DESCRIPTION (provided by applicant): Transmission electron microscopy is a valuable technique for characterizing biological therapeutics, vaccines, drug delivery vehicles, and nanoparticles. There is considerable evidence that links the physical properties of these samples to their bio-distribution, safety, and efficacy. TEM imaging allows direct observation and quantification of these parameters, which include size distributions, shape distributions, concentrations, aggregation states, and 2D and 3D structure determinations. This wealth of information is especially useful when researchers must troubleshoot problems of unknown origin. As bio-therapeutics and nanoparticles increase in size and complexity, TEM is becoming increasingly important as an orthogonal complement to other biophysical methods. Despite the obvious utility of TEM as a direct technique for describing the physicochemical properties of samples in a variety of relevant biological environments, the cost per sample is a significant barrier to the method's widespread adoption, particularly for routine screening of samples. To address this, we will develop software focused on high-throughput data acquisition of multiple samples applied to a single grid substrate. Our long-term goal is to lower the cost per sample for TEM by at least an order of magnitude, and thus establish TEM as an affordable and ubiquitous technique for commercial R&D and testing.

PUBLIC HEALTH RELEVANCE: Characterization of nanoparticles is a critical aspect in the development of biological therapeutics, vaccines, drug delivery vehicles, and nanoparticles. The physical properties of biologics and nanoparticles are tightly linked to their functional behavior, and are thus a determining factor in their biodistribution, safety, efficacy and toxicity. Transmission electron microscopy is a direct and powerful characterization tool, but the high per- sample cost limits its routine use. We propose to dramatically reduce these costs by developing automation software that maximizes data acquisition throughput using multiplexed samples.