title: A guide to rational dosing of monoclonal antibodies.
abstract: OBJECTIVE
  Dosing of therapeutic monoclonal antibodies (mAbs) is often based on body size, with the perception that body size-based dosing would reduce inter-subject variability in drug exposure. However, most mAbs are target specific with a relatively large therapeutic window and generally a small contribution of body size to pharmacokinetic variability. Therefore, the dosing paradigm for mAbs should be assessed in the context of these unique characteristics. The objective of this study was to review the current dosing strategy and to provide a scientific rationale for dosing of mAbs using a modelling and simulation approach.
  
  
  METHODS
  In this analysis, the body weight-based or body weight-independent (fixed) dosing regimens for mAbs were systematically evaluated. A generic two-compartment first-order elimination model was developed. Individual or population pharmacokinetic profiles were simulated as a function of the body weight effects on clearance (θ(BW_CL)) and on the central volume of distribution (θ(BW_V1)). The variability in exposure (the area under the serum concentration-time curve [AUC], trough serum concentration [C(min)] and peak serum concentration [C(max)]) was compared between body weight-based dosing and fixed dosing in the entire population. The deviation of exposure for light and heavy subjects from median body weight subjects was also measured. The simulation results were then evaluated with clinical pharmacokinetic characteristics of various mAbs that were given either by body weight-based dosing or by fixed dosing in the case study.
  
  
  RESULTS
  Results from this analysis demonstrated that exposure variability was dependent on the magnitude of the body weight effect on pharmacokinetics. In contrast to the conventional assumption, body weight-based dosing does not always offer advantages over fixed dosing in reducing exposure variability. In general, when the exponential functions of θ(BW_CL) and θ(BW_V1) in the population pharmacokinetic model are <0.5, fixed dosing results in less variability and less deviation than body weight-based dosing; when both θ(BW_CL) and θ(BW_V1) are >0.5, body weight-based dosing results in less variability and less deviation than fixed dosing. In the scenarios when either θ(BW_CL) or θ(BW_V1) is >0.5, the impact on exposure variability is different for each exposure measure. The case study demonstrated that most mAbs had little effect or a moderate body weight effect (θ(BW_CL) and θ(BW_V1) <0.5 or ∼0.5). The difference of variability in exposure between body weight-based and fixed dosing is generally less than 20% and the percentages of deviation for light and heavy subpopulations are less than 40%.
  
  
  CONCLUSIONS
  The analysis provided insights into the conditions under which either fixed or body weight-based dosing would be superior in reducing pharmacokinetic variability and exposure differences between light and heavy subjects across the population. The pharmacokinetic variability introduced by either dosing regimen is moderate relative to the variability generally observed in pharmacodynamics, efficacy and safety. Therefore, mAb dosing can be flexible. Given many practical advantages, fixed dosing is recommended to be the first option in first-in-human studies with mAbs. The dosing strategy in later stages of clinical development could then be determined based on combined knowledge of the body weight effect on pharmacokinetics, safety and efficacy from the early clinical trials.
authors.affiliation: Genentech Inc., South San Francisco, CA, USA. dresser.mark@gene.com
authors.forename: Shuang
authors.initials: S
authors.lastname: Bai
authors.forename: Karin
authors.initials: K
authors.lastname: Jorga
authors.forename: Yan
authors.initials: Y
authors.lastname: Xin
authors.forename: Denise
authors.initials: D
authors.lastname: Jin
authors.forename: Yanan
authors.initials: Y
authors.lastname: Zheng
authors.forename: Lisa A
authors.initials: LA
authors.lastname: Damico-Beyer
authors.forename: Manish
authors.initials: M
authors.lastname: Gupta
authors.forename: Meina
authors.initials: M
authors.lastname: Tang
authors.forename: David E
authors.initials: DE
authors.lastname: Allison
authors.forename: Dan
authors.initials: D
authors.lastname: Lu
authors.forename: Yi
authors.initials: Y
authors.lastname: Zhang
authors.forename: Amita
authors.initials: A
authors.lastname: Joshi
authors.forename: Mark J
authors.initials: MJ
authors.lastname: Dresser
mesh_terms: D000328:Adult; D000911:Antibodies, Monoclonal / Q000008:administration & dosage* / Q000097:blood / Q000493:pharmacokinetics* / Q000627:therapeutic use; D001830:Body Surface Area; D001835:Body Weight; D003198:Computer Simulation; D016208:Databases, Factual; D003663:Decision Trees; D004305:Dose-Response Relationship, Drug; D005260:Female; D006801:Humans; D008297:Male; D008657:Metabolic Clearance Rate; D008954:Models, Biological
chemical_list: D000911:Antibodies, Monoclonal