Pooling units of platelets from multiple donors is a well-accepted strategy to reduce biological variability in human platelet lysate (hPL). Individual donor samples can vary significantly, whether this is a variation in platelet counts, growth factor contents, or response to processing, which occurs naturally. Pooling essentially takes the average of these differences and provides a more uniform, consistent product.
When you work with single-donor hPL, while all products from that donor will be the same, you could see subtle changes in things like cell proliferation, morphology, or gene expression every time you run a batch of cells. However, with pooled hPL, you can expect consistent results across experiments, which is fundamentally important for scientific rigor. This consistency gives labs confidence in comparing datasets from days, passages, or centers.
Pooling also lends itself well to scale-up. Although most studies begin small, as they scale up to larger bioprocessing, pooling is simpler and cheaper than doing single-donor batches.
Most transparent suppliers have donor screening reports, performance reports, and batch performance data. They can show that a given lot has met standard specifications, and researchers can match by lot ID and production date. The documentation and the ability to track batch/treatment selection is extremely important for publication reliability, and good performance methodologies for process validation in regenerative medicine.