhanHifzur R Siddique
Published in: Phytotherapy research : PTR (2023)
Drug-induced liver injury (DILI) refers to adverse reactions to small chemical compounds, biological agents, and medical products. These reactions can manifest as acute or chronic damage to the liver. From 1997 to 2016, eight drugs, including troglitazone, nefazodone, and lumiracoxib, were removed from the market due to their liver-damaging effects, which can cause diseases. We aimed to review the recent research on natural products and their bioactive components as hepatoprotective agents in mitigating DILI. Recent articles were fetched via searching the PubMed, PMC, Google Scholar, and Web of Science electronic databases from 2010 to January 2023 using relevant keywords such as "natural products," "acetaminophen," "antibiotics," "paracetamol," "DILI," "hepatoprotective," "drug-induced liver injury," "liver failure," and "mitigation." The studies reveal that the antituberculosis drug (acetaminophen) is the most frequent cause of DILI, and natural products have been largely explored in alleviating acetaminophen-induced liver injury. They exert significant hepatoprotective effects by preventing mitochondrial dysfunction and inflammation, inhibiting oxidative/nitrative stress, and macromolecular damage. Due to the bioavailability and dietary nature, using natural products alone or as an adjuvant with existing drugs is promising. To advance DILI management, it is crucial to conduct well-designed randomized clinical trials to evaluate natural products' efficacy and develop new molecules clinically. However, natural products are a promising solution for remedying drug-induced hepatotoxicity and lowering the risk of DILI.
Keyphrases
  • drug induced
  • liver injury
  • liver failure
  • adverse drug
  • oxidative stress
  • hepatitis b virus
  • public health
  • current status
  • emergency department
  • early stage
  • single cell
  • intensive care unit
  • deep learning