Towards a platform quantitative systems pharmacology (QSP) model for preclinical to clinical translation of antibody drug conjugates (ADCs).

A next generation multiscale quantitative systems pharmacology (QSP) model for antibody drug conjugates (ADCs) is presented, for preclinical to clinical translation of ADC efficacy. Two HER2 ADCs (trastuzumab-DM1 and trastuzumab-DXd) were used for model development, calibration, and validation. The model integrates drug specific experimental data including in vitro cellular disposition data, pharmacokinetic (PK) and tumor growth inhibition (TGI) data for T-DM1 and T-DXd, as well as system specific data such as properties of HER2, tumor growth rates, and volumes. The model incorporates mechanistic detail at the intracellular level, to account for different mechanisms of ADC processing and payload release. It describes the disposition of the ADC, antibody, and payload inside and outside of the tumor, including binding to off-tumor, on-target sinks. The resulting multiscale PK model predicts plasma and tumor concentrations of ADC and payload. Tumor payload concentrations predicted by the model were linked to a TGI model and used to describe responses following ADC administration to xenograft mice. The model was translated to humans and virtual clinical trial simulations were performed that successfully predicted progression free survival response for T-DM1 and T-DXd for the treatment of HER2+ metastatic breast cancer, including differential efficacy based upon HER2 expression status. In conclusion, the presented model is a step toward a platform QSP model and strategy for ADCs, integrating multiple types of data and knowledge to predict ADC efficacy. The model has potential application to facilitate ADC design, lead candidate selection, and clinical dosing schedule optimization.

A next generation mathematical model for the in vitro to clinical translation of T-cell engagers.

T-cell engager (TCE) molecules activate the immune system and direct it to kill tumor cells. The key mechanism of action of TCEs is to crosslink CD3 on T cells and tumor associated antigens (TAAs) on tumor cells. The formation of this trimolecular complex (i.e. trimer) mimics the immune synapse, leading to therapeutic-dependent T-cell activation and killing of tumor cells. Computational models supporting TCE development must predict trimer formation accurately. Here, we present a next-generation two-step binding mathematical model for TCEs to describe trimer formation. Specifically, we propose to model the second binding step with trans-avidity and as a two-dimensional (2D) process where the reactants are modeled as the cell-surface density. Compared to the 3D binding model where the reactants are described in terms of concentration, the 2D model predicts less sensitivity of trimer formation to varying cell densities, which better matches changes in EC50 from in vitro cytotoxicity assay data with varying E:T ratios. In addition, when translating in vitro cytotoxicity data to predict in vivo active clinical dose for blinatumomab, the choice of model leads to a notable difference in dose prediction. The dose predicted by the 2D model aligns better with the approved clinical dose and the prediction is robust under variations in the in vitro to in vivo translation assumptions. In conclusion, the 2D model with trans-avidity to describe trimer formation is an improved approach for TCEs and is likely to produce more accurate predictions to support TCE development.

Use of translational modeling and simulation for quantitative comparison of PF-06804103, a new generation HER2 ADC, with Trastuzumab-DM1.

A modeling and simulation approach was used for quantitative comparison of a new generation HER2 antibody drug conjugate (ADC, PF-06804103) with trastuzumab-DM1 (T-DM1). To compare preclinical efficacy, the pharmacokinetic (PK)/pharmacodynamic (PD) relationship of PF-06804103 and T-DM1 was determined across a range of mouse tumor xenograft models, using a tumor growth inhibition model. The tumor static concentration was assigned as the minimal efficacious concentration. PF-06804103 was concluded to be more potent than T-DM1 across cell lines studied. TSCs ranged from 1.0 to 9.8 µg/mL (n = 7) for PF-06804103 and from 4.7 to 29 µg/mL (n = 5) for T-DM1. Two experimental models which were resistant to T-DM1, responded to PF-06804103 treatment. A mechanism-based target mediated drug disposition (TMDD) model was used to predict the human PK of PF-06804103. This model was constructed and validated based on T-DM1 which has non-linear PK at doses administered in the clinic, driven by binding to shed HER2. Non-linear PK is predicted for PF-06804103 in the clinic and is dependent upon circulating HER2 extracellular domain (ECD) concentrations. The models were translated to human and suggested greater efficacy for PF-06804103 compared to T-DM1. In conclusion, a fit-for-purpose translational PK/PD strategy for ADCs is presented and used to compare a new generation HER2 ADC with T-DM1.

Establishing in vitro-in vivo correlation for antibody drug conjugate efficacy: a PK/PD modeling approach.

The objective of this manuscript was to establish in vitro-in vivo correlation (IVIVC) between the in vitro efficacy and in vivo efficacy of antibody drug conjugates (ADCs), using a PK/PD modeling approach. Nineteen different ADCs were used to develop IVIVC. In vitro efficacy of ADCs was evaluated using a kinetic cell cytotoxicity assay. The cytotoxicity data obtained from in vitro studies was characterized using a novel mathematical model, parameter estimates from which were used to derive an in vitro efficacy matrix for each ADC, termed as 'in vitro tumor static concentration' (TSCin vitro). TSCin vitro is a theoretical concentration at continuous exposure of which the number of cells will neither increase nor decrease, compared to the initial cell number in the experiment. The in vivo efficacy of ADCs was evaluated using tumor growth inhibition (TGI) studies performed on human tumor xenograft bearing mice. The TGI data obtained from in vivo studies was characterized using a PK/PD model, parameter estimates from which were used to derive an in vivo efficacy matrix for each ADC, termed as 'in vivo tumor static concentration' (TSCin vivo). TSCin vivo is a theoretical concentration if one were to maintain in the plasma of a tumor bearing mouse, the tumor volume will neither increase nor decrease compared to the initial tumor volume. Comparison of the TSCin vitro and TSCin vivo values from 19 ADCs provided a linear and positive IVIVC. The Spearman's rank correlation coefficient for TSCin vitro and TSCin vivo was found to be 0.82. On average TSCin vivo was found to be ~ 27 times higher than TSCin vitro. The reasonable IVIVC for ADCs suggests that in vitro efficacy data was correctly able to differentiate ADCs for their in vivo efficacy. Thus, IVIVC can be used as a tool to triage ADC molecules in the discovery stage, thereby preventing unnecessary scaling-up of ADCs and waste of time and resources. An ability to predict the concentration of ADC that is efficacious in vivo using the in vitro data can also help in optimizing the experimental design of preclinical efficacy studies. As such, the novel PK/PD modeling method presented here to establish IVIVC for ADCs holds promise, and should be evaluated further using diverse set of cell lines and anticancer agents.

On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach.

Objectives of the present investigation were: (1) to compare three literature reported tumor growth inhibition (TGI) pharmacodynamic (PD) models and propose an optimal new model that best describes the xenograft TGI data for antibody drug conjugates (ADC), (2) to translate efficacy of the ADC Trastuzumab-emtansine (T-DM1) from mice to patients using the optimized PD model, and (3) to apply the translational strategy to predict clinically efficacious concentrations of a novel in-house anti-5T4 ADC, A1mcMMAF. First, the performance of all four of the PD models (i.e. 3 literature reported + 1 proposed) was evaluated using TGI data of T-DM1 obtained from four different xenografts. Based on the estimates of the pharmacodynamic/pharmacokinetic (PK/PD) modeling, a secondary parameter representing the efficacy index of the drug was calculated, which is termed as the tumor static concentration (TSC). TSC values derived from all four of the models were compared with each other, and with literature reported values, to assess the performance of these models. Subsequently, using the optimized PK/PD model, PD parameters obtained from different cell lines, human PK, and the proposed translational strategy, clinically efficacious doses of T-DM1 were projected. The accuracy of projected efficacious dose range for T-DM1 was verified by comparison with the clinical doses. Aforementioned strategy was then applied to A1mcMMAF for projecting its efficacious concentrations in clinic. TSC values for A1mcMMAF, obtained by fitting TGI data from 4 different xenografts with the proposed PK/PD model, were estimated to range from 0.6 to 11.5 µg mL⁻¹. Accordingly, the clinically efficacious doses for A1mcMMAF were projected retrospectively. All in all, the improved PD model and proposed translational strategy presented here suggest that appropriate correction for the clinical exposure and employing the TSC criterion can help translate mouse TGI data to predict first in human doses of ADCs.

Therapeutic index improvement of antibody-drug conjugates.

The commentary by Colombo and Rich recently published in Cancer Cell provides a timely and comprehensive review of the clinical maximum tolerated doses (MTDs) of antibody-drug conjugates (ADCs) and their corresponding small molecules/chemotherapies. The authors identified similarities between their MTDs and therefore question the historic assumptions made for ADCs, namely, that they increase the MTDs of their corresponding cytotoxic molecules. However, the authors did not address the superior anti-tumor responses of ADCs compared to their corresponding chemotherapies, as reported in clinical trials. In this point of view, we propose a revised model wherein the anti-tumor activities of ADCs and consequently their therapeutic indexes (TIs) are not solely associated with changes not only in their MTDs but also in their minimal effective doses (MEDs). In addition, when using an exposure-based TI calculation method, the superior anti-tumor activities of ADCs relative to their corresponding chemotherapy can readily be explained. We discussed the clinical and preclinical data in support of lower MEDs of ADCs and generated a revised graph illustrating the TI improvements of ADCs vs chemotherapy more accurately. We believe that our revised model can provide a blueprint for future improvements in protein engineering and chemical engineering of toxins to further advance ADC research and development.

Bench to bedside translation of antibody drug conjugates using a multiscale mechanistic PK/PD model: a case study with brentuximab-vedotin.

To build a multiscale mechanism based pharmacokinetic-pharmacodynamic (PK/PD) model for antibody drug conjugates (ADCs), using brentuximab-vedotin as an example, for preclinical to clinical translation of ADC efficacy. Brentuximab-vedotin experimental data, collected from diverse publications, were employed in the following steps to build and validate the model: (1) characterization of ADC and payload PK at the cellular level, (2) characterization of payload PK in plasma and tumor tissue of xenograft mouse, (3) characterization of ADC PK in mouse plasma, (4) prediction of the tumor payload concentrations in xenograft mouse by integrating parameters obtained from steps 1-3 with the novel tumor disposition model for ADC, (5) characterization of preclinical brentuximab-vedotin tumor growth inhibition data using the novel PK/PD model, (6) characterization of ADC and payload PK in cancer patients, and (7) prediction of clinical responses of brentuximab-vedotin using the PK/PD model, by integrating PK parameters obtained from step 6, and translated mouse parameters from step 5; and comparing them with clinical trial results. The tumor disposition model was able to accurately predict xenograft tumor and plasma payload concentrations. PK/PD model predicted progression free survival rates and complete response rates for brentuximab-vedotin in patients were comparable to the observed clinical results. It is essential to understand and characterize the disposition of ADC and payload, at the cellular and physiological level, to predict the clinical outcome of ADC. A first of its kind mechanistic model has been developed for ADCs, which can integrate preclinical biomeasures and PK/PD data, to predict clinical response.

Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human.

The objectives of the following investigation were (1) development of a physiologically based pharmacokinetic (PBPK) model capable of characterizing the plasma and tissue pharmacokinetics (PK) of nonspecific or antigen specific monoclonal antibodies (mAbs) in wild type, FcRn knockout, tumor bearing and non tumor bearing mice and (2) evaluation of the scale up potential of the model by characterizing the mouse, rat, monkey and human plasma PK of mAbs, simultaneously. A PBPK model containing 15 tissues, a carcass and a tumor compartment was developed by modifying/augmenting previously published PBPK models. Each tissue compartment was subdivided into plasma, blood cell, endothelial, interstitial and cellular sub-compartments. Each tissue was connected through blood and lymph flow to the systemic circulation. Lymph flow was set to a value 500 times lower than plasma flow and vascular reflection coefficients for each tissue were adjusted according to their vascular pore size. In each tissue endothelial space, mAb entered via pinocytosis and the interaction of FcRn with mAb was described by on and off rates. FcRn bound mAb was recycled and unbound mAb was eliminated by a first order process (K(deg)). The PBPK model was simultaneously fit to the following datasets to estimate four system parameters: (1) plasma and tissue PK of nonspecific mAb in wild type mouse with or without simultaneous intravenous immunoglobulin (IVIG) administration, (2) plasma and tissue PK of nonspecific mAb in FcRn knockout mouse, (3) plasma and tissue PK of nonspecific mAb in tumor bearing mouse, (4) plasma and tissue PK of tumor antigen specific mAb in tumor bearing mouse, and (5) plasma PK of mAb in rat, monkey and human. The model was able to characterize all the datasets reasonably well with a common set of parameters. The estimated value of the four system parameters i.e. FcRn concentration (FcRn), rate of pinocytosis per unit endosomal space (CL(up)), K(deg) and the proportionality constant (C_LNLF) between the rate at which antibody transfers from the lymph node compartment to the blood compartment and the plasma flow of the given species, were found to be 4.98E-05 M (CV% = 11.1), 3.66E-02 l/h/l (%CV = 3.48), 42.9 1/h (%CV = 15.7) and 9.1 (CV% > 50). Thus, a platform PBPK model has been developed that can not only simultaneously characterize mAb disposition data obtained from various previously published mouse PBPK models but is also capable of characterizing mAb disposition in various preclinical species and human.

Palaeoenvironmental proxies indicate long-term development of agro-pastoralist landscapes in Inner Asian mountains.

A growing body of archaeological research on agro-pastoralist populations of the Inner Asian mountains indicates that these groups adapted various systems of mobile herding and cultivation to ecotopes across the region from as early as 5000 BP. It has been argued that these adaptations allowed the development of flexible social-ecological systems well suited to the long-term management of these mountain landscapes. At present, less attention has been paid to examining the long-term ecological legacy of these adaptations within the sedimentary or palaeoenvironmental record. Here we present sediment, palynomorph and charcoal data that we interpret as indicating agro-pastoralist environmental perturbations, taken from three cores at middle and high altitudes in the Kashmir Valley at the southern end of the Inner Asian mountains. Our data indicate spatially and temporally discontinuous patterns of agro-pastoralist land use beginning close to 4000 BP. Periods of intensification of upland herding are often coincident with phases of regional social or environmental change, in particular we find the strongest signals for agro-pastoralism in the environmental record contemporary with regionally arid conditions. These patterns support previous arguments that specialised agro-pastoralist ecologies across the region are well placed to respond to past and future climate deteriorations. Our data indicating long-term co-evolution of humans and landscape in the study area also have implications for the ongoing management of environments generally perceived as "pristine" or "wilderness".

Quantitative systems pharmacology modeling provides insight into inter-mouse variability of Anti-CTLA4 response.

Clinical responses of immuno-oncology therapies are highly variable among patients. Similar response variability has been observed in syngeneic mouse models. Understanding of the variability in the mouse models may shed light on patient variability. Using a murine anti-CTLA4 antibody as a case study, we developed a quantitative systems pharmacology model to capture the molecular interactions of the antibody and relevant cellular interactions that lead to tumor cell killing. Nonlinear mixed effect modeling was incorporated to capture the inter-animal variability of tumor growth profiles in response to anti-CTLA4 treatment. The results suggested that intratumoral CD8+ T cell kinetics and tumor proliferation rate were the main drivers of the variability. In addition, simulations indicated that nonresponsive mice to anti-CTLA4 treatment could be converted to responders by increasing the number of intratumoral CD8+ T cells. The model provides a mechanistic starting point for translation of CTLA4 inhibitors from syngeneic mice to the clinic.

New evidence for supplementary crop production, foddering and fuel use by Bronze Age transhumant pastoralists in the Tianshan Mountains.

The nature of economies and the movement of agricultural crops across Eurasia in the Bronze Age have been the subject of significant research interest in recent years. This study presents and discusses new results of flotation, radiocarbon and carbon stable isotope analyses from the seed assemblage at the Adunqiaolu site (northwestern Xinjiang), in combination with archaeological evidence. Archaeobotanical evidence, including carbonized foxtail millet, broomcorn millet, and naked barley, documents the diversity of local cereal consumption during the mid-second millennium BC. Our results suggest that crops were not grown locally, however, but in the lower Boertala Valley, supporting the argument that Adunqiaolu was a winter camp. These new sets of data constitute an important contribution to the discussion on cereal dispersal across the Tianshan Mountains in the Bronze Age.

Quantitative modeling predicts competitive advantages of a next generation anti-NKG2A monoclonal antibody over monalizumab for the treatment of cancer.

A semimechanistic pharmacokinetic (PK)/receptor occupancy (RO) model was constructed to differentiate a next generation anti-NKG2A monoclonal antibody (KSQ mAb) from monalizumab, an immune checkpoint inhibitor in multiple clinical trials for the treatment of solid tumors. A three-compartment model incorporating drug PK, biodistribution, and NKG2A receptor interactions was parameterized using monalizumab PK, in vitro affinity measurements for both monalizumab and KSQ mAb, and receptor burden estimates from the literature. Following calibration against monalizumab PK data in patients with rheumatoid arthritis, the model successfully predicted the published PK and RO observed in gynecological tumors and in patients with squamous cell carcinoma of the head and neck. Simulations predicted that the KSQ mAb requires a 10-fold lower dose than monalizumab to achieve a similar RO over a 3-week period following q3w intravenous (i.v.) infusion dosing. A global sensitivity analysis of the model indicated that the drug-target binding affinity greatly affects the tumor RO and that an optimal affinity is needed to balance RO with enhanced drug clearance due to target mediated drug disposition. The model predicted that the KSQ mAb can be dosed over a less frequent regimen or at lower dose levels than the current monalizumab clinical dosing regimen of 10 mg/kg q2w. Either dosing strategy represents a competitive advantage over the current therapy. The results of this study demonstrate a key role for mechanistic modeling in identifying optimal drug parameters to inform and accelerate progression of mAb to clinical trials.

Discovery and optimization of a novel anti-GUCY2c x CD3 bispecific antibody for the treatment of solid tumors.

We report here the discovery and optimization of a novel T cell retargeting anti-GUCY2C x anti-CD3ε bispecific antibody for the treatment of solid tumors. Using a combination of hybridoma, phage display and rational design protein engineering, we have developed a fully humanized and manufacturable CD3 bispecific antibody that demonstrates favorable pharmacokinetic properties and potent in vivo efficacy. Anti-GUCY2C and anti-CD3ε antibodies derived from mouse hybridomas were first humanized into well-behaved human variable region frameworks with full retention of binding and T-cell mediated cytotoxic activity. To address potential manufacturability concerns, multiple approaches were taken in parallel to optimize and de-risk the two antibody variable regions. These approaches included structure-guided rational mutagenesis and phage display-based optimization, focusing on improving stability, reducing polyreactivity and self-association potential, removing chemical liabilities and proteolytic cleavage sites, and de-risking immunogenicity. Employing rapid library construction methods as well as automated phage display and high-throughput protein production workflows enabled efficient generation of an optimized bispecific antibody with desirable manufacturability properties, high stability, and low nonspecific binding. Proteolytic cleavage and deamidation in complementarity-determining regions were also successfully addressed. Collectively, these improvements translated to a molecule with potent single-agent in vivo efficacy in a tumor cell line adoptive transfer model and a cynomolgus monkey pharmacokinetic profile (half-life>4.5 days) suitable for clinical development. Clinical evaluation of PF-07062119 is ongoing.

The application of target information and preclinical pharmacokinetic/pharmacodynamic modeling in predicting clinical doses of a Dickkopf-1 antibody for osteoporosis.

PF-04840082 is a humanized prototype anti-Dickkopf-1 (Dkk-1) immunoglobulin isotype G(2) (IgG(2)) antibody for the treatment of osteoporosis. In vitro, PF-04840082 binds to human, monkey, rat, and mouse Dkk-1 with high affinity. After administration of PF-04840082 to rat and monkey, free Dkk-1 concentrations decreased rapidly and returned to baseline in a dose-dependent manner. In rat and monkey, PF-04840082 exhibited nonlinear pharmacokinetics (PK) and a target-mediated drug disposition (TMDD) model was used to characterize PF-04840082 versus Dkk-1 concentration response relationship. PK/pharmacodynamic (PK/PD) modeling enabled estimation of antibody non-target-mediated elimination, Dkk-1 turnover, complex formation, and complex elimination. The TMDD model was translated to human to predict efficacious dose and minimum anticipated biological effect level (MABEL) by incorporating information on typical IgG(2) human PK, antibody-target association/dissociation rates, Dkk-1 expression, and turnover rates. The PK/PD approach to MABEL was compared with the standard "no adverse effect level" (NOAEL) approach to calculating clinical starting doses and a pharmacological equilibrium method. The NOAEL method gave estimates of dose that were too high to ensure safety of clinical trials. The pharmacological equilibrium approach calculated receptor occupancy (RO) based on equilibrium dissociation constant alone and did not take into account rate of turnover of the target or antibody-target complex kinetics and, as a result, it likely produced a substantial overprediction of RO at a given dose. It was concluded that the calculation of MABEL according to the TMDD model was the most appropriate means for ensuring safety and efficacy in clinical studies.

Pharmacokinetics and elucidation of the rates and routes of N-glucuronidation of PF-592379, an oral dopamine 3 agonist in rat, dog, and human.

PF-592379 is a potent, selective agonist of the dopamine 3 receptor, for the treatment of male erectile dysfunction and female sexual dysfunction. In vivo, PF-592379 has low-moderate clearance relative to liver blood flow of 6.3 and 8.5 ml/min/kg in dog and 44.8 and 58.2 ml/min/kg in rat. It has high permeability in Caco-2 cells and was completely absorbed in rat and dog pharmacokinetic studies with an oral bioavailability of 28% in both rats and 61 and 87% in the dogs. These data are consistent with the physicochemical properties of PF-592379, which indicate complete absorption by the transcellular route. Elimination of PF-592379 was predominantly metabolic in nature. In vitro routes of metabolism studies indicate that metabolism in the rat is a combination of P450 mechanisms and N-glucuronidation, whereas in dog and human, N-glucuronidation is the major route. NMR analysis indicates that N-glucuronidation is non-quaternary in nature and occurs on both the pyridyl amine and ring nitrogen. Rates of clearance via N-glucuronidation were predicted to be low in humans compared with acyl or phenolic glucuronidation. PF-592379 was predicted to have complete absorption from the gastrointestinal tract and an oral bioavailability of >60% in the clinic. Clinical data verified that PF-592379 is a low clearance compound in human, with a mean oral clearance of 6.5 ml/min/kg following a 200 mg oral dose. PF-592379 has ideal pharmacokinetic properties for an oral D3 agonist, intended for on demand dosing.

Mechanistic Quantitative Pharmacology Strategies for the Early Clinical Development of Bispecific Antibodies in Oncology.

Bispecific antibodies (bsAbs) have become an integral component of the therapeutic research strategy to treat cancer. In addition to clinically validated immune cell re-targeting, bsAbs are being designed for tumor targeting and as dual immune modulators. Explorative preclinical and emerging clinical data indicate potential for enhanced efficacy and reduced systemic toxicity. However, bsAbs are a complex modality with challenges to overcome in early clinical trials, including selection of relevant starting doses using a minimal anticipated biological effect level approach, and predicting efficacious dose despite nonintuitive dose response relationships. Multiple factors can contribute to variability in the clinic, including differences in functional affinity due to avidity, receptor expression, effector to target cell ratio, and presence of soluble target. Mechanistic modeling approaches are a powerful integrative tool to understand the complexities and aid in clinical translation, trial design, and prediction of regimens and strategies to reduce dose limiting toxicities of bsAbs. In this tutorial, the use of mechanistic modeling to impact decision making for bsAbs is presented and illustrated using case study examples.

Seasonal movements of Bronze Age transhumant pastoralists in western Xinjiang.

The paper explores seasonal movements of Bronze Age mobile pastoralists in the western Tianshan mountainous region of Xinjiang, China. Fieldwork by a team from the Institute of Archaeology of the Chinese Academy of Social Science (CASS) and the University of Sydney, Australia have identified cyclical land use practices associated with the Andronovo cultural complex. Their pattern of seasonal movements has been reconstructed through ethnographic studies and analysis of modern snow and grass cover. Using this detailed combination of data, the study defines requirements for seasonal pastures-winter, summer and spring/autumn-and shows a clear correlation between modern land use and seasonal patterns of movement in the Bronze Age.

In vitro and in vivo SAR of pyrido[3,4-d]pyramid-4-ylamine based mGluR1 antagonists.

The SAR of a series of novel pyrido[3,4-d]pyramid-4-ylamine mGluR1 antagonists is described. The multiple of the unbound K(i) in cerebrospinal fluid necessary to give morphine like analgesic effects in an electromyograph pinch model in rodents is determined and the effect of structure on CNS penetration examined.

A Physiologically-Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics From In Vitro Data.

Monoclonal antibody (mAb) pharmacokinetics (PK) have largely been predicted via allometric scaling with little consideration for cross-species differences in neonatal Fc receptor (FcRn) affinity or clearance/distribution mechanisms. To address this, we developed a mAb physiologically-based PK model that describes the intracellular trafficking and FcRn recycling of mAbs in a human FcRn transgenic homozygous mouse and human. This model uses mAb-specific in vitro data together with species-specific FcRn tissue expression, tissue volume, and blood-flow physiology to predict mAb in vivo linear PK a priori. The model accurately predicts the terminal half-life of 90% of the mAbs investigated within a twofold error. The mechanistic nature of this model allows us to not only predict linear PK from in vitro data but also explore the PK and target binding of mAbs engineered to have pH-dependent binding to its target or FcRn and could aid in the selection of mAbs with optimal PK and pharmacodynamic properties.

Correction to: A Translational Quantitative Systems Pharmacology Model for CD3 Bispecific Molecules: Application to Quantify T Cell-Mediated Tumor Cell Killing by P-Cadherin LP DART®.

Typesetting error occurred and Figure 1a and Figure 1b were altered during the uploading process. The original article has been corrected.