Headspace Gas Analysis (HGA) is a safe, accurate and reliable method for checking whether concentrations of certain molecules in a sealed container’s headspace (i.e. in the space not occupied by the product) are greater than expected. This is essential because higher concentrations can change the product’s characteristics throughout its shelf life.
This type of inspection method is useful in pharmaceutical quality control because identifying containers that have been contaminated not only eliminates the risk of selling drugs that are potentially dangerous to consumer health, but also provides useful information that helps companies improve their internal production processes. A contaminated sealed product means that something has not gone as expected during a previous processing stage, and analysis of the performance data collected by HGA also allows for early detection, and therefore correction, of any production line malfunctions.
How is HGA performed?
Headspace Gas Analysis uses tunable diode laser absorption spectroscopy (TDLAS), with laser diodes tuned to the frequency of the molecule being sought. When the laser beam passes through a gaseous medium, some of the photons are absorbed by the gas, causing darker lines to appear in the laser spectrum (these are called “absorption lines” or “Fraunhofer lines”). The spectrum of the outgoing beam is analysed to detect these lines. So, by assessing the quantity of photons absorbed during passage through the pharmaceutical product container, the presence, absence and concentration of a particular molecule in the container can be established.
Which molecules can be detected by HGA?
HGA can identify the presence of various gases and molecules inside the headspace of product containers. In the pharmaceutical sector, the most frequently sought gases and molecules are:
- Oxygen
- Carbon dioxide
- Water vapour
An excessively high concentration of these molecules can damage pharmaceutical products and significantly compromise their characteristics and effectiveness. Just consider, for example, the damage that excess moisture can cause inside a container of lyophilised powder, or the oxidation that oxygen molecules in the headspace can cause.
Because some pharmaceutical products are highly sensitive, the containers used to store them are sometimes flushed with nitrogen to remove other gases inside before being filled. If HGA finds that the concentration of oxygen, carbon dioxide or water vapour in the headspace is greater than expected, it means that the container was improperly treated at some point, which suggests that the production line is not operating correctly (e.g., there could be a malfunction in the nitrogen cleaning system, the capping machine might not be working properly, etc.).
The advantages of HGA using TDLAS
TDLAS can provide very accurate results, and is especially advantageous with respect to other headspace composition analysis methods. Some of the benefits of this method are:
- Speed: TDLAS technology provides results in a very short time, even in real time in some cases.
- Simplicity: The laser beam calibration process is very simple and guarantees excellent results both in a “protected” laboratory context and directly on the production line.
- Accuracy: The TDLAS system is very sensitive: the laser beam can be precisely calibrated and the presence of other gases does not affect detection.
Bonfiglioli Engineering has extensive experience in the design and construction of machines for HGA, and provides its customers with both laboratory HGA sample analysis equipment and tools that can be installed directly on the production line so that 100% of products can be inspected. Over the years, Bonfiglioli Engineering has developed solutions that address many of the problems associated with signal noise, for example, finding corrections that ensure it offers customers high-performance and accurate testing tools that can operate on high-speed lines and therefore perform analysis more quickly. Contact us today to discuss how we can solve your pharmaceutical package inspection challenges.
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