Chemometric-empowered spectroscopic techniques in pharmaceutical fields: A bibliometric analysis and updated review - Zulkifli, Baidillah; Fakri, Fajar; Odigie, Joan; Nnabuife, Loveday; Isitua, Chinwe C.; Chiari, Williams (Narra X, 2023)
Undeniable increase in pharmaceutical demand has encouraged researchers to develop analytical techniques to analyze drugs and monitor their effects. Chemometrics enabled simple spectroscopic approaches (such as infrared or UV spectroscopy) to analyze complex samples, including drug formulations, excreted fluids and tissues of living organisms. The aim of this study was to evaluate the research trend of this combinatorial technique utilized for pharmaceutical-related sample analysis using a bibliometric analysis. Bibliometric data of published literature from the Scopus database on March 14, 2023 were retrieved using the keyword combinations of "multivariate", "chemometrics", "pattern recognition", "drug", "pharmaceutical" and "spectroscopy". Network visualization analysis was performed using VOSviewer on the co-occurring keywords and authorships, presenting data such as top cited papers (n=10). The literature review was performed based on the research trend revealed by the clusters that emerged in the network visualization. The analysis revealed that the first paper was published in 1973 (n=1) and a total of 3544 records have been published as of March 14, 2023, comprising original research articles (n=3144, 88.71%) and review articles (n=232, 6.55%). The keyword “chemometrics” with Total Link Strength (TLS) of 826 emerged as the most abundant, followed by “metabolomics” (TLS=388), “Raman spectroscopy” (TLS=280), “metabonomics” (TLS=272), “nuclear magnetic resonance” or “NMR” (TLS=271), and “multivariate analysis” (TLS=254). Network visualization revealed that the research falls into two general categories: (1) drug toxicity and efficacy monitoring and (2) quality control of drug manufacturing. The top cited paper (n=3269) was a review article published in 1999 describing the utility of nuclear magnetic resonance combined with multivariate statistics for metabolite profiling of biological samples. The chemometric-empowered spectroscopy techniques were expected to provide objective measurement during clinical studies and monitoring of therapeutic effects.