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Scaling
Published in R. C. Richard Davison, Paul M. Smith, James Hopker, Michael J. Price, Florentina Hettinga, Garry Tew, Lindsay Bottoms, Sport and Exercise Physiology Testing Guidelines: Volume I – Sport Testing, 2022
McMahon (1973) identified a key complication to simple surface-law considerations and elasticity: the change in relative size of segments that occurs during growth and development (Medawar, 1944). As humans grow and increase absolutely in BM and other anthropometric dimensions, the relative sizes of each of the body’s segments change. For example, the head of an infant is proportionally larger than that of an adult. Conversely, the length of adult legs is a greater proportion of stature than a child’s. This change in relative proportions is allometric, but unlike for regular objects such as cubes and spheres, it is termed non-isometric.
Pharmacokinetics
Published in Samuel C. Morris, Cancer Risk Assessment, 2020
Allometry describes the disporportionate relationship of the size or function of isolated features in animals with body size or mass (Lindstedt, 1987). Although all mammals share much in common in bodily structure and function, larger animals are not proportionally scaled to smaller animals. In larger animals, for example, the skeleton comprises a greater proportion of the total mass than in small animals while smaller animals have a higher metabolism rate per unit mass. This relationship is generally described as a power function:
The brain
Published in Francesco E. Marino, Human Fatigue, 2019
However, regardless of what the exponent might be (noting that previous research has suggested exponents ranging from 0.3 to 3.0; Stevens 1957), it is worthwhile understanding (1) what purpose the exponent plays in psychophysical relations beyond its quantification, and (2) what advantage this relationship provided during our evolutionary past and how it relates to fatigue. The answers to these questions are not particularly apparent, but we are able to infer from previous work that has established an allometric law that pervades biological diversity (Porter & Brand 1993; West et al. 1997). Although allometry specifically describes relations of size of different organs or parts of an organism, it is now accepted that a 3/4 scaling law has been established by nature as a way of placing constraints on body size relative to the rates at which resources are used from the environment, transported and transformed within the body (West et al. 1997). Similarly, an exponent related to apparent and perceived exertion based on the accelerating growth of sensation would also constrain the organism within its biological limitations.
Aldehyde oxidase mediated drug metabolism: an underpredicted obstacle in drug discovery and development
Published in Drug Metabolism Reviews, 2022
Siva Nageswara Rao Gajula, Tanaaz Navin Nathani, Rashmi Madhukar Patil, Sasikala Talari, Rajesh Sonti
The allometric scaling in biology estimates how the traits scale or process with one another. In drug discovery, allometric scaling predicts human physiological traits (e.g. metabolic rate) based on animal studies’ data. Allometric scaling is calculated using the mathematical equation Y = a (bodyweight)b, where Y is the parameter of interest, a and b are the allometric coefficient and exponent, respectively. The allometric scaling exponent, b, is 0.75 in clearance studies, predicting the drug clearance per 1.73 m2 (average body surface area; Zhang 2014). Allometric scaling involves single species scaling (SSS) and multi-species allometry (MA). Crouch and colleagues proposed an in vitro allometric scaling approach consisting of SSS and MA. Guinea pigs, minipigs, and monkeys were more successful in predicting human AO mediated clearance than data obtained from rodents. Thus, species selection for further PK testing and allometric scaling of human clearance should be based on species with comparable predicted extraction ratios to humans (Crouch et al. 2018).
Allometric scaling of therapeutic monoclonal antibodies in preclinical and clinical settings
Published in mAbs, 2021
Eva Germovsek, Ming Cheng, Craig Giragossian
The main goal of using allometry in clinical development is either to describe the pediatric and/or adult PK or to extrapolate PK information from adults to the pediatric patients, and so support the design of the pediatric clinical studies, help decide on a starting dose, or optimize a dosing/sampling regimen.3,4,21,95 It may also be used to waive certain unnecessary pediatric trials, and hence avoid ethical and practical concerns that can occur with pediatric trials.8,10,57 Allometric scaling approaches are thus regularly used for pediatric PK extrapolation, and are applicable to small-molecule drugs20,95,134 and also mAbs.1,7,15,47 Allometric weight scaling of clinical PK data is typically done within a population PK approach, due to the abovementioned advantages, namely the ability to analyze sparse data (common in adult trials beyond Phase 1 and typical for pediatric studies), and possibility to identify and include covariates that affect PK, facilitating (pediatric) dose selection.15,95
First dose in neonates: pharmacokinetic bridging study from juvenile mice to neonates for drugs metabolized by CYP3A
Published in Xenobiotica, 2020
Pan-Pan Ye, Yi Zheng, Bin Du, Xi-Ting Liu, Bo-Hao Tang, Min Kan, Yue Zhou, Guo-Xiang Hao, Xin Huang, Le-Qun Su, Wen-Qi Wang, Feng Yu, Wei Zhao
There are about five inter-species scaling methods commonly used in bridging studies for CL (Kang & Lee, 2011; Mahmood, 2007): weight normalization, simple allometry, simple allometry with fixed exponent 0.75, simple allometry with a correction factor for brain weight and simple allometry with a correction factor for MLP. Our results showed that weight normalization, simple allometry, and simple allometry with fixed exponent 0.75 were not suitable for the prediction of CL in neonates because the mean fold-error for CL was 18.44, 26.35 and 31.97 for MDZ, and 4.64, 29.22 and 6.78 for CLD, respectively. It has shown that the exponent of simple allometry was changeable for different species (Mahmood, 2009). Previous studies have shown that brain weight and MLP could be used in inter-species bridging (Mahmood, 2009; Suresh et al., 2018). Our results supported a more accurate prediction using MLP than brain weight. The mean fold-error for CL was 0.01 and 0.02 of MDZ and CLD using brain weight. While for simple allometry with an MLP correction factor, the estimated mean fold-error of CL for MDZ and CLD was only 0.75 and 0.94, respectively.