New Approaches for Modeling Radiopharmaceutical Pharmacokinetics Using Continuous Distributions of Rates

Future Prospective of Radiopharmaceuticals from Natural Compounds Using Iodine Radioisotopes as Theranostic Agents

Natural compounds provide precursors with various pharmacological activities and play an important role in discovering new chemical entities, including radiopharmaceuticals. In the development of new radiopharmaceuticals, iodine radioisotopes are widely used and interact with complex compounds including natural products. However, the development of radiopharmaceuticals from natural compounds with iodine radioisotopes has not been widely explored. This review summarizes the development of radiopharmaceuticals from natural compounds using iodine radioisotopes in the last 10 years, as well as discusses the challenges and strategies to improve future discovery of radiopharmaceuticals from natural resources. Literature research was conducted via PubMed, from which 32 research articles related to the development of natural compounds labeled with iodine radioisotopes were reported. From the literature, the challenges in developing radiopharmaceuticals from natural compounds were the purity and biodistribution. Despite the challenges, the development of radiopharmaceuticals from natural compounds is a golden opportunity for nuclear medicine advancement.

Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects

Mechanistic mathematical modeling of ionizing radiation (IR) effects has a long history spanning several decades. Models that mathematically represent current knowledge and hypotheses about how radiation damages cells and organs, leading to deleterious outcomes such as carcinogenesis, are particularly useful for estimating radiation risks at doses that are relevant for radiation protection, but are too low to provide a strong 'signal-to-noise ratio' in epidemiological or experimental studies with realistic sample sizes. Here, I discuss examples of models in several relevant areas, including radionuclide biokinetics, non-targeted IR effects, DNA double-strand break (DSB) rejoining and radiation carcinogenesis. I do not provide a detailed review of the vast modeling literature in these fields, but focus on concepts that we have implemented, such as using continuous probability distributions of exponential rates to model radionuclide biokinetics and DSB rejoining, and combining short and long time scales in carcinogenesis models. Improvements in models, including the ability to generate new hypotheses based on model predictions, may come from the introduction of additional novel concepts and from integrating multiple data types.

Effect of dose and dose rate on temporal γ-H2AX kinetics in mouse blood and spleen mononuclear cells in vivo following Cesium-137 administration

Background

Cesium-137 (¹³⁷Cs) is one of the major and most clinically relevant radionuclides of concern in a radiological dispersal device, “dirty bomb” scenario as well as in nuclear accidents and detonations. In this exposure scenario, a significant amount of soluble radionuclide(s) may be dispersed into the atmosphere as a component of fallout. The objectives of the present study were to investigate the effect of protracted ¹³⁷Cs radionuclide exposures on DNA damage in mouse blood and spleen mononuclear cells (MNCs) in vivo using the γ-H2AX biomarker, and to develop a mathematical formalism for these processes.

Results

C57BL/6 mice were injected with a range of ¹³⁷CsCl activities (5.74, 6.66, 7.65 and 9.28 MBq) to achieve total-body committed doses of ~ 4 Gy at Days 3, 5, 7, and 14. Close to 50% of ¹³⁷Cs was excreted by day 5, leading to a slower rate of decay for the remaining time of the study; ¹³⁷Cs excretion kinetics were independent of activity level within the tested range, and the absorbed radiation dose was determined by injected activity and time after injection. Measurements of γ-H2AX fluorescence in blood and spleen MNCs at each time point were used to develop a new biodosimetric mathematical formalism to estimate injected activity based on γ-H2AX fluorescence and time after injection. The formalism performed reasonably well on blood data at 2–5 days after injection: Pearson and Spearman’s correlation coefficients between actual and predicted activity values were 0.857 (p = 0.00659) and 0.929 (p = 0.00223), respectively.

Conclusions

Despite the complicated nature of the studied biological system and the time-dependent changes in radiation dose and dose rate due to radionuclide excretion and other processes, we have used the γ-H2AX repair kinetics to develop a mathematical formalism, which can relatively accurately predict injected ¹³⁷Cs activity 2–5 days after initial exposure. To determine the assay’s usefulness to predict retrospective absorbed dose for medical triage, further studies are required to validate the sensitivity and accuracy of the γ-H2AX response after protracted exposures.

Electronic supplementary material

The online version of this article (10.1186/s12860-019-0195-2) contains supplementary material, which is available to authorized users.

Usefulness of continuous probability distributions of rates for modelling radionuclide biokinetics in humans and animals

Modelling the biokinetics of radionuclide excretion or retention is important in nuclear medicine and following accidental/malicious radioactivity releases. Sums of discrete exponential decay rates are often used, but we hypothesized that continuous probability distributions (CPD) of decay rates can describe the data more parsimoniously and robustly. We tested this hypothesis on diverse human and animal data sets involving various radionuclides (including plutonium, strontium, caesium) measured in the laboratory and in regions contaminated by the Fukushima and Chernobyl nuclear accidents. We used four models on each data set: mono-exponential (ME) with one discrete decay rate, bi-exponential (BE) with two rates, gamma-exponential (GE) with a Gamma distribution of stretched-exponential rates, and power-decay (PD) with a Gamma distribution of power-decay rates. Information-theoretic model selection suggested that radionuclide biokinetics, e.g. for plutonium in humans, are often better described by CPD models like GE and PD, than by discrete rates (ME and BE). Extrapolation of models fitted to data at short times to longer times was frequently more robust for CPD formalisms. We suggest that using a set of several CPD and discrete-rate models, and comparing them by information-theoretic methods, is a promising strategy to enhance the analysis of radionuclide excretion and retention kinetics.