ABSTRACT
AIMS: This study aims to develop a generalized pharmacokinetic (PK) model for monomethyl auristatin E (MMAE)-based antibody-drug conjugates (ADCs) that can simultaneously capture the PK of multiple ADC analytes commonly measured in the clinic. METHODS: A comprehensive literature review was conducted to collect PK data on MMAE-based ADCs from clinical trials. From each study, PK profiles of total antibody, the ADC, conjugated MMAE, and unconjugated MMAE, were extracted. These data were pooled and dose-normalized to evaluate the generalizability of PK across various ADCs and dose levels. Upon confirming PK generalizability, a generalized PK model for MMAE-based ADCs was developed using the entire dataset. Furthermore, exposure metrics ( C max and AUC) reported across the range of doses were combined to establish linear relationships between dose and exposure metrics for MMAE-based ADCs. RESULTS: A total of 109 PK profiles from 18 distinct MMAE-based ADCs were gathered. The dose-normalized PK profiles supported the generalizability of PK for MMAE-based ADCs. A generalized PK model was developed, which enabled capturing the PK data for 4 ADC analytes across all collected MMAE-based ADCs. A linear relationship between dose and PK exposure metrics was established, enabling the prediction of typical exposure values across different doses for MMAE-based ADCs. CONCLUSIONS: This study comprehensively analysed clinical PK data from different valine-citrulline (vc)-MMAE-based ADCs. The generalized PK model developed here serves as an important tool for a priori prediction of the PK for multiple ADC analytes in clinical settings and lays the foundation for establishing generalized exposure-response and exposure-toxicity correlations for MMAE-based ADCs.
Subject(s)
Dose-Response Relationship, Drug , Immunoconjugates , Models, Biological , Oligopeptides , Humans , Area Under Curve , Immunoconjugates/pharmacokinetics , Immunoconjugates/administration & dosage , Oligopeptides/pharmacokinetics , Oligopeptides/administration & dosageABSTRACT
We hypothesize that different routes of administration may lead to altered pharmacokinetics/pharmacodynamics (PK/PD) behavior of antibody-drug conjugates (ADCs) and may help to improve their therapeutic index. To evaluate this hypothesis, here we performed PK/PD evaluation for an ADC administered via subcutaneous (SC) and intratumoral (IT) routes. Trastuzumab-vc-MMAE was used as the model ADC, and NCI-N87 tumor-bearing xenografts were used as the animal model. The PK of multiple ADC analytes in plasma and tumors, and the in vivo efficacy of ADC, after IV, SC, and IT administration were evaluated. A semi-mechanistic PK/PD model was developed to characterize all the PK/PD data simultaneously. In addition, local toxicity of SC-administered ADC was investigated in immunocompetent and immunodeficient mice. Intratumoral administration was found to significantly increase tumor exposure and anti-tumor activity of ADC. The PK/PD model suggested that the IT route may provide the same efficacy as the IV route at an increased dosing interval and reduced dose level. SC administration of ADC led to local toxicity and reduced efficacy, suggesting difficulty in switching from IV to SC route for some ADCs. As such, this manuscript provides unprecedented insight into the PK/PD behavior of ADCs after IT and SC administration and paves the way for clinical evaluation of these routes.
ABSTRACT
PURPOSE: To quantitate and mathematically characterize the whole-body pharmacokinetics (PK) of different ADC analytes following administration of an MMAE-conjugated ADC in tumor-bearing mice. METHODS: The PK of different ADC analytes (total antibody, total drug, unconjugated drug) was measured following administration of an MMAE-conjugated ADC in tumor-bearing mice. The PK of ADC analytes was compared with the whole-body PK of the antibody and drug obtained following administration of these molecules alone. An ADC PBPK model was developed by linking antibody PBPK model with small-molecule PBPK model, where the drug was assumed to deconjugate in DAR-dependent manner. RESULTS: Comparison of antibody biodistribution coefficient (ABC) values for total antibody suggests that conjugation of drug did not significantly affect the PK of antibody. Comparison of tissue:plasma AUC ratio (T/P) for the conjugated drug and total antibody suggests that in certain tissues (e.g., spleen) ADC may demonstrate higher deconjugation. It was observed that the tissue distribution profile of the drug can be altered following its conjugation to antibody. For example, MMAE distribution to the liver was found to increase while its distribution to the heart was found to decrease upon conjugation to antibody. MMAE exposure in the tumor was found to increase by ~20-fold following administration as conjugate (i.e., ADC). The PBPK model was able to a priori predict the PK of all three ADC analytes in plasma, tissues, and tumor reasonably well. CONCLUSIONS: The ADC PBPK model developed here serves as a platform for translational and clinical investigations of MMAE containing ADCs.
Subject(s)
Immunoconjugates , Neoplasms , Animals , Cell Line, Tumor , Immunoconjugates/pharmacokinetics , Mice , Models, Biological , Oligopeptides/pharmacokinetics , Tissue DistributionABSTRACT
AIMS: In order to better predict the pharmacokinetics (PK) of antibodies in children, and to facilitate dose optimization of antibodies in paediatric patients, there is a need to develop systems PK models that integrate ontogeny-related changes in human physiological parameters. METHODS: A population-based physiological-based PK (PBPK) model to characterize antibody PK in paediatrics has been developed, by incorporating age-related changes in body weight, organ weight, organ blood flow rate and interstitial volumes in a previously published platform model. The model was further used to perform Monte Carlo simulations to investigate clearance vs. age and dose-exposure relationships for infliximab. RESULTS: By estimating only one parameter and associated interindividual variability, the model was able to characterize clinical PK of infliximab from two paediatric cohorts (n = 141, 4-19 years) reasonably well. Model simulations demonstrated that only 50% of children reached desired trough concentrations when receiving FDA-labelled dosing regimen for infliximab, suggesting that higher doses and/or more frequent dosing are needed to achieve target trough concentrations of this antibody. CONCLUSION: The paediatric PBPK model presented here can serve as a framework to characterize the PK of antibodies in paediatric patients. The model can also be applied to other protein therapeutics to advance precision medicine paradigm and optimize antibody dosing regimens in children.
Subject(s)
Models, Biological , Pediatrics , Child , Humans , Infliximab , Monte Carlo Method , Precision MedicineABSTRACT
Antibody drug-conjugates (ADCs) targeting human epidermal growth factor (HER2) are a rapidly expanding class of cancer therapeutics. Such ADCs are known to suffer from inefficient trafficking to the lysosome due to HER2 endosomal recycling, leaving most bound ADCs at the cell surface or in early endosomes. This study aims to increase the maximum cytotoxicity of ADC treatment by co-delivering a small molecule inhibitor targeting the primary chaperone of HER2, heat shock protein 90 (HSP90). We hypothesized that inhibiting HSP90 could aid ADC cytotoxicity by overcoming HER2 endosomal recycling. Flow cytometric studies tracking HER2 surface expression revealed â¼ 10 nM geldanamycin (GA) as the threshold for inhibiting HSP90 mediated HER2 recycling. Cytotoxicity studies in HER2 overexpressing cancer cell lines NCI-N87, MDA-MB-453, and SKOV3 demonstrated that co-administration of ADC alongside 100 nM GA significantly increased cytotoxicity compared to ADC alone. In all cases, baseline cytotoxicity was observed even in low HER2 expressing line MDA-MB-231 cells, indicating possible off-target effects. To mitigate this baseline cytotoxicity, a "pulse treatment" regime was adopted where cells are pre-loaded with T-DM1 or T-MMAE ADCs for 4 h, followed by a 4-hour pulse treatment with ADC and 100 nM GA to initiate trafficking of HER2 bound ADC to the lysosome. Afterwards, GA is removed, and ADC treatment is continued. GA pulse co-treatment decreased the amount of ADC required to achieve maximum cytotoxicity while minimizing baseline cytotoxicity. No such co-treatment regime featuring a pulse sequence has been explored before. Such co-treatments could offer a viable solution to increase ADC efficacy in hard to treat or resistant HER2-positive cancers.
Subject(s)
Immunoconjugates , Benzoquinones , Cell Line, Tumor , Humans , Lactams, Macrocyclic , Receptor, ErbB-2 , Trastuzumab , Xenograft Model Antitumor AssaysABSTRACT
The ocular pharmacokinetics (PK) of antibody-based therapies are infrequently studied in mice due to the technical difficulties in working with the small murine eye. This study is the first of its kind to quantitatively measure the PK of variously sized proteins in the plasma, cornea/ICB, vitreous humor, retina, and posterior cup (including choroid) of the mouse and to evaluate the relationship between molecular weight (MW) and antibody biodistribution coefficient (BC) to the eye. Proteins analyzed include trastuzumab (150 kDa), trastuzumab-vc-MMAE (T-vc-MMAE, 155 kDa), F(ab)2 (100 kDa), Fab (50 kDa), and scFv (27 kDa). As expected, ocular PK mirrored the systemic PK as plasma was the driving force for ocular exposure. For trastuzumab, T-vc-MMAE, F(ab)2, Fab, and scFv, respectively, the BCs in the cornea/ICB were 0.610%, 0.475%, 1.74%, 3.39%, and 13.7%; the BCs in the vitreous humor were 0.0198%, 0.0427%, 0.0934%, 0.234%, and 5.56%; the BCs for the retina were 0.539%, 0.230%, 0.704%, 2.44%, and 20.4%; the BCs for the posterior cup were 0.557%, 0.650%, 1.47%, 4.06%, and 13.9%. The relationship between BC and MW was best characterized by a log-log regression in which BC decreased as MW increased, with every doubling in MW leading to a decrease in BC by a factor of 3.44 × , 6.76 × , 4.74 × , and 3.43 × in cornea/ICB, vitreous humor, retina, and posterior cup, respectively. In analyzing the disposition of protein therapeutics to the eye, these findings enhance our understanding of the potential for ocular toxicity of systemically administered protein therapeutics and may aid in the discovery of systemically administered protein therapeutics for ocular disorders.
Subject(s)
Eye/metabolism , Immunoconjugates/pharmacokinetics , Immunoglobulin Fab Fragments/metabolism , Oligopeptides/pharmacokinetics , Trastuzumab/pharmacokinetics , Animals , Immunoconjugates/administration & dosage , Immunoconjugates/chemistry , Immunoglobulin Fab Fragments/administration & dosage , Immunoglobulin Fragments/administration & dosage , Immunoglobulin Fragments/metabolism , Mice , Mice, Inbred C57BL , Mice, Nude , Molecular Weight , Oligopeptides/administration & dosage , Oligopeptides/chemistry , Tissue Distribution , Trastuzumab/administration & dosage , Trastuzumab/chemistryABSTRACT
In the past, our lab proposed a two-pore PBPK model for different-size protein therapeutics using de novo derived parameters and the model was validated using plasma PK data of different-size antibody fragments digitized from the literature (Li Z, Shah DK, J Pharmacokinet Pharmacodynam 46(3):305-318, 2009). To further validate the model using tissue distribution data, whole-body biodistribution study of 6 different-size proteins in mice were conducted. Studied molecules covered a wide MW range (13-150 kDa). Plasma PK and tissue distribution profiles is 9 tissues were measured, including heart, lung, liver, spleen, kidney, skin, muscle, small intestine, large intestine. Tumor exposure of different-size proteins were also evaluated. The PBPK model was validated by comparing percentage predictive errors (%PE) between observed and model predicted results for each type of molecule in each tissue. Model validation showed that the two-pore PBPK model was able to predict plasma, tissues and tumor PK of all studied molecules relatively well. This model could serve as a platform for developing a generic PBPK model for protein therapeutics in the future.
Subject(s)
Tissue Distribution/physiology , Trastuzumab/pharmacokinetics , Animals , Antibodies, Monoclonal/pharmacokinetics , Cell Line, Tumor , Humans , Mice , Mice, Nude , Models, Biological , Neoplasms/metabolismABSTRACT
Quantitative modeling of the subcutaneous absorption processes of protein therapeutics is challenging. Here we have proposed a "two-pore" PBPK model that is able to simultaneously characterize plasma PK of different-size protein therapeutics in mice. The skin compartment is evolved to mechanistically account for the absorption pathways through lymph and blood capillaries, as well as local degradation at the SC injection site. The model is developed using in-house plasma PK data generated following subcutaneous administration of 6 different-size protein therapeutics (13-150 kDa) in mice. The model was able to capture plasma PK of all molecules following intravenous and subcutaneous administration relatively well. From the observed plasma PK profiles, as well as from the model simulation result, several important PK descriptors were found to be dependent on protein size for FcRn nonbinding molecules. A positive correlation was found between Tmax and protein size. A "U" shape relationship was found between Cmax and protein size. Negative correlations were observed between bioavailability (F) and local degradation rate (kdeg,SC), and F and protein size. Pathway analysis of the model was conducted for the subcutaneous absorption process, and continuous relationships were established between the percentage of absorption through lymphatic and vascular pathways and protein size. This PBPK model could serve as a platform for the development of different-size protein therapeutics and will be scaled up to humans for translational studies in the future.
Subject(s)
Antibodies, Monoclonal/pharmacokinetics , Immunoglobulin Fragments/pharmacology , Models, Biological , Neoplasms/drug therapy , Subcutaneous Tissue/metabolism , Administration, Intravenous , Animals , Antibodies, Monoclonal/administration & dosage , Antibodies, Monoclonal/chemistry , Biological Availability , Cell Line, Tumor , Computer Simulation , Humans , Immunoglobulin Fragments/chemistry , Immunoglobulin Fragments/therapeutic use , Injections, Subcutaneous , Mice , Molecular Weight , Neoplasms/pathology , Subcutaneous Absorption , Tissue Distribution , Xenograft Model Antitumor AssaysABSTRACT
Development of comprehensive and updated quantitative relationships between physiological parameters and age for pediatrics remains to be accomplished. Towards this goal, we have performed a thorough literature search and collected published data on organ weights and organ blood flow rates for 0-20-year-old male and female human subjects. The data were used to develop continuous relationships between physiological parameters and age, using a single form of mathematical equation. Four sets of equations (0-2 years male, 0-2 years female, 2-20 years male, 2-20 years female) for the body weight vs. age, height vs. age, and organ weight vs. age relationships and 2 sets of equations (0-20 years male, 0-20 years female) for organ flow rate vs. age relationship were developed. The variability of each physiological parameter was also estimated, and the equations allow simulation of a virtual population for a specific age, weight, and sex. We further compared the physiological parameters vs. age curves simulated using our equations to the existing databases (Simcyp Simulator and PK-Sim). The predicted physiological parameters were comparable between our study and the existing databases, validating our equation's utility. Additionally, we described body weight-normalized organ weights and organ blood flow rates as a function of age, to provide an insight into how the contribution of each organ towards total body weight and total blood flow changes throughout ontogenesis. The physiological parameter database and equations presented here can serve as an open source to facilitate the development of pediatric physiologically based pharmacokinetic models.
Subject(s)
Child Development/physiology , Models, Biological , Organ Size/physiology , Regional Blood Flow/physiology , Adolescent , Age Factors , Body Height , Body Weight , Child , Child, Preschool , Computer Simulation , Female , Humans , Infant , Infant, Newborn , Male , Sex Factors , Young AdultABSTRACT
Monomethyl auristatin E (MMAE) is one of the most commonly used payloads for developing antibody-drug conjugates (ADC). However, limited studies have comprehensively evaluated the whole-body disposition of MMAE. Consequently, here, we have investigated the whole-body pharmacokinetics (PK) of MMAE in tumor-bearing mice. We show that while MMAE is rapidly eliminated from the plasma, it shows prolonged and extensive distribution in tissues, blood cells, and tumor. Highly perfused tissues (e.g., lung, kidney, heart, liver, and spleen) demonstrated tissue-to-plasma area under the concentration curve (AUC) ratios > 20, and poorly perfused tissues (e.g., fat, pancreas, skin, bone, and muscle) had ratios from 1.3 to 2.4. MMAE distribution was limited in the brain, and tumor had 8-fold higher exposure than plasma. A physiological-based pharmacokinetic (PBPK) model was developed to characterize the whole-body PK of MMAE, which accounted for perfusion/permeability-limited transfer of drug in the tissue, blood cell distribution of the drug, tissue/tumor retention of the drug, and plasma protein binding. The model was able to characterize the PK of MMAE in plasma, tissues, and tumor simultaneously, and model parameters were estimated with good precision. The MMAE PBPK model presented here can facilitate the development of a platform PBPK model for MMAE containing ADCs and help with their preclinical-to-clinical translation and clinical dose optimization.
ABSTRACT
Here we have reported whole-body disposition of wild-type IgG and FcRn non-binding IgG in mice, determined using Enzyme-Linked Immunosorbent Assay (ELISA). The disposition data generated using ELISA are compared with previously published biodistribution data generated using radiolabelled IgG. In addition, we introduce a novel concept of ABCIS values, which are defined as percentage ratios of tissue interstitial and plasma AUC values. These values can help in predicting tissue interstitial concentrations of monoclonal antibodies (mAbs) based on the plasma concentrations. Tissue interstitial concentrations derived from our study are also compared with previously reported values measured using microdialysis or centrifugation method. Lastly, the new set of biodistribution data generated using ELISA are used to refine the PBPK model for mAbs.
Subject(s)
Antibodies, Monoclonal , Immunoglobulin G , Animals , Antibodies, Monoclonal/metabolism , Enzyme-Linked Immunosorbent Assay , Histocompatibility Antigens Class I/metabolism , Immunoglobulin G/metabolism , Mice , Receptors, Fc/metabolism , Tissue DistributionABSTRACT
Total antibody, conjugated antibody or antibody-conjugated drug, and free drug are key analytes required to establish exposure-response relationships for ADCs. Therefore, bioanalytical strategies for ADCs include ligand-binding assays (LBA) and LC-MS/MS methods. Here we describe detailed methodology to develop a solid-phase-based enzyme-linked immunosorbent assay (ELISA), which is the most widely used LBA to quantify large-molecule components of ADC in biological matrices such as plasma, serum, tumor, or tissue homogenates. The approach presented here is designed to quantify total antibody concentrations in ADC containing samples, and can be easily adapted to quantify conjugated antibody concentrations.
Subject(s)
Biological Assay , Drug Monitoring/methods , Immunoconjugates/chemistry , Immunoconjugates/pharmacokinetics , Biological Assay/methods , Enzyme-Linked Immunosorbent Assay , Humans , Ligands , Protein BindingABSTRACT
In this study, we evaluated the effect of size on tumor disposition of protein therapeutics, including the plasma and tumor pharmacokinetics (PK) of trastuzumab (â¼150 kDa), FcRn-nonbinding trastuzumab (â¼150 kDa), F(ab)2 fragment of trastuzumab (â¼100 kDa), Fab fragment of trastuzumab (â¼50 kDa), and trastuzumab scFv (â¼27 kDa) in both antigen (i.e., HER2)-overexpressing (N87) and antigen-nonexpressing (MDA-MB-468) tumor-bearing mice. The observed data were used to develop the maximum tumor uptake versus molecular weight and tumor-to-plasma area under the curve (AUC) ratio versus molecular weight relationships. Comparison of the PK of different sizes of FcRn nonbinding molecules in target-expressing tumor showed that â¼100 kDa is an optimal size to achieve maximum tumor uptake and â¼50 kDa is an optimal size to achieve maximum tumor-to-plasma exposure ratio of protein therapeutics. The PK data were also used to validate a systems PK model for tumor disposition of different-sized protein therapeutics. The PK model was able to predict a priori the PK of all five molecules in both tumor types reasonably well (within 2- to 3-fold). In addition, the model captured the bell-shaped relationships observed between maximum tumor uptake and molecular weight and between tumor-to-plasma AUC ratio and molecular weight. Our results provide an unprecedented insight into the effect of size and target engagement on the tumor PK of protein therapeutics. Our results also provide further validation of the tumor disposition model, which can be used to support discovery, development, and preclinical-to-clinical translation of different sizes of protein therapeutics. SIGNIFICANCE STATEMENT: This article highlights the importance of molecular size and target engagement on the tumor disposition of protein therapeutics. Our results suggest that â¼100 kDa is an optimal size to achieve maximum tumor uptake and â¼50 kDa is an optimal size to achieve maximum tumor-to-plasma exposure ratio for non-FcRn-binding targeted protein therapeutics. We also demonstrate that a systems pharmacokinetics model developed to characterize tumor disposition of protein therapeutics can predict a priori the disposition of different-sized protein therapeutics in target-expressing and target-nonexpressing solid tumors.