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Drug Distribution Dynamics: History
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Contributor: Yu Peng

Drug distribution dynamics designates the quantitative study of the reversible transfer of a drug between the systemic circulation and the tissues and organs of the body over time, describing how the concentration of the drug in each anatomical region evolves as a function of the rates of blood perfusion, capillary permeability, and tissue binding [1]. The defining conceptual framework is the compartmental model: the one-compartment model treats the body as a single kinetically homogeneous unit, the two-compartment model resolves a central (plasma and well-perfused organs) and a peripheral (poorly perfused tissues) compartment, and physiologically based pharmacokinetic (PBPK) models partition the organism into anatomically realistic organ compartments connected by blood flow, each governed by its own partition coefficient and permeability rate limit [2]. A defining parameter of distribution dynamics is the volume of distribution, which relates the amount of drug in the body to its plasma concentration and, when measured at equilibrium, quantifies the extent of extravascular distribution [3]. Within pharmacology and nanomedicine research, the term encompasses the spatiotemporal distribution of nanocarriers and their payloads, in which particle size, surface chemistry, and the biological barriers of the target tissue determine the kinetics of accumulation and the uniformity of tissue exposure [4][5].

  • Volume of distribution
  • compartmental model
  • physiologically based pharmacokinetics
  • spatiotemporal distribution

Pharmacology and Nanomedicine Research·Drug Discovery·Pharmacology, Toxicology and Pharmaceutics·Life Sciences

References

  1. Michael Weiss; Distribution Clearance: Significance and Underlying Mechanisms. Pharm. Res. 2024, 41, 1391-1400, 10.1007/s11095-024-03738-7.
  2. Arthur J. Atkinson; Tsuen Ih Ruo; Marilynn C. Frederiksen; Physiological basis of multicompartmental models of drug distribution. Trends Pharmacol. Sci. 1991, 12, 96-101, 10.1016/0165-6147(91)90515-t.
  3. Thi Tuyet Van Tran; Hilal Tayara; Kil To Chong; Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction. Int. J. Mol. Sci. 2023, 24, 1815, 10.3390/ijms24031815.
  4. Mengmeng Qin; Heming Xia; Wenhao Xu; Binlong Chen; Yiguang Wang; The spatiotemporal journey of nanomedicines in solid tumors on their therapeutic efficacy. Adv. Drug Deliv. Rev. 2023, 203, 115137, 10.1016/j.addr.2023.115137.
  5. Horacio Cabral; Junjie Li; Kanjiro Miyata; Kazunori Kataoka; Controlling the biodistribution and clearance of nanomedicines. Nat. Rev. Bioeng. 2023, 2, 214-232, 10.1038/s44222-023-00138-1.
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