Development of a Translational Physiologically Based Pharmacokinetic Model for Antibody-Drug Conjugates: a Case Study with T-DM1

Khot, Antari; Tibbitts, Jay; Rock, Dan A.; Shah, Dhaval K.

doi:10.1208/s12248-017-0131-3

Cited by 26 publications

(18 citation statements)

References 34 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Later, Khot et al developed a PBPK model for T-DM1, with the platform PBPK model for the mAb linked to the small-molecule PBPK model for the payload through the proteolytic degradation and deconjugation processes of antibodydrug conjugates. 15 The degradation and distribution of the antibody-drug conjugate were assumed to be similar to the backbone mAb (ie, trastuzumab), and the deconjugation of DM1 from T-DM1 over time was estimated using plasma PK of total trastuzumab and T-DM1. The DM1 released from T-DM1, through either proteolytic degradation or deconjugation, was then served as input of the small-molecule PBPK model, which was established using biodistribution data of radiolabeled small-molecule [ 3 H]DM1 in rats.…”

Section: Pbpk Modeling Of Antibody-drug Conjugatesmentioning

confidence: 99%

Impact of Physiologically Based Pharmacokinetics, Population Pharmacokinetics and Pharmacokinetics/Pharmacodynamics in the Development of Antibody‐Drug Conjugates

Li¹,

Chen²,

Chen³

et al. 2020

The Journal of Clinical Pharma

View full text Add to dashboard Cite

Antibody-drug conjugates are important molecular entities in the treatment of cancer, with 8 antibody-drug conjugates approved by the US Food and Drug Administration since 2000 and many more in early-and late-stage clinical development. These conjugates combine the target specificity of monoclonal antibodies with the potent anticancer activity of small-molecule therapeutics. The complex structure of antibody-drug conjugates poses unique challenges to pharmacokinetic (PK) and pharmacodynamic (PD) characterization because it requires a quantitative understanding of the PK and PD properties of multiple different molecular species (eg, conjugate, total antibody, and unconjugated payload) in different tissues. Quantitative clinical pharmacology using mathematical modeling and simulation provides an excellent approach to overcome these challenges, as it can simultaneously integrate the disposition, PK, and PD of antibody-drug conjugates and their components in a quantitative manner. In this review, we highlight diverse quantitative clinical pharmacology approaches, ranging from system models (eg, physiologically based pharmacokinetic [PBPK] modeling) to mechanistic and empirical models (eg, population PK/PD modeling for single or multiple analytes, exposure-response modeling, platform modeling by pooling data across multiple antibody-drug conjugates). The impact of these PBPK and PK/PD models to provide insights into clinical dosing justification and inform drug development decisions is also highlighted.

show abstract

Section: Pbpk Modeling Of Antibody-drug Conjugatesmentioning

confidence: 99%

Impact of Physiologically Based Pharmacokinetics, Population Pharmacokinetics and Pharmacokinetics/Pharmacodynamics in the Development of Antibody‐Drug Conjugates

Li¹,

Chen²,

Chen³

et al. 2020

The Journal of Clinical Pharma

View full text Add to dashboard Cite

show abstract

“…While plausible, this simplified analysis fails to incorporate the full range of properties of affinity ligand and target (eg, binding affinity, kinetics, expression, and internalization), or the multitude of physiologic processes (eg, blood flow rates, organ volumes) relevant to biodistribution. Indeed, relatively few efforts have been made to develop mechanistic understanding of the PK of endothelial surface targeting, despite significant work done on modeling intracellular delivery [53][54][55] and transcytosis. 56 To our knowledge, the only example of a mechanistic model of cell surface anchoring has been in the case of bispecific T-cell engagers, 57,58 making the PBPK approach described here relatively unique.…”

Section: Discussionmentioning

confidence: 99%

Bivalent engagement of endothelial surface antigens is critical to prolonged surface targeting and protein delivery in vivo

et al. 2020

View full text Add to dashboard Cite

Targeted drug delivery to the endothelium has the potential to generate localized therapeutic effects at the blood‐tissue interface. For some therapeutic cargoes, it is essential to maintain contact with the bloodstream to exert protective effects. The pharmacokinetics (PK) of endothelial surface‐targeted affinity ligands and biotherapeutic cargo remain a largely unexplored area, despite obvious translational implications for this strategy. To bridge this gap, we site‐specifically radiolabeled mono‐ (scFv) and bivalent (mAb) affinity ligands specific for the endothelial cell adhesion molecules, PECAM‐1 (CD31) and ICAM‐1 (CD54). Radiotracing revealed similar lung biodistribution at 30 minutes post‐injection (79.3% ± 4.2% vs 80.4% ± 10.6% ID/g for αICAM and 58.9% ± 3.6% ID/g vs. 47.7% ± 5.8% ID/g for αPECAM mAb vs. scFv), but marked differences in organ residence time, with antibodies demonstrating an order of magnitude greater area under the lung concentration vs. time curve (AUCinf 1698 ± 352 vs. 53.3 ± 7.9 ID/g*hrs for αICAM and 1023 ± 507 vs. 114 ± 37 ID/g*hrs for αPECAM mAb vs scFv). A physiologically based pharmacokinetic model, fit to and validated using these data, indicated contributions from both superior binding characteristics and prolonged circulation time supporting multiple binding‐detachment cycles. We tested the ability of each affinity ligand to deliver a prototypical surface cargo, thrombomodulin (TM), using one‐to‐one protein conjugates. Bivalent mAb‐TM was superior to monovalent scFv‐TM in both pulmonary targeting and lung residence time (AUCinf 141 ± 3.2 vs 12.4 ± 4.2 ID/g*hrs for ICAM and 188 ± 90 vs 34.7 ± 19.9 ID/g*hrs for PECAM), despite having similar blood PK, indicating that binding strength is more important parameter than the kinetics of binding. To maximize bivalent target engagement, we synthesized an oriented, end‐to‐end anti‐ICAM mAb‐TM conjugate and found that this therapeutic had the best lung residence time (AUCinf 253 ± 18 ID/g*hrs) of all TM modalities. These observations have implications not only for the delivery of TM, but also potentially all therapeutics targeted to the endothelial surface.

show abstract

“…Other PK modeling approaches include semi-mechanistic PK models using a series of transit compartments to describe the deconjugation process from higher to lower DAR species, 10,22,23 multiscale mechanistic PK models in the cellular level, plasma and tissue 24 and physiologically based pharmacokinetic (PBPK) models. 25 The semi-mechanistic PK model developed by Sukumaran et al 10 incorporated the effects of DAR on drug deconjugation and antibody clearance processes. The structure of our mathematical model, which is adapted from Sukumaran's model, was developed based on the known mechanisms of deconjugation and observed impact of the DAR on the PK of ADCs in general.…”

Section: Discussionmentioning

confidence: 99%

Preclinical and translational pharmacokinetics of a novel THIOMAB™ antibody-antibiotic conjugate againstStaphylococcus aureus

Deng¹,

Zhou²,

Li³

et al. 2019

mAbs

View full text Add to dashboard Cite

DSTA4637S, a novel THIOMAB™ antibody-antibiotic conjugate (TAC) against Staphylococcus aureus (S. aureus), is currently being investigated as a potential therapy for complicated S. aureus bloodstream infections. DSTA4637S is composed of a monoclonal THIOMAB TM IgG1 recognizing S. aureus linked to a rifamycin-class antibiotic (dmDNA31) via a protease-cleavable linker. The pharmacokinetics (PK) of DSTA4637A (a liquid formulation of DSTA4637S) and its unconjugated antibody MSTA3852A were characterized in rats and monkeys. Systemic concentrations of three analytes, total antibody (TAb), antibody-conjugated dmDNA31 (ac-dmDNA31), and unconjugated dmDNA31, were measured to describe complex TAC PK in nonclinical studies. In rats and monkeys, following intravenous administration of a single dose of DSTA4637A, systemic concentration-time profiles of both TAb and ac-dmDNA31 were bi-exponential, characterized by a short distribution phase and a long elimination phase as expected for a monoclonal antibody-based therapeutic. Systemic exposures of both TAb and ac-dmDNA31 were dose proportional over the dose range tested, and ac-dmDNA31 cleared 2-3 times faster than TAb. Unconjugated dmDNA31 plasma concentrations were low (<4 ng/mL) in every study regardless of dose. In this report, an integrated semi-mechanistic PK model for two analytes (TAb and ac-dmDNA31) was successfully developed and was able to well describe the complicated DSTA4637A PK in mice, rats and monkeys. DSTA4637S human PK was predicted reasonably well using this model with allometric scaling of PK parameters from monkey data. This work provides insights into PK behaviors of DSTA4637A in preclinical species and informs clinical translatability of these observed results and further clinical development.

show abstract

Development of a Translational Physiologically Based Pharmacokinetic Model for Antibody-Drug Conjugates: a Case Study with T-DM1

Cited by 26 publications

References 34 publications

Impact of Physiologically Based Pharmacokinetics, Population Pharmacokinetics and Pharmacokinetics/Pharmacodynamics in the Development of Antibody‐Drug Conjugates

Impact of Physiologically Based Pharmacokinetics, Population Pharmacokinetics and Pharmacokinetics/Pharmacodynamics in the Development of Antibody‐Drug Conjugates

Bivalent engagement of endothelial surface antigens is critical to prolonged surface targeting and protein delivery in vivo

Preclinical and translational pharmacokinetics of a novel THIOMAB™ antibody-antibiotic conjugate againstStaphylococcus aureus

Contact Info

Product

Resources

About