title: An integrated multiple-analyte pharmacokinetic model to characterize trastuzumab emtansine (T-DM1) clearance pathways and to evaluate reduced pharmacokinetic sampling in patients with HER2-positive metastatic breast cancer.
abstract: OBJECTIVE
  Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate recently approved by the US Food and Drug Administration for the treatment of human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer previously treated with trastuzumab and taxane chemotherapy. It comprises the microtubule inhibitory cytotoxic agent DM1 conjugated to the HER2-targeted humanized monoclonal antibody trastuzumab via a stable linker. To characterize the pharmacokinetics of T-DM1 in patients with metastatic breast cancer, concentrations of multiple analytes were quantified, including serum concentrations of T-DM1 conjugate and total trastuzumab (the sum of conjugated and unconjugated trastuzumab), as well as plasma concentrations of DM1. The clearance of T-DM1 conjugate is approximately 2 to 3 times faster than its parent antibody, trastuzumab. However, the clearance pathways accounting for this faster clearance rate are unclear. An integrated population pharmacokinetic model that simultaneously fits the pharmacokinetics of T-DM1 conjugate and total trastuzumab can help to elucidate the clearance pathways of T-DM1. The model can also be used to predict total trastuzumab pharmacokinetic profiles based on T-DM1 conjugate pharmacokinetic data and sparse total trastuzumab pharmacokinetic data, thereby reducing the frequency of pharmacokinetic sampling.
  
  
  METHODS
  T-DM1 conjugate and total trastuzumab serum concentration data, including baseline trastuzumab concentrations prior to T-DM1 treatment, from phase I and II studies were used to develop this integrated population pharmacokinetic model. Based on a hypothetical T-DM1 catabolism scheme, two-compartment models for T-DM1 conjugate and trastuzumab were integrated by assuming a one-step deconjugation clearance from T-DM1 conjugate to trastuzumab. The ability of the model to predict the total trastuzumab pharmacokinetic profile based on T-DM1 conjugate pharmacokinetics and various sampling schemes of total trastuzumab pharmacokinetics was assessed to evaluate total trastuzumab sampling schemes.
  
  
  RESULTS
  The final model reflects a simplified catabolism scheme of T-DM1, suggesting that T-DM1 clearance pathways include both deconjugation and proteolytic degradation. The model fits T-DM1 conjugate and total trastuzumab pharmacokinetic data simultaneously. The deconjugation clearance of T-DM1 was estimated to be ~0.4 L/day. Proteolytic degradation clearances for T-DM1 and trastuzumab were similar (~0.3 L/day). This model accurately predicts total trastuzumab pharmacokinetic profiles based on T-DM1 conjugate pharmacokinetic data and sparse total trastuzumab pharmacokinetic data sampled at preinfusion and end of infusion in cycle 1, and in one additional steady state cycle.
  
  
  CONCLUSIONS
  This semi-mechanistic integrated model links T-DM1 conjugate and total trastuzumab pharmacokinetic data, and supports the inclusion of both proteolytic degradation and deconjugation as clearance pathways in the hypothetical T-DM1 catabolism scheme. The model attributes a faster T-DM1 conjugate clearance versus that of trastuzumab to the presence of a deconjugation process and suggests a similar proteolytic clearance of T-DM1 and trastuzumab. Based on the model and T-DM1 conjugate pharmacokinetic data, a sparse pharmacokinetic sampling scheme for total trastuzumab provides an entire pharmacokinetic profile with similar predictive accuracy to that of a dense pharmacokinetic sampling scheme.
authors.affiliation: Genentech Inc., 1 DNA Way, South San Francisco, CA 94080, USA. lu.dan@gene.com
authors.forename: Dan
authors.initials: D
authors.lastname: Lu
authors.forename: Amita
authors.initials: A
authors.lastname: Joshi
authors.forename: Bei
authors.initials: B
authors.lastname: Wang
authors.forename: Steve
authors.initials: S
authors.lastname: Olsen
authors.forename: Joo-Hee
authors.initials: JH
authors.lastname: Yi
authors.forename: Ian E
authors.initials: IE
authors.lastname: Krop
authors.forename: Howard A
authors.initials: HA
authors.lastname: Burris
authors.forename: Sandhya
authors.initials: S
authors.lastname: Girish
mesh_terms: D000080044:Ado-Trastuzumab Emtansine; D061067:Antibodies, Monoclonal, Humanized / Q000097:blood / Q000493:pharmacokinetics*; D000970:Antineoplastic Agents / Q000097:blood / Q000493:pharmacokinetics*; D001943:Breast Neoplasms / Q000378:metabolism*; D005260:Female; D006801:Humans; D008453:Maytansine / Q000031:analogs & derivatives* / Q000097:blood / Q000493:pharmacokinetics; D008954:Models, Biological; D018719:Erb-b2 Receptor Tyrosine Kinases; D015203:Reproducibility of Results; D000068878:Trastuzumab
chemical_list: D000080044:Ado-Trastuzumab Emtansine; D061067:Antibodies, Monoclonal, Humanized; D000970:Antineoplastic Agents; D008453:Maytansine; D018719:Erb-b2 Receptor Tyrosine Kinases; D000068878:Trastuzumab; C508053:ERBB2 protein, human
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