Response Surface Methodology (RSM) models combined with experimental designs became popular in recent years. Their advantages to analyze the interactive effects among different factors and the efficiency considerations encouraged more researchers to conduct natural product research employed with these models. A review about basic principles of factorial designs, central composite designs, Box–Behnken designs, and Doehlert designs which utilized along with the RSM and their applications in natural product research is presented. The objective of this review was to report various experimental design techniques and their applications in the field of natural product research. Furthermore, the characteristic of each design is also presented and the trends of RSM applications in natural product research are also discussed in this paper.

Extemporaneous preparations are still widely prescribed for pediatric patients with special treatments of certain doses and/or combinations of drugs. Several problems related to extemporaneous preparations have been linked to the incidence of adverse events or a lack of therapeutic effectiveness. Developing nations are facing the challenges of compounding practices. The prevalence of compounded medication in developing nations must be explored to determine the urgency of compounding practices. Furthermore, the risks and challenges are described and explained through investigation and collection of numerous scientific articles from reputable databases, including Web of Science, Scopus, and PubMed. Pediatric patients need compounded medication related to the appropriate dosage form and dosage adjustment. Notably, it is important to observe extemporaneous preparations in order to provide patient-oriented medication.

Herbal medicines (HMs) are regarded as one of the traditional medicines in health care to prevent and treat some diseases. Some herbal components such as turmeric and ginger are used as HMs, therefore the identification and confirmation of herbal use are very necessary. In addition, the adulteration practice, mainly motivated to gain economical profits, may occur by substituting the high price of HMs with lower-priced ones or by addition of certain chemical constituents known as Bahan Kimia Obat (chemical drug ingredients) in Indonesia. Some analytical methods based on spectroscopic and chromatographic methods are developed for the authenticity and confirmation of the HMs used. Some approaches are explored during HMs authentication including single-component analysis, fingerprinting profiles, and metabolomics studies. The absence of reference standards for certain chemical markers has led to exploring the fingerprinting approach as a tool for the authentication of HMs. During fingerprinting-based spectroscopic and chromatographic methods, the data obtained were big, therefore the use of chemometrics is a must. This review highlights the application of fingerprinting profiles using variables of spectral and chromatogram data for authentication in HMs. Indeed, some chemometrics techniques, mainly pattern recognition either unsupervised or supervised, were applied for this purpose.

Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R²X = 0.88, R²Y = 0.71) and good predictivity (Q² = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R² = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products.

Curcuma longa, Curcuma xanthorrhiza, and Curcuma manga have been widely used for herbal or traditional medicine purposes. It was reported that turmeric plants provided several biological activities such as antioxidant, anti-inflammatory, hepatoprotector, cardioprotector, and anticancer activities. Authentication of the Curcuma species is important to ensure its authenticity and to avoid adulteration practices. Plants from different origins will have different metabolite compositions because metabolites are affected by soil nutrition, climate, temperature, and humidity. ¹H-NMR spectroscopy, principal component analysis (PCA), and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) were used for authentication of C. longa, C. xanthorrhiza, and C. manga from seven different origins in Indonesia. From the ¹H-NMR analysis it was obtained that 14 metabolites were responsible for generating classification model such as curcumin, demethoxycurcumin, alanine, methionine, threonine, lysine, alpha-glucose, beta-glucose, sucrose, alpha-fructose, beta-fructose, fumaric acid, tyrosine, and formate. Both PCA and OPLS-DA model demonstrated goodness of fit (R² value more than 0.8) and good predictivity (Q² value more than 0.45). All OPLS-DA models were validated by assessing the permutation test results with high value of original R² and Q². It can be concluded that metabolite fingerprinting using ¹H-NMR spectroscopy and chemometrics provide a powerful tool for authentication of herbal and medicinal plants.

Halal meats are meats that are allowed to be consumed by Muslim societies according to Islamic law (Syariah). Due to the development of food technology, non-halal meats such as pork or canine meat are added to food products to reduce the production costs. Non-halal meats also include meats from animals which are not slaughtered according to Syariah law; therefore, the availability of a standardized analytical method capable of detecting the presence of non-halal meats with high sensitivity is very urgent. The metabolomics technique, either targeted or untargeted approaches based on liquid chromatography–tandem mass spectrometry (LC-MS/MS) measurements is an emerging analytical method applied to the identification of non-halal meats in food products. The LC-MS/MS measurements provide an enormous metabolomics data, therefore, sophisticated data analysis tools such as chemometrics is required. Among the chemometrics techniques, exploratory data analysis for supervised and unsupervised pattern recognition, including principal component analysis (PCA), hierarchical cluster analysis (HCA), and linear-discriminant analysis (LDA), are the most-used. This review focused on the recent application of LC-MS/MS in combination with chemometrics for the detection and identification (qualitative analysis) of non-halal meats in food products. The selection criteria used for the papers in this review were studies on the application of metabolomics using LC-MS/MS and chemometrics for the halal authentication of meat products between 2005 and 2022. The results showed that potential biomarkers of non-halal meats could be found using chemometrics analysis. Therefore, it can be concluded that a combination of LC-MS/MS and chemometrics is promising for development as a standard analytical method for the analysis of non-halal meats in food products.