Millions of people around the world do not have access to necessary medicines. The exacerbation of these health problems is an increasingly widespread problem in the world: counterfeit drugs and pharmaceuticals.
The World Health Organization (WHO) has found that “one in 10 medicines in low- and middle-income countries are estimated to be substandard or falsified”. In total, they estimate that at least “10% of the global pharmaceutical trade, or $21 billion, involves counterfeit drugs”. Part of the concern that needs to be addressed is how easy it can be to buy drugs online from unauthorized sources and how difficult it is to distinguish between real and fake drugs. And some counterfeits have even “infiltrated legitimate supply chains,” according to researchers from the Forensics and Innovative Technologies group of Bristol-Myers Squibb’s Global Quality Analytical Science and Technology division.
A global push to eradicate the health threats posed by counterfeit medicines is growing. However, in a study published in the European pharmaceutical journal, the Bristol-Myers Squibb team of scientists demonstrated that visible and near-infrared (VNIR) hyperspectral imaging, as well as Raman spectroscopy, can effectively identify and classify several types of counterfeit drugs.
All drug products, such as tablets, have unique light absorption and reflection characteristics in the VNIR spectral region of the electromagnetic spectrum. The researchers say that “only hyperspectral imaging can collect a detailed and specific fingerprint in this [VNIR] region at an extremely rapid pace. The reflectance spectral fingerprint in the VNIR regions for each pixel in an image can create a map showing the quality of a given product. It can also accurately differentiate between pixels that might look identical to the human eye, but may actually be very different. For example, some counterfeit pharmaceuticals may appear visually authentic, but are actually chemically different. Hyperspectral imaging offers “an extra dimension of information in every pixel of a pharmaceutical product to distinguish its quality”. Essentially, this spectral dimension helps differentiate counterfeit drugs from genuine drugs.
In their study, the researchers created a calibration dataset with reflectance measurements of two tablets of genuine drug products as well as two to seven tablets of each counterfeit type. By testing 44 tablet samples, this calibration model correctly identified which were genuine and which were fake.
The researchers also used Raman spectroscopy – specifically Fourier Transform (FT) Raman spectroscopy – in their study, demonstrating its ability to be a “successful screening tool”. They note that this technique can be used to study “fundamental modes of molecular vibration using monochromatic light” – a laser whose light interacts with a sample (in this case, a pharmaceutical drug). “Scattered radiation is detected to gather information about the interrogated product.”
In this study, a total of 153 tablets of four known types of counterfeits were analyzed with this method; the team collected 143 Raman spectra of the four types of counterfeits, as well as 10 spectra of genuine tablets. These data, combined with other analyses, showed that this technique can be used successfully to classify counterfeits.
Ultimately, the researchers found that “once the initial detection of different types of counterfeits for a given branded product is confirmed using Raman spectroscopy, VNIR hyperspectral imaging can eventually replace it and be successfully implemented for rapid detection of counterfeit pharmaceuticals”.