Related Experiment Video

Updated: May 8, 2026

Initial Evaluation of Antibody-conjugates Modified with Viral-derived Peptides for Increasing Cellular Accumulation and Improving Tumor Targeting
11:58

Initial Evaluation of Antibody-conjugates Modified with Viral-derived Peptides for Increasing Cellular Accumulation and Improving Tumor Targeting

Published on: March 8, 2018

Preclinical and clinical pharmacokinetic/pharmacodynamic considerations for antibody-drug conjugates

Puja Sapra1, Alison Betts, Joseph Boni

  • 1Bioconjugates Discovery and Development, Oncology Research Unit, Pfizer Worldwide Research and Development, Pearl River, NY, 10965, USA.

Expert Review of Clinical Pharmacology
|August 28, 2013
PubMed

Insights

Antibody-drug conjugates (ADCs) offer a promising cancer therapy. This review explores their clinical pharmacology, safety, and the development of PK/PD models to predict effective dosing for ADCs.

Area of Science:

  • Oncology
  • Pharmacology
  • Drug Development

Background:

  • Antibody-drug conjugates (ADCs) are an emerging class of therapeutics for cancer treatment.
  • ADCs combine targeted antibody delivery with potent cytotoxic payloads.
  • Approved and late-stage clinical ADCs are crucial for advancing cancer therapy.

Purpose of the Study:

  • To review the clinical pharmacology and safety of approved and late-stage ADCs.
  • To examine the influence of dosing on the pharmacokinetics/pharmacodynamics (PK/PD) and safety of ADCs.
  • To discuss the application of PK/PD models for predicting efficacious ADC doses.

Main Methods:

  • Review of clinical pharmacology and safety data for ADCs.
  • Analysis of ADCs utilizing DNA damaging agents (e.g., calicheamicin) and tubulin depolymerizing agents (e.g., auristatins, maytansinoids).
  • Development and validation of PK/PD models using preclinical and clinical data from approved ADCs (T-DM1, brentuximab vedotin).

Main Results:

  • Dose and dosage intervals significantly impact ADC PK/PD and safety profiles.
  • Validated PK/PD models can accurately predict clinical outcomes.
  • Examples include ado-trastuzumab emtansine (T-DM1) and brentuximab vedotin (SGN-35).

Conclusions:

  • PK/PD modeling is essential for optimizing ADC therapy.
  • These models can guide the selection of clinical efficacious doses for ADCs.
  • Further development of ADCs relies on understanding their complex PK/PD relationships.

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