Derivation of occupational exposure levels (OELs) of Low-toxicity isometric biopersistent particles: how can the kinetic lung overload paradigm be used for improved inhalation toxicity study design and OEL-derivation? (Particle and Fibre Toxicology)

Background: Convincing evidence suggests that poorly soluble low-toxicity particles (PSP) exert two unifying major modes of action (MoA), in which one appears to be deposition-related acute, whilst the other is retention-related and occurs with particle accumulation in the lung and associated persistent inflammation. Either MoA has its study- and cumulative dose-specific adverse outcome and metric. Modeling procedures were applied to better understand as to which extent protocol variables may predetermine any specific outcome of study. The results from modeled and empirical studies served as basis to derive OELs from modeled and empirically confirmed directions. Results: This analysis demonstrates that the accumulated retained particle displacement volume was the most prominent unifying denominator linking the pulmonary retained volumetric particle dose to inflammogenicity and toxicity. However, conventional study design may not always be appropriate to unequivocally discriminate the surface thermodynamics-related acute adversity from the cumulative retention volume-related chronic adversity. Thus, in the absence of kinetically designed studies, it may become increasingly challenging to differentiate substance-specific deposition-related acute effects from the more chronic retained cumulative dose-related effects. Conclusion: It is concluded that the degree of dissolution of particles in the pulmonary environment seems to be generally underestimated with the possibility to attribute to toxicity due to decreased particle size and associated changes in thermodynamics and kinetics of dissolution. Accordingly, acute deposition-related outcomes become an important secondary variable within the pulmonary microenvironment. In turn, lung-overload related chronic adversities seem to be better described by the particle volume metric. This analysis supports the concept that `self-validating?, hypothesis-based computational study design delivers the highest level of unifying information required for the risk characterization of PSP. In demonstrating that the PSP under consideration is truly following the generic PSP-paradigm, this higher level of mechanistic information reduces the potential uncertainty involved with OEL derivation.