An<i>in vitro</i>FcRn- dependent transcytosis assay as a screening tool for predictive assessment of nonspecific clearance of antibody therapeutics in humans

Chung, Shan; Nguyen, Van Hanh; Lin, Yuwen Linda; Lafrance‐Vanasse, Julien; Scales, Suzie J.; Lin, Kevin K.; Deng, Rong; Williams, Kathi; Sperinde, Gizette; Li, Juan Jenny; Zheng, Kai; Sukumaran, Siddharth; Tesar, Devin; Ernst, James A.; Fischer, Saloumeh K; Lazar, Greg A.; Prabhu, Saileta; Song, An

doi:10.1080/19420862.2019.1605270

Cited by 47 publications

(49 citation statements)

References 61 publications

(92 reference statements)

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“…However, despite these literature reports, the use of PBPK modeling for mAbs in the pharmaceutical industry is still limited. Most PBPK models published have relied on in vivo data for fitting as there have been few predictive in vitro assays described and few in vitro – in vivo relationships established . Although these models can fit the experimental data, the models are heterogeneous, and different groups have used not only different physiological parameters but also different representations of physiology to fit the data .…”

Section: Discussionmentioning

confidence: 99%

“…The in vitro – in vivo correlations of PK properties are therefore less well established. However, several physicochemical attributes, e.g., non‐specific charge‐based interactions, self‐association, and hFcRn binding affinity, have recently been shown to correlate with in vivo clearance (CL) . One particular in vitro assay is the affinity‐capture self‐interaction nanoparticle spectroscopy (AC‐SINS) assay .…”

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confidence: 99%

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A Physiologically‐Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics FromIn VitroData

Jones

Zhang

Jasper

et al. 2019

CPT Pharmacom & Syst Pharma

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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. www.psp-journal.com PBPK Model for Monoclonal Antibody PK Prediction Jones et al. www.psp-journal.com PBPK Model for Monoclonal Antibody PK Prediction Jones et al.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

A Physiologically‐Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics FromIn VitroData

Jones

Zhang

Jasper

et al. 2019

CPT Pharmacom & Syst Pharma

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“…Previous work in this area has suggested that self-interactions and nonspecific interactions in phosphate-buffered saline or similar buffers may be important (27,28). Recently, assays based on cellular trafficking processes, facilitated by specific binding and transcytosis through the FcRn receptor, have been shown to be important in determining mAb PK (29). With respect to molecular attributes, PK modeling (30) and specific engineering of IgGs at the FcRn binding interface, between the C H 2 and C H 3 domains, have yielded definitive evidence of half-life extension or reduced clearance of mAbs in preclinical settings (31,32).…”

Section: No Pk Disadvantage For Selecting Mabs That Display Favorablementioning

confidence: 99%

“…The best-fit parameters were used to interpolate the viscosity at 150 mg/ml. In 11 cases (mAbs 6,11,13,14,22,24,28,29,41,53, and 57), the sample quantities available did not permit generation of the concentrationviscosity data. Instead, a single viscosity measurement was conducted on the sample at a target concentration of 150 mg/ml.…”

Section: Viscosity Measurementmentioning

confidence: 99%

A single molecular descriptor to predict solution behavior of therapeutic antibodies

Kingsbury¹,

Saini²,

Auclair³

et al. 2020

Sci. Adv.

103

168

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Despite the therapeutic success of monoclonal antibodies (mAbs), early identification of developable mAb-drug candidates with optimal manufacturability, stability, and delivery attributes remains elusive. Poor solution behavior, which manifests as high solution viscosity or opalescence, profoundly affects the developability of mAb-drugs. Employing a diverse dataset of 59 mAbs, including 43 approved products, and an array of molecular descriptors spanning colloidal, conformational, charge-based, hydrodynamic, and hydrophobic properties, we show that poor solution behavior is prevalent (>30%) in mAbs and is singularly predicted (>90%) by the diffusion interaction parameter (kD), a dilute-solution measure of colloidal self-interaction. No other descriptor, individually or in combination, was found to be as effective as kD. We also show that well-behaved mAbs, a significant subset of which bear high positive charge and pI, present no disadvantages with respect to pharmacokinetics in humans. Here, we provide a systematic framework with quantitative thresholds for selecting well-behaved therapeutic mAbs during drug-discovery.

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“…A wide variety of in vitro assays have been used to evaluate nonspecific binding and antibody uptake, but none of these assays are able to quantitatively predict PK profiles 6 – 8 . In addition, cell-based assays such as FcRn-mediated transcytosis assays have been developed to predict the half-life of an antibody, but they can only be used to rank candidate antibodies by half-life 9 – 12 . For these reasons, an in vivo-based approach would be the most efficient strategy for evaluating the PK of an antibody not cleared by target-dependent elimination in animals and predicting it in humans.…”

Section: Introductionmentioning

confidence: 99%

Pharmacokinetic prediction of an antibody in mice based on an in vitro cell-based approach using target receptor-expressing cells

Noguchi¹,

Ozeki²,

Akita

2020

Sci Rep

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In vivo pharmacokinetics (PK) studies using mice and monkeys are the main approaches for evaluating and predicting the PK of antibodies, and there is a strong demand for methods that do not require animal experiments. In this work, we focused on quantitatively predicting the nonlinear PK of an antibody based on cell-based assays. An anti-mouse Fc gamma receptor IIB antibody was used as a model antibody. To determine the PK parameters related to nonspecific elimination in vivo, the plasma concentration profile at 100 mg/kg, at which target-specific clearance is saturated, was analyzed by a 2-compartment model. To estimate the parameters related to target-specific elimination, the Michaelis–Menten constant (Km) and the maximum elimination rate (Vmax) were determined by an uptake assay using Chinese hamster ovary (CHO) cells expressing the target receptor. Finally, the integration of all of these parameters permitted the PK to be predicted at doses ranging from 1 to 100 mg/kg regardless of whether target-specific clearance was saturated or nonsaturated. The findings presented herein show that in vitro assays using target-expressing cells are useful tools for obtaining PK parameters and predicting PK profiles and, in some cases, eliminate the need for in vivo PK studies using experimental animals.

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Anin vitroFcRn- dependent transcytosis assay as a screening tool for predictive assessment of nonspecific clearance of antibody therapeutics in humans

Abstract: View related articles View Crossmark data Citing articles: 5 View citing articles REPORT An in vitro FcRn-dependent transcytosis assay as a screening tool for predictive assessment of nonspecific clearance of antibody therapeutics in humans

Cited by 47 publications

References 61 publications

A Physiologically‐Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics FromIn VitroData

A Physiologically‐Based Pharmacokinetic Model for the Prediction of Monoclonal Antibody Pharmacokinetics FromIn VitroData

A single molecular descriptor to predict solution behavior of therapeutic antibodies

Pharmacokinetic prediction of an antibody in mice based on an in vitro cell-based approach using target receptor-expressing cells

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