Using normal fat mass to account for body size and composition

Aims:    Allometry is the study of how body size is related to body function. In clinical medicine, size related differences in biological functions such as heart function (cardiac output, CO) and kidney function (glomerular filtration rate, GFR) are routinely scaled by body surface area (BSA). In contrast, a more fundamental theory (1) relates body mass to function, based on the energetic needs of cells and the structural overhead associated with larger mass. This biologically based allometric theory is consistent with previous "scaling laws" and has been confirmed by extensive cross-species observations in all domains of biology. Total body mass (TBM) can be thought of as being composed of fat mass (FAT) and (fat free mass (FFM). However, current allometric theory does not distinguish between these two components of body mass. The aim of this presentation is to show how allometric theory can be extended to describe body size and composition using the concept of normal fat mass (NFM).

Methods: Normal fat mass is defined by NFM=FFM + Ffat x FAT

Ffat is the fraction of FAT kg that contributes to functional body size relative to FFM kg.

 Results: For a wide variety of drugs, elimination and distribution are well described using theory based allometry and normal fat mass. NFM becomes FFM when Ffat=0 and TBM when Ffat=1.

Drug

Ffat  elimination

Ffat distribution

Subject population

Warfarin

0

0

264 adults (2)

Gemcitabine

0

0

56 adults (3)

Dexmedetomidine

0

0

40 adults (4)

Busulfan

0.509

0.203

1610 neonates-adults  (5)

Ethanol

1

0.390

108 adults (6)

Paracetamol

1

0.778

189 adults (7)

Propofol

1

1

70 adults (8)

 

References:

1.            West GB, Brown JH, Enquist BJ. The fourth dimension of life: fractal geometry and allometric scaling of organisms. Science. 1999;284(5420):1677-9.

2.            Xue L, Holford NHG, Miao L. Warfarin PKPD – Theory, Body Composition and Genotype. PAGE. 2016;25 Abstr 5759 [www.page-meeting.org/?abstract=5759].

3.            Tham LS, Wang LZ, Soo RA, Lee HS, Lee SC, Goh BC, et al. Does saturable formation of gemcitabine triphosphate occur in patients? Cancer Chemother Pharmacol. 2008;63(1):55-64.

4.            Cortinez LI, Anderson BJ, Holford NH, Puga V, de la Fuente N, Auad H, et al. Dexmedetomidine pharmacokinetics in the obese. Eur J Clin Pharmacol. 2015;doi:10.1007/s00228-015-1948-2.

5.            McCune JS, Bemer MJ, Barrett JS, Scott Baker K, Gamis AS, Holford NHG. Busulfan in Infant to Adult Hematopoietic Cell Transplant Recipients: A Population Pharmacokinetic Model for Initial and Bayesian Dose Personalization. Clin Cancer Res. 2014;20(3):754-63.

6.            Holford N, Jiang Y, Murry DJ, Brown TL, Gary Milavetz G. The Influence of Body Composition on Ethanol Pharmacokinetics using a Rate Dependent Extraction Model. PAGE. 2015;24 Abstr 3405 [www.page-meeting.org/?abstract=3405].

7.            Allegaert K, Olkkola KT, Owens KH, Van de Velde M, de Maat MM, Anderson BJ. Covariates of intravenous paracetamol pharmacokinetics in adults. BMC Anesthesiol. 2014;14:77.

8.            Cortinez LI, Anderson BJ, Penna A, Olivares L, Munoz HR, Holford NH, et al. Influence of obesity on propofol pharmacokinetics: derivation of a pharmacokinetic model. Br J Anaesth. 2010;105(4):448-56.