Math model could choose most effective drug delivery nanoparticle

With an increasing reliance on nanoparticles to deliver intravenous drug treatments and serve as imaging agents, how do you make sure they are powerful enough to reach their target? The answer: math.

More precisely, a Wayne State University team believes drug researchers can use a mathematical model to determine which nanoparticles are the most effective and the least toxic and when they will dissolve to release their drug payload. Read the research in detail in the journal Molecular Pharmaceutics.

In a nutshell, they drew their conclusion by studying how poly(lactic-co-glycolic) acid, or PLGA, breaks down in living tissue versus in the lab. In short, through their research on mice, researchers found that 200-nanometer PLGA particles broke down in the body more quickly than in vitro. But 500 nanometers degraded at a similar rate in both the body and in vitro. Another realization: 500-nanometer nanoparticles broke down more quickly in the liver versus the spleen. On the other hand, 200-nanometer-sized particles broke down at about the same rate in both organs.

What does this all mean? It says that the nanoparticles degrade differently, in the body compared to in vitro, and the rate of breakdown varies depending on the organ involved. Researcher Joshua Reineke and his team believe further testing in living organisms of various types of nanoparticles will help create a large database of information that will lead to a consistent mathematical model. And this formula, they assert, will zero in on the most effective, least toxic option to evaluate when a nanoparticle will release a given drug.

- read the release
- here's the journal abstract

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