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Langevin B, Singh P, Plett PA, Sampson CH, Masters A, Gibbs A, Faria ED, Triesler S, Zodda A, Jackson IL, Orschell CM, Gopalakrishnan M, Pelus LM. Pharmacokinetics and Biodistribution of 16,16 dimethyl Prostaglandin E2 in Non-Irradiated and Irradiated Mice and Non-Irradiated Non-Human Primates. Radiat Res 2024; 201:7-18. [PMID: 38019093 PMCID: PMC11163368 DOI: 10.1667/rade-23-00040.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 10/23/2023] [Indexed: 11/30/2023]
Abstract
Exposure to high-dose ionizing radiation can lead to life-threatening injuries and mortality. Bone marrow is the most sensitive organ to radiation damage, resulting in the hematopoietic acute radiation syndrome (H-ARS) with the potential sequelae of infection, hemorrhage, anemia, and death if untreated. The development of medical countermeasures (MCMs) to protect or mitigate radiation injury is a medical necessity. In our well-established murine model of H-ARS we have demonstrated that the prostaglandin E2 (PGE2) analog 16,16 dimethyl-PGE2 (dmPGE2) has survival efficacy as both a radioprotectant and radiomitigator. The purpose of this study was to investigate the pharmacokinetics (PK) and biodistribution of dmPGE2 when used as a radioprotector in irradiated and non-irradiated inbred C57BL/6J mice, PK in irradiated and non-irradiated Jackson Diversity Outbred (JDO) mice, and the PK profile of dmPGE2 in non-irradiated non-human primates (NHPs). The C57BL/6J and JDO mice each received a single subcutaneous (SC) dose of 35 ug of dmPGE2 and were randomized to either receive radiation 30 min later or remain non-irradiated. Plasma and tissue PK profiles were established. The NHP were dosed with 0.1 mg/kg by SC administration and the PK profile in plasma was established. The concentration time profiles were analyzed by standard non-compartmental analysis and the metrics of AUC0-Inf, AUC60-480 (AUC from 60-480 min), Cmax, and t1/2 were evaluated. AUC60-480 represents the postirradiation time frame and was used to assess radiation effect. Overall, AUC0-Inf, Cmax, and t1/2 were numerically similar between strains (C57BL/6J and JDO) when combined, regardless of exposure status (AUC0-Inf: 112.50 ng·h/ml and 114.48 ng·h/ml, Cmax: 44.53 ng/ml and 63.96 ng/ml; t1/2: 1.8 h and 1.1 h, respectively). PK metrics were numerically lower in irradiated C57BL/6J mice than in non-irradiated mice [irradiation ratio: irradiated values/non-irradiated values = 0.71 for AUC60-480 (i.e., 29% lower), and 0.6 for t1/2]. In JDO mice, the radiation ratio was 0.53 for AUC60-480 (i.e., 47% lower), and 1.7 h for t1/2. The AUC0-Inf, Cmax, and t1/2 of the NHPs were 29.20 ng·h/ml, 7.68 ng/ml, and 3.26 h, respectively. Despite the numerical differences seen between irradiated and non-irradiated groups in PK parameters, the effect of radiation on PK can be considered minimal based on current data. The biodistribution in C57BL/6J mice showed that dmPGE2 per gram of tissue was highest in the lungs, regardless of exposure status. The radiation ratio for the different tissue AUC60-480 in C57BL/6J mice ranged between 0.5-1.1 (50% lower to 10% higher). Spleen, liver and bone marrow showed close to twice lower exposures after irradiation, whereas heart had a 10% higher exposure. Based on the clearance values from mice and NHP, the estimated allometric scaling coefficient was 0.81 (95% CI: 0.75, 0.86). While slightly higher than the current literature estimates of 0.75, this scaling coefficient can be considered a reasonable estimate and can be used to scale dmPGE2 dosing from animals to humans for future trials.
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Affiliation(s)
- Brooke Langevin
- Center for Translational Medicine, University of Maryland School of Pharmacy, Baltimore, Maryland 21201
| | - Pratibha Singh
- Department of Medicine, Division of Hematology/Oncology, Indiana University School of Medicine, Indianapolis, Indiana 46202
| | - P. Artur Plett
- Department of Medicine, Division of Hematology/Oncology, Indiana University School of Medicine, Indianapolis, Indiana 46202
| | - Carol H. Sampson
- Department of Medicine, Division of Hematology/Oncology, Indiana University School of Medicine, Indianapolis, Indiana 46202
| | - Andi Masters
- Clinical Pharmacology Analytical Core, Indiana University School of Medicine, IU Simon Comprehensive Cancer Center, Indianapolis, Indiana 46202
| | - Allison Gibbs
- Division of Translational Radiation Sciences, Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Eduardo De Faria
- Division of Translational Radiation Sciences, Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Sarah Triesler
- Division of Translational Radiation Sciences, Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Andrew Zodda
- Division of Translational Radiation Sciences, Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Isabel L. Jackson
- Division of Translational Radiation Sciences, Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201
| | - Christie M. Orschell
- Department of Medicine, Division of Hematology/Oncology, Indiana University School of Medicine, Indianapolis, Indiana 46202
| | - Mathangi Gopalakrishnan
- Center for Translational Medicine, University of Maryland School of Pharmacy, Baltimore, Maryland 21201
| | - Louis M. Pelus
- Department of Medicine, Division of Hematology/Oncology, Indiana University School of Medicine, Indianapolis, Indiana 46202
- Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, Indiana 46202
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Rayner CR, Smith PF, Andes D, Andrews K, Derendorf H, Friberg LE, Hanna D, Lepak A, Mills E, Polasek TM, Roberts JA, Schuck V, Shelton MJ, Wesche D, Rowland‐Yeo K. Model-Informed Drug Development for Anti-Infectives: State of the Art and Future. Clin Pharmacol Ther 2021; 109:867-891. [PMID: 33555032 PMCID: PMC8014105 DOI: 10.1002/cpt.2198] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 02/05/2021] [Indexed: 12/13/2022]
Abstract
Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.
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Affiliation(s)
- Craig R. Rayner
- CertaraPrincetonNew JerseyUSA
- Monash Institute of Pharmaceutical SciencesMonash UniversityMelbourneVictoriaAustralia
| | | | - David Andes
- University of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Kayla Andrews
- Bill & Melinda Gates Medical Research InstituteCambridgeMassachusettsUSA
| | | | | | - Debra Hanna
- Bill & Melinda Gates FoundationSeattleWashingtonUSA
| | - Alex Lepak
- University of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | - Thomas M. Polasek
- CertaraPrincetonNew JerseyUSA
- Centre for Medicines Use and SafetyMonash UniversityMelbourneVictoriaAustralia
- Department of Clinical PharmacologyRoyal Adelaide HospitalAdelaideSouth AustraliaAustralia
| | - Jason A. Roberts
- Faculty of MedicineUniversity of Queensland Centre for Clinical ResearchThe University of QueenslandBrisbaneQueenslandAustralia
- Departments of Pharmacy and Intensive Care MedicineRoyal Brisbane and Women’s HospitalBrisbaneQueenslandAustralia
- Division of Anaesthesiology Critical Care Emergency and Pain MedicineNîmes University HospitalUniversity of MontpellierMontpellierFrance
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Wu K, Choi S, Bergman K, Seo S. Antimicrobial Dose Selection under the Animal Rule. Clin Pharmacol Ther 2021; 109:971-976. [DOI: 10.1002/cpt.2201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 02/03/2021] [Indexed: 11/08/2022]
Affiliation(s)
- Kunyi Wu
- Office of Clinical Pharmacology Office of Translational Sciences Center for Drug Evaluation and Research (CDER) US Food and Drug Administration (FDA) Silver Spring Maryland USA
| | - Su‐Young Choi
- Office of Clinical Pharmacology Office of Translational Sciences Center for Drug Evaluation and Research (CDER) US Food and Drug Administration (FDA) Silver Spring Maryland USA
| | - Kimberly Bergman
- Office of Clinical Pharmacology Office of Translational Sciences Center for Drug Evaluation and Research (CDER) US Food and Drug Administration (FDA) Silver Spring Maryland USA
| | - Shirley Seo
- Office of Clinical Pharmacology Office of Translational Sciences Center for Drug Evaluation and Research (CDER) US Food and Drug Administration (FDA) Silver Spring Maryland USA
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Wu K, Bergman KL. Dose Selection in a Pandemic: A Framework Informed by the FDA Animal Rule. Clin Transl Sci 2020; 14:5-7. [PMID: 33201590 PMCID: PMC7753767 DOI: 10.1111/cts.12936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/09/2020] [Accepted: 11/15/2020] [Indexed: 12/02/2022] Open
Affiliation(s)
- Kunyi Wu
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA
| | - Kimberly L Bergman
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, Maryland, USA
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