UNLABELLED: Intraarterial microdosing (IAM) is a novel drug development approach combining intraarterial drug delivery and microdosing. We aimed to demonstrate that IAM leads to target exposure similar to that of systemic full-dose administration but with minimal systemic exposure. IAM could enable the safe, inexpensive, and early study of novel drugs at the first-in-human stage and the study of established drugs in vulnerable populations. METHODS: Insulin was administered intraarterially (ipsilateral femoral artery) or systemically to 8 CD IGS rats just before blood sampling or 60-min (18)F-FDG uptake PET imaging of ipsilateral and contralateral leg muscles (lateral gastrocnemius) and systemic muscles (spinotrapezius). The (18)F-FDG uptake slope analysis was used to compare the interventions. Plasma levels of insulin and glucose were compared using area under the curve calculated by the linear trapezoidal method. A physiologically based computational pharmacokinetics/pharmacodynamics model was constructed to simulate the relationship between the administered dose and response over time. RESULTS: (18)F-FDG slope analysis found no difference between IAM and systemic full-dose slopes (0.0066 and 0.0061, respectively; 95% confidence interval [CI], -0.024 to 0.029; P = 0.7895), but IAM slope was statistically significantly greater than systemic microdose (0.0018; 95% CI, -0.045 to -0.007; P = 0.0147) and sham intervention (-0.0015; 95% CI, 0.023-0.058; P = 0.0052). The pharmacokinetics/pharmacodynamics data were used to identify model parameters that describe membrane insulin binding and glucose-insulin dynamics. CONCLUSION: Target exposure after IAM was similar to systemic full dose administration but with minimal systemic effects. The computational pharmacokinetics/pharmacodynamics model can be generalized to predict whole-body response. Findings should be validated in larger, controlled studies in animals and humans using a range of targets and classes of drugs.
UNLABELLED: Intraarterial microdosing (IAM) is a novel drug development approach combining intraarterial drug delivery and microdosing. We aimed to demonstrate that IAM leads to target exposure similar to that of systemic full-dose administration but with minimal systemic exposure. IAM could enable the safe, inexpensive, and early study of novel drugs at the first-in-human stage and the study of established drugs in vulnerable populations. METHODS: Insulin was administered intraarterially (ipsilateral femoral artery) or systemically to 8 CD IGS rats just before blood sampling or 60-min (18)F-FDG uptake PET imaging of ipsilateral and contralateral leg muscles (lateral gastrocnemius) and systemic muscles (spinotrapezius). The (18)F-FDG uptake slope analysis was used to compare the interventions. Plasma levels of insulin and glucose were compared using area under the curve calculated by the linear trapezoidal method. A physiologically based computational pharmacokinetics/pharmacodynamics model was constructed to simulate the relationship between the administered dose and response over time. RESULTS: (18)F-FDG slope analysis found no difference between IAM and systemic full-dose slopes (0.0066 and 0.0061, respectively; 95% confidence interval [CI], -0.024 to 0.029; P = 0.7895), but IAM slope was statistically significantly greater than systemic microdose (0.0018; 95% CI, -0.045 to -0.007; P = 0.0147) and sham intervention (-0.0015; 95% CI, 0.023-0.058; P = 0.0052). The pharmacokinetics/pharmacodynamics data were used to identify model parameters that describe membrane insulin binding and glucose-insulin dynamics. CONCLUSION: Target exposure after IAM was similar to systemic full dose administration but with minimal systemic effects. The computational pharmacokinetics/pharmacodynamics model can be generalized to predict whole-body response. Findings should be validated in larger, controlled studies in animals and humans using a range of targets and classes of drugs.
Authors: Paul Morgan; Piet H Van Der Graaf; John Arrowsmith; Doug E Feltner; Kira S Drummond; Craig D Wegner; Steve D A Street Journal: Drug Discov Today Date: 2011-12-29 Impact factor: 7.851
Authors: T Burt; D MacLeod; K Lee; A Santoro; D K DeMasi; T Hawk; M Feinglos; M Rowland; R J Noveck Journal: Clin Transl Sci Date: 2017-07-08 Impact factor: 4.689
Authors: T Burt; K Yoshida; G Lappin; L Vuong; C John; S N de Wildt; Y Sugiyama; M Rowland Journal: Clin Transl Sci Date: 2016-03-30 Impact factor: 4.689