Using ASAP-MS to detect the difference between over-the-counter and counterfeit paracetamol tablets

Using ASAP-MS to detect the difference b etween over-the-counter and counterfeit paracetamol tablets

Ben S. Campbell1, Matthew Roberts1, Scott J. Campbell2, John H. Moncur2 and David Douce3
1Liverpool John Moores University, Liverpool, UK; 2SpectralWorks Ltd, Runcorn, UK and 3Waters, Wilmslow, UK

First presented as a poster at BMSS Ambient Ionisation SIG Meeting February 2024


According to the World Health Organizaon, an estimated 1 in 10 medical products in low- and middle-income countries is substandard or falsified1. This can range from medical products containing no active ingredients, or incorrect amounts. As a result, the recipient’s response (or lack of) to the medication may vary and can lead to significant consequences. The ability to quickly and accurately the difference between genuine and counterfeit products is therefore an important requirement in tackling the threat to human health. Here we invesgate how Atmospheric Solids Analysis Probe (ASAP) mass spectrometry can be used to differenate between authentic and counterfeit paracetamol tablets, and measure the amount of the Active Pharmaceutical Ingredient (API).


Three commercially manufactured Paracetamol tablets and three locally prepared tablets (used to simulate counterfeit products) containing Paracetamol (Sigma-Aldrich, UK) with one of three different excipients: (KollitabTM DC 87 (BASF, Germany); PROSOLV® EASYtab SP (JRS Pharma, Germany) and Starch 1500® (Colorcon, USA).

For the counterfeit tablets, the API and excipients were placed into an amber glass jar and blended within a Turbula mixer (WAB, Switzerland) for 5 minutes. The powder was passed through a 500 μm laboratory sieve (EndecoHs, UK) then transferred back into the amber glass jar and blended for another 5 minutes. For lubrication of the Starch 1500® excipient batch, 1 % w/w magnesium stearate was added, then mixed for a further 2 minutes.

Tablets were produced through the use of a single-station press (Riva Minipress®) fitted with 10 mm round, flat-faced tooling. The tablets were collected, placed in a 30 mL vial and labelled.

For each counterfeit batch, a glass capillary sampling rod was brushed against the tablet
and MS data was acquired on the Waters’ RADIAN ASAP MS. Prior to sampling, the rod was baked out for 30 seconds at 600°C, the following acquisition method was used:

  • Full Scan mode over mass range m/z 50 – 650 in ASAP posive ionizaon mode.
  • 4-Function method utilising cone voltages 15, 25, 35 and 50 V to facilitate the use
    of the Waters’ PANDORA library for API idenfication.
  • Acquisition time was 15 seconds with the sample was inserted into the RADIAN for
    5 seconds.

Figure 1 shows the workflow for collecting a sample from the tablet and the use of SpectralWorks’ RemoteAnalyzer software to acquire and process the samples.

For the quantitation and statistical comparison of the samples, a single function with a cone voltage of 15 V was used. Five replicates of each of the six tablets were then acquired for further analysis.

Results and Discussion

To confifirm the presence and validity of the API in the counterfeit samples, the data from the 4-Function acquision was processed immediately after acquisition and the results relayed to the user as shown in figure 1. This workflow confirmed to the non-expert operator that each of the counterfeit tablets sampled contained a target component in the PANDORA library.

The samples can then be further interrogated by an expert user in RemoteAnalyzer as
shown in figure 2. Here we can see that each of the counterfeit tablets were idenfied with a confidence of > 95%.

For the quantitative and statistical comparison, SpectralWorks’ AnalyzerPro XD was used to process the data.

Figure 3 shows the calibration curves for m/z 152 for the five replicates of the three genuine paracetamol tablets.

Figure 4 shows the variation in the authentic paracetamol tablets and the calculated amounts of the three batches of counterfeit tablets against the GSK calibration curve. Using an Unpaired t-test, the calculated amounts for the counterfeit tablets showed significantly more variaon in comparison to those commercially manufactured (p-Value < 0.0001).

From the processed data, a matrix of m/z against sample was created and used to generate a PCA scores plot as shown in figure 5. The m/z for the given data set ranged from m/z 53 to 481. The first PCA scores plot (A), uses the full m/z range and shows a tight clustering of the commercial tablets. This is further shown by viewing only the commercial tablet groups (B).

Using only the masses associated with the commercial tablets, further differentiation was seen between the commercial and counterfeit tablets (C).


Using ASAP-MS combined with software specifically designed for non-expert MS users  provided a fast sample turnaround to identify the API in counterfeit tablets. Quantitation of the expected API showed that there were significant differences between the commercially manufactured and counterfeit tablets. PCA was able to differentiate between the two categories of tablets.

Further improvements could be made to the quantitation by including an internal standard and introducing additional sample preparation. However, the objective was to create a simple workflow in this study.