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Development and validation of HPLC method for simultaneous estimation of erlotinib and niclosamide from liposomes optimized by screening design

  • Amruta Prabhakar Padakanti
  • , Sachin Dattaram Pawar
  • , Pramod Kumar
  • , Naveen Chella*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The emerging drug resistance to the approved first-line drug therapy leads to clinical failure in cancer. Drug repurposing studies lead to the identification of many old drugs to be used for cancer treatment. Combining the repurposed drugs (niclosamide) with first-line therapy agents like erlotinib HCl showed improved efficacy by inhibiting erlotinib HCl acquired resistance. But there is a need to develop a sensitive, accurate, and excellent analytical method and drug delivery system for successfully delivering drug combinations. In the current study, an HPLC method was developed and validated for the simultaneous estimation of niclosamide and erlotinib HCl. The retention time of niclosamide and erlotinib hydrochloride was 6.48 and 7.65 min at 333 nm. The developed method was rapid and sensitive to separating the two drugs with reasonable accuracy, precision, robustness, and ruggedness. A Plackett–Burman (PBD) screening design was used to identify the critical parameters affecting liposomal formulation development using particle size, size distribution, zeta potential, and entrapment efficiency as the response. Lipid concentration, drug concentration, hydration temperature, and media volume were critical parameters affecting the particle size, polydispersity index (PDI), ZP, and %EE of the liposomes. The optimized NCM-ERL liposomes showed the particle size (126.05 ± 2.1), PDI (0.498 ± 0.1), ZP (−16.2 ± 0.3), and %EE of NCM and ERL (50.04 ± 2.8 and 05.42 ± 1.3). In vitro release studies indicated the controlled release of the drugs loaded liposomes (87.06 ± 9.93% and 42.33 ± 0.89% in 24 h).

Original languageEnglish
Pages (from-to)268-282
Number of pages15
JournalJournal of Liposome Research
Volume33
Issue number3
DOIs
Publication statusPublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Pharmaceutical Science

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