8/2/2019 Dosing Obesity

1/4

CLINICAL PHARMACOLOGY & THERAPEUTICS|VOLUME 82 NUMBER 5 |NOVEMBER 2007 505

PERSPECTIVES

identified as a priority. Groups such asneonates and premature neonates, whosedisease burden may make them therapeu-tic orphans, need their unique situationaddressed, and every effort should bemade to include therapies for the differ-

ent age groups.e subcommittee went on to decidethat selection of medicines would, asa priority, reflect the needs of childrenunder age 12 years of age. Although itacknowledged the need to consider spe-cific medicines needs for adolescents aged12 to 18, it was agreed that this subgroupcan generally be treated with productsdesigned for and studied in adults. esubcommittee also discussed criteriafor selection of fixed-dose combinationproducts, pediatric age categories, pre-

ferred dosage forms for pediatric use, anda position paper on off-label use.

e subcommittee proposed the firstWHO Model List of Essential Medicinesfor Children and planned a comprehen-sive roadmap for the future, with a clearset of actions to be completed. Finally,specific areas were identified for furtherresearch and medicines developmentaddressing pediatric populations. Thefull report of the subcommittee will beposted on the WHO medicines website

(http://www.who.int/medicines/en).In conclusion, the WHO has taken

steps to map the global situation concern-ing access and use of pediatric medicinesand has designed specific activities to fillexisting gaps. Needless to say, there is ahuge unfinished agenda, and resourcesmust be harnessed within a short timeframe. Success will be dependent on thequality of the response and on our abil-ity to focus individual and collectiveresponsibility. With the well-coordinatedjoint efforts of all stakeholders, includingacademia, industry, governments, non-governmental organizations, and fund-ing agencies, progress can be achievedand help provided to children, especiallythose in less favored settings.

CONFLICT OF INTEREST

The authors declared no conflict of interest.

2007 ASCPT

1. Gazarian, M., Kelly, M., McPhee, J.R., Graudins,L.V., Ward, R.L. & Campbell, T.J. Off-label use ofmedicines: consensus recommendations for

evaluating appropriateness. Med. J. Aust. 185,544548 (2006).

2. Ceci, A. et al. Medicines for children licensedby the European Agency for the Evaluation ofMedicinal Products. Eur. J. Clin. Pharmacol. 58,495500 (2002).

3. Dunne, J. The European Regulation onmedicines for paediatric use. Paediatr. Respir. Rev.

8, 177183 (2007).4. Charlish, P. Clinical trials in paediatricpopulations.Regulatory Affairs J. 18, 465469(2007).

5. Impicciatore, P., Choonara, I., Clarkson, A.,Provasi, D., Pandolfini, C. & Bonati, M. Incidenceof adverse drug reactions in paediatric in/out-patients: a systematic review and meta-analysis

of prospective studies. Br. J. Clin. Pharmacol. 52,7783 (2001).

6. Carleton, B.C., Smith, M.A., Gelin, M.N. &Heathcote, S.C. Paediatric adverse drug reactionreporting: understanding and future directions.Can. J. Clin. Pharmacol. 14, e45e57 (2007).

7. Newton, P.N., Green, M.D., Fernandez, F.M., Day,N.P. & White, N.J. Counterfeit anti-infective drugs.Lancet Infect. Dis. 6, 602613 (2006).

8. Atemnkeng, M.A., De Cock, K. & Plaizier-Vercammen, J. Quality control of activeingredients in artemisinin-derivativeantimalarials within Kenya and DR Congo. Trop.Med. Int. Health12, 6874 (2007).

9. World Health Organization.Promoting Safety ofMedicines for Children (WHO, Geneva, 2007).

Dosing in Obesity: A SimpleSolution to a Big ProblemPY Han1, SB Duffull1,2, CMJ Kirkpatrick1 and B Green1

The global epidemic of obesity has led to an increased prevalence

of chronic diseases and need for pharmacological intervention.

However, little is known about the influence of obesity on the drug-

exposure profile, resulting in few clear dosing guidelines for the

obese. Here we present a semi-mechanistic model for lean body

weight (LBW) that we believe is sufficiently robust to quantify the

influence of body composition on drug clearance, and is therefore an

ideal metric for adjusting chronic dosing in the obese.

Obesity has reached epidemic propor-tions worldwide, and the obese can nolonger be considered a minority demo-graphic.1 Despite increased pharmaco-therapy among obese patients, there is apaucity of dosing guidelines for this pop-ulation. is could be partly attributedto insufficient knowledge about phar-macokinetic parameters as a function ofbody composition due to the exclusionof obese subjects from clinical trials (inwhich body composition is defined as thedifferentiation of lean tissue from bodyfat in an individual). In addition, therehas been no suitable size descriptor fordose adjustments across a wide range ofbody compositions.2 It should be notedthat dose adjustments referred to in this

commentary pertain to maintenancedoses, not loading doses.

is commentary aims to (i) presenta recent derivation of a size metric, leanbody weight (LBW), which takes intoaccount changes in body compositionthat occur with obesity, and (ii) pro-pose a hypothesis that LBW is sufficientto explain the influence of body com-position on clearance and can thereforeadequately predict drug exposure in theobese. We do this not only to highlightthe complexity of designing appropri-ate studies to investigate the impact ofobesity on drug clearance, but also toformally recommend that our hypoth-esis be the subject of future testing. Itis our belief that dose individualization

1School of Pharmacy, University of Queensland, Brisbane, Queensland, Australia; 2School of Pharmacy,

University of Otago, Dunedin, New Zealand. Correspondence: B Green (greenb@pharmacy.uq.edu.au)

doi:10.1038/sj.clpt.2007.6100381

http://www.who.int/medicines/en/mailto:greenb@pharmacy.uq.edu.auhttp://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381mailto:greenb@pharmacy.uq.edu.auhttp://www.who.int/medicines/en/

8/2/2019 Dosing Obesity

2/4

506 VOLUME 82 NUMBER 5 |NOVEMBER 2007|www.nature.com/cpt

PERSPECTIVES

can be significantly improved by under-standing the quantitative relationshipbetween body composition and drugclearance. We also believe that thisrelationship should be described by amechanistically derived dosing scalar,thereby enabling it to provide quanti-tative predictions about the impact ofbody composition on the drug-expo-sure profile. is goal is in line with the

Food and Drug Administrations (FDA)Critical Path Initiative,3 which seeks toimprove understanding of the expo-sureresponse relationship.

In clinical practice, conventionalmethods of dose adjustment via weight-based regimens, i.e., milligram per kilo-gram, assume that biological functionsare directly proportional to total bodyweight (WT). However, 99% of thebodys metabolic processes (includingclearance) take place within lean tissues.4We contend that using WT to calculatemaintenance doses for obese patients isscientifically unsound. e obese have alower LBW/WT ratio overall,5 althoughtheir total LBW is greater than that ofnormal-weight individuals. Because WTrepresents the integral of body compo-nents, it is too simplified for describingchanges in body composition that occurwith obesity. We believe that a two-com-partment model, with LBW as Compart-ment 1, is the simplest model needed toadequately describe body composition.

LBW represents the sum of cellularmass and nonfatty intercellular connectivetissue, such as bone (excluding fatty mar-row), tendons, ligaments, and basementmembranes.4 It should be noted that indi-viduals used in the derivation of JamesLBW equations in 1976 (maximum bodymass index (BMI) = 43 kg/m2; maximumWT = 122 kg)6 weighed considerably lessthan obese patients commonly found in

the clinic today (maximum BMI = 100kg/m2; maximum WT = 273 kg).7 isunderrepresentation of obese subjectsin James population (only 9.2% of studysubjects had a BMI > 30 kg/m2) resultedin LBW equations that provided biologi-cally implausible estimates of LBW in theform of negative values (Figure 1a).8

To overcome the limitations of Jamesempirical LBW equations, a semi-mech-anistic model for LBW, based on bio-impedance, was developed in 2005 in apopulation with wide-ranging WTs thatare representative of the current popula-tion. ese equations are shown below;further details on their derivation areavailable in Janmahasatian et al.9:For males:

For females:

One key advantage of the LBW2005model, apart from agreeing well withJames LBW equations over normalranges of height and WT, is that the esti-mate of LBW2005 never declines as WTincreases (Figure 1a). ese equations

also have good predictive properties whencompared with LBW derived from dual-energy X-ray absorptiometry (DXA),9 areference method for LBW estimation.

With LBW2005, we now have a robustsize descriptor capable of quantifyingchanges in hepatic and renal clearance forindividuals of a wide range of body com-positions, which sets the stage for a con-ceptual shi in the way we perceive therelationship between body compositionand clearance. is relationship translatesinto the following hypothesized observa-

tions, which are graphically depicted inFigure 1b:

Observation 1: Absolute clearance isgreater in obese individuals.

Observation 2: Clearance increasesnonlinearly with WT.

Observation 3: Clearance correlateslinearly with LBW.

Our proposal that LBW and clearanceare linearly related is based on mecha-nistic principles derived from priorbiological knowledge and differs from

earlier investigations that drew empiri-cal relationships between body compo-sition and clearance. It is probable thattechnical challenges in measuring andrelating pharmacokinetic parameters toLBW prevented the use of a mechanistic

Figure 1 Relationship between LBW and WT for males of a standardized height of 1.7 m.

(a)Comparison of LBW calculated using the semi-mechanistic LBW2005 equation (solid curve) and

James empirical LBW equation (dashed curve). James equation generates predicted LBW values that

increase to a peak before declining to negative values with increasing WT. (b)Graphical depiction of

the three observations. All individuals with a WT above 87.5 kg (vertical dashed line) were considered

obese (BMI > 30 kg/m2). Comparison of clearance on the left and right of the obesity line shows that

absolute clearance is greater in the obese than in the normal-weight subjects, illustrating Observation

1. Clearance (dashed curve) also increases nonlinearly with WT, illustrating Observation 2. The linear

relationship between clearance and LBW is shown by the LBW (solid curve) and clearance graphs

running parallel to each other, illustrating Observation 3.

Figure 2 Dose of enoxaparin prescribed for

patients of varying WTs. The solid line represents

the calculated dose of enoxaparin based on

the drug-label recommendation of 1 mg/kg.

Patients with higher WTs have a tendency to

be underdosed according to the label, because

physicians often reduce doses to adjust for

differences in body composition.

LBW2005

(kg)=9270 WT (kg)

6680 + 216 BMI (kg m2)

LBW2005

(kg)=9270 WT (kg)

8780 + 244 BMI (kg m2)

http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/doifinder/10.1038/sj.clpt.2007.6100381http://www.nature.com/cpthttp://www.nature.com/cpt

8/2/2019 Dosing Obesity

3/4

CLINICAL PHARMACOLOGY & THERAPEUTICS|VOLUME 82 NUMBER 5 |NOVEMBER 2007 507

PERSPECTIVES

approach when performing such stud-ies. Although prior investigators alludedto the possibility that excess adipose tis-sue influenced pharmacokinetic param-eters in the obese, we surmise that their

progress was hindered by the use of inap-propriate size descriptors such as idealbody weight (IBW).10 IBW is a functionof height and sex only, and does not takeinto account differences in body com-position. Use of IBW as a surrogate forlean mass is inherently flawed, becauseit assumes that individuals of the samesex and height have exactly the same ideal(and presumably lean) mass. Understand-ably, this approach confounds the abilityto identify the true impact of obesity and

body composition on drug clearance.Given the availability of methods to

precisely determine LBW (e.g., DXA,bioimpedance) and an improved under-standing of how LBW changes acrossindividuals of varying body composition(with the increased prevalence of obes-ity), we recommend that investigatorsdesign and analyze dose-exposure trialswith clearance expressed as a function ofLBW. Results from such studies can alsobe used to predict drug exposure in theobese, even if they were excluded from thestudies. is provides a distinct advantageover empirical dosing strategies based onWT, which are likely to result in overdosewhen extended to the obese. In fact, phy-sicians oen attempt to adjust for alteredbody composition in the obese by arbi-trarily reducing weight-based drug doses.A good example is the drug enoxaparin,which has a labeled dose of 1 mg/kg. Anobservational study (n = 50) has shownthat physicians do not prescribe 1 mg/kgin the obese (probably because of the risk

of adverse bleeding events) and arbitrar-ily reduce the dose to account for bodycomposition (Figure 2).11

Having recognized the shortcomingsof using empirical methodologies dur-

ing the drug-development process, theFDA launched the Critical Path Initia-tive in 2004 to promote the concept thatscientific tools for predicting and evalu-ating drug safety and efficacy should bedeveloped mechanistically.3Althoughempirical methodologies can ensure thatthe drug is right for its intended thera-peutic purposes by confirming its aver-age effectiveness on a population level,ensuring the right dose on an individu-alized basis can be achieved only by using

mechanistic approaches that build onimproved insights into the influence ofpatient variables on the dose exposureresponse relationship.12

Given that the concept of relating drugclearance to LBW rather than WT is rela-tively new, it is understandable that priorstudies were not designed specifically totest this hypothesis. We have reanalyzedrenal clearance data from a previousstudy using LBW2005 in which absoluteclearance, as well as clearance valuesnormalized by WT and LBW

2005for

normal-weight and obese subjects, werecompared using repeated-measures analy-sis of variance (Table 1) (unpublisheddata from S. Janmahasatian, S.B. Duffull,A. Chagnac, C.M.J. Kirkpatrick, and B.Green). e results of this study concurwith our hypothesis that drug clearancefor individuals of varying heights andWTs is the same aer adjusting for bodycomposition. ey also imply that LBW isa useful dosing scalar that is transportableacross all body compositions.

Although our hypothesis is novel, otherinvestigators have similarly recognizedthe limitations of using conventional dos-ing scalars in obese patients. Shibutani etal.13 observed that the absolute clear-

ance for a hepatically cleared drug (fen-tanyl) was significantly higher in obesepatients and that clearance increasednonlinearly with WT. They solved fortheir observations by deriving a sizemetric termed pharmacokinetic massthat increased linearly with clearance. Wehave compared their empirically derivedpharmacokinetic mass with our semi-mechanistic LBW model for subjects withWTs and heights from 35 to 165 kg and1.3 to 1.95 m, respectively, and found a

close correlation between the two sizedescriptors (R2 = 0.92 for males and R2= 0.94 for females). eir results agreewith Observations 1 and 2 and indirectlyaccord with Observation 3, thus provid-ing additional evidence in support ofour hypothesis.

We have also reviewed other stud-ies examining the influence of obesityon drug clearance published between1978 and 2004 (Supplementary TableS1 online). A complete reanalysis of thedata is not possible because of unavail-able published individual data and lackof studies specifically designed to test ourhypothesis. Of the 72 studies, only 5 usedLBW or a similar size metric (pharma-cokinetic mass). e remainder definedobesity as a function of IBW or BMI. einherent flaws of IBW as a surrogate forlean mass, as discussed above, only serveto confound the results. BMI is also anunsuitable body composition metric,because it does not distinguish betweenexcess fat and a larger muscle/bone mass.

Table 1 Renal clearance of normal-weight and obese subjects

Mean SD (range)

Normal-weight Obese P-value from repeated measures ANOVA

Absolute clearance (ml/min) 90.90 16.25(69.0 124.0)

131.07 34.62(85.0 216.0)

8/2/2019 Dosing Obesity

4/4