Distribution simulating testing, also known as ship testing or distribution testing, is an essential step in the process of safely bringing a medical device to market. As part of the 510(K) submission to the U.S. Food & Drug Administration, medical device manufacturers must prove their products can withstand standard shipping environments without being damaged or having their sterile barriers breached.
To do that, there are a number of tests that simulate the potential “shake, rattle, and roll” products experience during shipping, from being crushed under a heavier package or being dropped off a loading dock. The tests also ensure package integrity and sterility are maintained in different environmental conditions, from the frigid temperatures of Alaska to the heat and humidity of Florida.
The specifics for distribution simulation testing are spelled out in a number of accepted industry standards that regulators will check against, including ISO 11607. More specifically, sterile devices should conform to testing covered under ASTM D4169, whereas non-sterile devices will adhere to ISTA-2A or ISTA-3A requirements. Many of these standards have become more rigorous over the years, so ensuring compliance is essential.
These simulation tests often take about three weeks – although sometimes longer – so manufacturers should take proactive steps to ensure the process is as efficient as possible. This will ensure they have the best chance of securing a positive outcome and advancing the product’s path to market. Given Life Science Outsourcing’s deep experience and expertise with distribution simulation testing, here are three steps organizations can take to ensure a streamlined process.
1. Test the right number of samples
Lots of manufacturers have questions about the right distribution simulation testing sample size. It’s an important consideration – include too few samples, and it may not be considered statistically significant. But, testing too many can create unnecessary costs and delays, especially when current manufacturing capabilities are limited.
As a baseline, manufacturers should expect 29 samples at a minimum, though the exact number will vary depending on risk and the results of the failure modes and effects analysis (FMEA) results. A high-risk device such as a pacemaker or heart valve will likely require a larger sample size, as will any devices with sharp edges or other elements that increase the likelihood of damage occurring during shipping and distribution.
2. Test at the correct ‘level’
Manufacturers have some flexibility on what packaging “level” they use to run distribution simulation tests. For example, say a device is placed inside a pouch, which is then placed into a carton, which is combined with other devices in a shipping box. A manufacturer can test the carton or the shipping box. Testing at the carton level provides some more flexibility in the larger shipping container, but may require more protections and testing may be more expensive in the short term.
It’s an important consideration because once a product has been tested and validated for specific shipping details, manufacturers should stick to those materials and processes going forward. Understanding how packaging and shipping needs may evolve in the future can help determine which level is the most effective now and down the road.
3. Utilize dunnage parts in testing
One way to reduce the resources and financial investment needed to run distribution simulation tests is to replace actual products with representative material – also known as “dunnage.” Dunnage can be scrap material or dummy parts, but it must share key characteristics with the actual product. It has to be a similar size, weight, mass, etc.
Better Distribution Simulation Testing with a Proven Partner
In many cases, the right partner can help determine testing requirements and flag issues that might come up before the testing even begins. An organization like Life Science Outsourcing can help manufacturers from start-ups to established OEMs streamline the process through more efficient sample sizes, determining the appropriate level to test at, and utilizing dunnage to reduce costs.