Talk abstracts

Talk on Wednesday 10:50-11:05am submitted by Kelsey Schafer

What would it take to diagnose Alzheimer's disease? A predictive study using pharmacokinetic modeling of PET imaging agents

Kelsey Schafer (Department of Molecular and Cellular Biochemistry, Ohio State University), Sohee Kim (Department of Molecular and Cellular Biochemistry, Ohio State University), Anastasios Matzavinos (Department of Mathematics, Iowa State University), Jeff Kuret (Department of Molecular and Cellular Biochemistry, Ohio State University)

Abstract:
Whole-brain imaging is a promising strategy for premortem detection of tau-bearing neurofibrillary lesions that accumulate in Alzheimer's disease. However, the approach is complicated by the high concentrations of potentially confounding binding sites presented by beta-amyloid plaques. To predict the contributions of relative binding affinity and binding site density to the imaging-dynamics and selectivity of a hypothetical tau-directed radiotracer, a nonlinear, four-tissue compartment pharmacokinetic model of diffusion-mediated radiotracer uptake and distribution was developed. Initial estimates of nonspecific binding and brain uptake parameters were made by fitting data from a previously published kinetic study of Pittsburgh Compound B, an established amyloid-directed radiotracer. The resulting estimates were then used to guide simulations of tau binding selectivity while assuming early-stage accumulation of disease pathology. The simulations suggest that for tau aggregates to represent at least 80% of specific binding signal, binding affinity or density selectivities for tau over beta-amyloid should be at least 20- or 50-fold, respectively. The simulations also suggest, however, that overcoming nonspecific binding will be an additional challenge for tau-directed radiotracers owing to low concentrations of available binding sites. Overall, nonlinear modeling can provide insight into the performance characteristics needed for tau-directed radiotracers in vivo.

References:
Schafer, K. N., S. Kim, et al. (2012).

Keywords: Alzheimers disease, Pharmacokinetic modeling, Whole brain imaging