TY - JOUR
T1 - Developing a Computational Pharmacokinetic Model of Systemic Snakebite Envenomation and Antivenom Treatment
AU - Morris, Natalie M
AU - Blee, Johanna
AU - Hauert, Sabine
N1 - Funding Information:
N.M.M would like to acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC) grant number EP/L016494/1 . S.H and J.A.B were funded by EU Horizon 2020 (grant number 800983 ) and Cancer Research UK (grant number C18281/A29019 ).
Publisher Copyright:
© 2022 The Authors
PY - 2022/6/20
Y1 - 2022/6/20
N2 - Snakebite envenomation is responsible for over 100,000 deaths and 400,000 cases of disability annually, most of which are preventable through access to safe and effective antivenoms. Snake venom toxins span a wide molecular weight range, influencing their absorption, distribution, and elimination within the body. In recent years, a range of scaffolds have been applied to antivenom development. These scaffolds similarly span a wide molecular weight range and subsequently display diverse pharmacokinetic behaviours. Computational simulations represent a powerful tool to explore the interplay between these varied antivenom scaffolds and venoms, to assess whether a pharmacokinetically optimal antivenom exists. The purpose of this study was to establish a computational model of systemic snake envenomation and treatment, for the quantitative assessment and comparison of conventional and next-generation antivenoms. A two-compartment mathematical model of envenomation and treatment was defined and the system was parameterised using existing data from rabbits. Elimination and biodistribution parameters were regressed against molecular weight to predict the dynamics of IgG, F(ab’)2, Fab, scFv, and nanobody antivenoms, spanning a size range of 15-150 kDa. As a case study, intramuscular envenomation by Naja sumatrana (equatorial spitting cobra) and its treatment using Fab, F(ab’)2, and IgG antivenoms was simulated. Variable venom dose tests were applied to visualise effective antivenom dose levels. Comparisons to existing antivenoms and experimental rescue studies highlight the large dose reductions that could result from recombinant antivenom use. This study represents the first comparative in silico model of snakebite envenomation and treatment.
AB - Snakebite envenomation is responsible for over 100,000 deaths and 400,000 cases of disability annually, most of which are preventable through access to safe and effective antivenoms. Snake venom toxins span a wide molecular weight range, influencing their absorption, distribution, and elimination within the body. In recent years, a range of scaffolds have been applied to antivenom development. These scaffolds similarly span a wide molecular weight range and subsequently display diverse pharmacokinetic behaviours. Computational simulations represent a powerful tool to explore the interplay between these varied antivenom scaffolds and venoms, to assess whether a pharmacokinetically optimal antivenom exists. The purpose of this study was to establish a computational model of systemic snake envenomation and treatment, for the quantitative assessment and comparison of conventional and next-generation antivenoms. A two-compartment mathematical model of envenomation and treatment was defined and the system was parameterised using existing data from rabbits. Elimination and biodistribution parameters were regressed against molecular weight to predict the dynamics of IgG, F(ab’)2, Fab, scFv, and nanobody antivenoms, spanning a size range of 15-150 kDa. As a case study, intramuscular envenomation by Naja sumatrana (equatorial spitting cobra) and its treatment using Fab, F(ab’)2, and IgG antivenoms was simulated. Variable venom dose tests were applied to visualise effective antivenom dose levels. Comparisons to existing antivenoms and experimental rescue studies highlight the large dose reductions that could result from recombinant antivenom use. This study represents the first comparative in silico model of snakebite envenomation and treatment.
KW - Computational Modelling
KW - synthetic biology
KW - Snakebite
KW - Pharmacokinetics
KW - Venom
KW - In silico modelling
KW - Mathematical Modelling
KW - Antivenom
U2 - 10.1016/j.toxicon.2022.06.006
DO - 10.1016/j.toxicon.2022.06.006
M3 - Article (Academic Journal)
C2 - 35716719
SN - 0041-0101
VL - 215
SP - 77
EP - 90
JO - Toxicon
JF - Toxicon
ER -