In the manuscript titled ‘Classification of tablet formulations by desorption electrospray ionisation mass spectrometry and transmission Raman spectroscopy’, the authors reported the multivariate analysis of DESI-MS and transmission Raman data to discriminate common painkillers. Many concerns should be considered to improve the text and the results.
The Introduction is well-structured, and it is highly praiseworthy that quite recent papers are also mentioned.
Pg 5 Ln 33-35 It would be recommended to reveal the total mass of the tablets as the API content could be better interpreted, and it helps to understand the Figures.
Pg 7 Ln 24 The msbackadj function is used to correct the baseline of mass spectra. However, the spline approximation method is a very hard method to apply for Raman spectra, where broader peaks appear (mainly in the case of polymers). This approach can lead to information loss. So, it is not surprising that only the sharp peaks are visible in Fig. 1F. Using a proper baseline correction method may be crucial in this study.
Pg 7 Ln 50 There is no Table 1 in Supplementary information
Pg 9 Ln 20-29 Why did tablet A show very low signals for paracetamol while the content is as high as in the case of tablet D. Both tablets A and D have film coatings.
Pg 10 Ln 33-34 The cosine similarity between types B and C looks too high, almost identical. However, previous spectral analysis (see Fig. 1G) revealed differences between the Raman spectra of types B and C. The caffeine content should have a much more significant effect on spectra.
Pg 11 Ln 27-36 The high rate of misclassification (17 and 33%) at the best LDA method is surprising. Types A and D had lower cosine similarity, yet the method distinguishes more similar tablet spectra (types B and C) better.
Pg 15 Ln 38-39 The two analytical techniques provide complementary information. It would be worthwhile to think about data fusion, allowing for more efficient classification.
Typos:
Pg 4 Ln 60 lineiar discriminant → linear discriminant
Pg 5 Ln 51 tarch → Starch
Pg 11 Ln 42 SFM → SVM