Characterization of materials with biological applications and assessment of physiological effects of therapeutic interventions are critical for translating research to the clinic and preventing adverse reactions. Analytical techniques typically used to characterize targeted nanomaterials and tissues rely on bulk measurement. Therefore, the resulting data represent an average structure of the sample, masking stochastic (randomly generated) distributions that are commonly present. In this Perspective, we examine almost 20 years of work our group has done in different fields to characterize and control distributions. We discuss the analytical techniques and statistical methods we use and illustrate how we leverage them in tandem with other bulk techniques. We also discuss the challenges and time investment associated with taking such a detailed view of distributions as well as the risks of not fully appreciating the extent of heterogeneity present in many systems. Through three case studies showcasing our research on conjugated polymers for drug delivery,collagen in bone, and endogenous protein nanoparticles, we discusshow identification and characterization of distributions, i.e., amolecular view of the system, was critical for understanding the observedbiological effects. In all three cases, data would have been misinterpretedand insights missed if we had only relied upon spatially averageddata. Finally, we discuss how new techniques are starting to bridgethe gap between bulk and molecular level analysis, bringing more opportunityand capacity to the research community to address the challenges ofdistributions and their roles in biology, chemistry, and the translationof science and engineering to societal challenges.
展开▼
