http://informahealthcare.com/xen ISSN: 0049-8254 (print), 1366-5928 (electronic) Xenobiotica, Early Online: 1–8 ! 2014 Informa UK Ltd. DOI: 10.3109/00498254.2014.941963
RESEARCH ARTICLE
Application of human FcRn transgenic mice as a pharmacokinetic screening tool of monoclonal antibody Kenta Haraya1,2, Tatsuhiko Tachibana1,2, Masahiko Nanami2, and Masaki Ishigai2 Chugai Pharmabody Research Pte. Ltd., Singapore and 2Research Division, Chugai Pharmaceutical Co., Ltd., Gotemba, Shizuoka, Japan
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Abstract
Keywords
1. For drug discovery, useful screening tools are essential to select superior candidates. Here, we evaluated the applicability of transgenic mice expressing human neonatal Fc receptor (FcRn) (hFcRn Tgm) as a pharmacokinetic screening tool of therapeutic monoclonal antibodies (mAbs) and Fc-fusion proteins that overcomes the species difference in FcRn binding. 2. Marketed 11 mAbs and 2 Fc-fusion proteins were intravenously administered to hFcRn Tgm and WT mice. The half-lives in hFcRn Tgm and WT mice were compared with those in human obtained from literature. The linear half-lives in human and monkey were also calculated by nonlinear pharmacokinetic analysis. For comparison, correlations of half-lives between monkey and human were also evaluated. 3. The half-lives of mAbs and Fc-fusion proteins after intravenous administration ranged from 1.1 to 13.2 days in hFcRn Tgm and from 1.2 to 30.3 days in WT mice. The half-lives in human correlated more closely with those in hFcRn Tgm than in WT mice and monkey. 4. Our results suggest that hFcRn Tgm are a valuable and useful tool for pharmacokinetic screening of mAbs and Fc-fusion proteins in the preclinical stage. Furthermore, we believe that hFcRn Tgm are broadly applicable to preclinical pharmacokinetic screening of mAbsbased therapeutics.
FcRn, monoclonal antibody, preclinical pharmacokinetic screening, transgenic mice
Introduction Therapeutic monoclonal antibodies (mAbs) and Fc fusion proteins have been successfully developed for various diseases (Chan & Carter, 2010; Weiner et al., 2010). Currently, about 30 mAbs are being marketed in the US or the EU, and the pipeline includes 350 mAbs being evaluated in clinical trials around the world (Nelson et al., 2010; Reichert, 2012). Although in human there are 5 subclasses of immunoglobulins (IgA, IgD, IgE, IgG and IgM), most mAbs are IgG. MAbs are characterized by high specificity and affinity to the target antigen and a long half-life in vivo (Morell et al., 1970; Waldmann & Strober, 1969). Generally, although therapeutic proteins exhibit a short half-life of up to 2 days (e.g. erythropoietin (McMahon et al., 1990), growth hormone (Tanaka et al., 1999) and granulocyte colonystimulating factor (Hernandez-Bernal et al., 2005)), mAbs and Fc-fusion proteins exhibit a long half-life of 10–30 days (Black et al., 2010; Lopez et al., 2010). Therefore, the greatest advantage of mAbs and Fc-fusion proteins over other
Address for correspondence: Kenta Haraya, Chugai Pharmabody Research Pte. Ltd., 3 Biopolis Drive, #04-11 to 17 Synapse 138623, Singapore. Tel: (+65)-6933-4847. Fax: (+65)-6684-2257. E-mail: [email protected]
History Received 17 April 2014 Revised 30 June 2014 Accepted 2 July 2014 Published online 17 July 2014
therapeutic proteins is in reducing the dosing frequency. The long half-life of mAbs and Fc-fusion proteins has largely been attributed to the protective role of neonatal Fc receptor (FcRn). FcRn was first detected in the intestine of rodents as the protein which transfers maternal IgG from mother to infant via ingestion of milk (Jones & Waldmann, 1972; Rodewald, 1973). It is a heterodimeric protein consisting of class I major histocompatibility complex (MHC-I) like-protein (a-FcRn) and b2-microglobulin (b2m) (West & Bjorkman, 2000) and is widely expressed in various organs (Israel et al., 1997). The binding of IgG to FcRn is reported to be strictly pH-dependent (Martin et al., 2001; Vaughn & Bjorkman, 1998; West & Bjorkman, 2000); that is, IgG binds to FcRn at acidic pH (pH 6.0–6.5) but not at neutral pH (pH 7.4). As IgG binds to FcRn in the endosome under acidic pH, it is recycled to the cell surface as part of the IgG-FcRn complex and then, since FcRn cannot bind to IgG at neutral pH, is released to plasma. As a result, IgG has a long half-life in blood. Studies in FcRn-deficient mice have illustrated that clearance of IgG was greatly increased, demonstrating the important role of FcRn (Ghetie et al., 1996; Israel et al., 1996; Junghans & Anderson, 1996). Although IgG-FcRn binding has been demonstrated in various species such as mouse, rat, rabbit, bovine, monkey
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and human, it is subject to species differences (Andersen et al., 2010; Ober et al., 2001). For human IgG-based drugs such as mAbs and Fc-fusion proteins, human IgG Fc is known to bind to human and monkey FcRn with similar affinity, but to bind to rodent FcRn with significantly higher affinity (Datta-Mannan et al., 2007; Deng et al., 2010; Yeung et al., 2009). Moreover, most mAbs and Fc-fusion proteins bind to monkey target antigens because sequence homology of target antigen between human and monkey is extremely high in many cases. Therefore, cynomolgus monkey has frequently been used as a predictive method for human pharmacokinetics and as an evaluation tool for pharmacology and toxicology (Deng et al., 2011; Dong et al., 2011; Ling et al., 2009). In the drug development process, selecting a promising candidate is critically important and needs screening tools that have high predictive accuracy to select candidates with the desired pharmacokinetics in human. As noted above, predictions in cynomolgus monkey have proved reliable; however, it involves considerable expense and there are animal ethical concerns that limit their routine use. Since optimal pharmacokinetic properties can improve the quality of life (QOL) of patients, a screening tool that is highly predictive, high throughput and simple to handle is required for pharmacokinetic evaluation for mAbs and Fc-fusion proteins. In this report, we focused on transgenic mice expressing human FcRn (hFcRn Tgm) as an in vivo pharmacokinetic screening tool for mAbs and Fc-fusion proteins. hFcRn Tgm developed by Jackson Laboratory are deficient in mouse a-FcRn and carry human a-FcRn (Petkova et al., 2006), making them a valuable tool for pharmacokinetic screening. Marketed 11 mAbs and 2 Fc fusion proteins were used for evaluation. Half-lives of mAbs and Fc-fusion proteins were assessed in hFcRn Tgm and WT mice following intravenous administration and were then compared with those in human. For comparison, the half-lives in monkey obtained from literature were also compared with those in human. We found that there was a better correlation of half-lives to human in hFcRn Tgm rather than WT mice or monkey, which supports the applicability of hFcRn Tgm as a pharmacokinetic screening tool for mAbs and Fc-fusion proteins.
Materials and methods
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Table 1. List of mAbs and Fc-fusion proteins used in this study. Antibody name Trastuzumab Bevacizumab Infliximab Palivizumab Omalizumab Tocilizumab Golimumab Ustekinumab Rituximab Panitumumab Denosumab Abatacept Etanercept
Target
Subclass
PK linearity
HER2 VEGF TNFa RSV IgE IL-6R TNFa IL-12/23 CD20 EGFR RANKL CD80/86 TNFa
IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG2 IgG2 Fc-fusion Fc-fusion
Nonlinear Linear Linear Linear Linear Nonlinear Linear Linear Linear Nonlinear Nonlinear Linear Linear
trastuzumab in human were obtained by scanning the data from PMDA (2005) and Tokuda et al. (1999). Also, the plasma concentration–time profiles of tocilizumab, trastuzumab and denosumab in monkey were obtained by scanning the data from PMDA (2001, 2005, 2012). The plasma concentration–time profiles were analyzed by empirical 2-compartmental models with parallel linear and nonlinear clearance represented by the Michaelis–Menten model (Figure 1). Nonlinear clearance from central compartment was assumed in this model. The linear half-life was obtained according to the following equations ( > ): þ ¼ k12 þ k21 þ kel ¼ k21 þ kel 1 ¼ ½ðkel þ k12 þ k21 Þ 2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðkel þ k12 þ k21 Þ2 4 kel k21 Half-life ¼
ln 2
The pharmacokinetic parameters of linear elimination for panitumumab and denosumab in human were obtained from literature (Gibiansky et al., 2012; Ma et al., 2009a).
Data collection
MAbs and Fc-fusion proteins
In this study, marketed 11 mAbs and 2 Fc-fusion proteins were selected for evaluation (Table 1) by choosing those for which pharmacokinetic data in human could be obtained and that had diverse target antigens (soluble or membrane and monomer or multimer). Eleven mAbs consisted of 9 IgG1 and 2 IgG2 subtype. Pharmacokinetic parameters of those mAbs and Fc-fusion proteins in human and monkey were obtained from information on Pharmaceuticals and Medical Devices Agency (PMDA) or literature. For mAbs and Fc-fusion proteins with multiple sources of data, the half-life data from the highest given dose was selected.
Tocilizumab, trastuzumab, bevacizumab and rituximab were obtained from within Chugai Pharmaceuticals Co., Ltd. Other mAbs and Fc fusion proteins were purchased from Komtur Pharmaceuticals (Freiburg, Germany).
Nonlinear pharmacokinetic analysis Tocilizumab, trastuzumab, panitumumab and denosumab exhibited nonlinear pharmacokinetics in clinical trials. The plasma concentration–time profiles of tocilizumab and
Pharmacokinetic study in WT mice and human FcRn transgenic mice Pharmacokinetic studies for mAbs were conducted in male C57BL/6J WT mice (Charles River, Yokohama, Japan) and human FcRn homozygous transgenic mice (line 276) (B6. mFcRn/. hFcRn Tg line 276+/+ mouse, Jackson Laboratories, Bar Harbor, ME) (Roopenian et al., 2010). MAbs (1 mg/kg) were administered intravenously to WT mice (n ¼ 3) and hFcRn Tgm (n ¼ 3) via the tail vein. Blood samples were collected at 15 min, 7 h, 1, 2, 4, 7, 14, 21, 28, 35, 42, 49 and 56 days after administration. Blood samples
DOI: 10.3109/00498254.2014.941963
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Data analysis The plasma concentration–time profiles were analyzed by non-compartmental analysis with pharmacokinetic analysis software Phoenix WinNonlin (Ver. 6.2, Pharsight Corporation, Mountain View, CA), to calculate the PK parameters. Terminal elimination rate constants (kel) were estimated by linear regression of the log-linear plasma concentration–time profiles. Half-life was calculated by dividing natural logarithm of two by the kel. The correlation coefficient (r), the mean value and the standard deviation (SD) were calculated using Microsoft Excel 2007.
Results
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Pharmacokinetic parameters in human and monkey
Figure 1. Two-compartmental models with parallel linear and nonlinear clearance after intravenous administration. kel, k12, k21, V1, V2, Vmax and Km represent linear elimination rate constant, transfer rate constant from central compartment to peripheral compartment, transfer rate constant from peripheral compartment to central compartment, volume of distribution of central compartment, volume of distribution of peripheral compartment, maximum rate of nonlinear elimination and Michaelis– Menten constatnt, respectively.
were centrifuged at 12 000 rpm for 15 min at 4 C to obtain plasma samples, which were kept at 40 C until assay. All animal experiments in this study were performed according to the Guidelines for the Care and Use of Laboratory Animals at Chugai Pharmaceutical Co., Ltd. Bioanalytical assay Plasma concentrations of mAbs and Fc-fusion proteins were determined using an anti-human IgG bioanalytical assay. ELISA 96-well plates (Nunc-Immuno plates with a MaxiSorp surface; Nalge Nunc International, Rochester, NY) were precoated with 1 mg/ml anti-human IgG (g-chain specific) F(ab0 )2 fragment of antibody (Sigma, Tokyo, Japan). The plates were blocked with 0.5% bovine serum albumin (BSA, Roche Applied Science, Penzberg, Germany) and 10% Block Ace (Dainippon Sumitomo Pharma, Japan) in Tris-buffered saline (TBS, Sigma, Japan) for 2 h. Plasma samples were added and incubated for 1 h, followed by incubation with biotinylated goat anti-human IgG (Southern Biotechnology Associates, Birmingham, AL) for 1 h. Subsequently, Streptavidin-PolyHRP80 (Stereospecific Detection Technologies, Baesweiler, Germany) was added to react for 1 h, and chromogenic reaction was carried out using TMB One Component HRP Microwell Substrate (BioFX Laboratories, Owings Mills, MA) as a substrate. After stopping the reaction with 1 N sulfuric acid (Showa Chemical, Tokyo, Japan), the absorbance at 450 nm was measured by a microplate reader. The plates were washed 3–5 times with PBS containing 0.05% Tween 20 (Sigma, Tokyo, Japan) after each step.
Half-lives of mAbs and Fc-fusion proteins in human and monkey were obtained from PMDA or literature (Table 2). Although most of the half-lives were obtained from intravenous data, some half-lives were obtained from subcutaneous data. In human, half-lives of mAbs and Fc-fusion proteins exhibited a wide range of values (about 3–30 days) (Gottlieb et al., 2007; Hayashi et al., 2007; Herbst et al., 2005; Klotz et al., 2007; Korth-Bradley et al., 2000; Ma et al., 2009b; Marathe et al., 2008; Nishimoto et al., 2003; Saez-Llorens et al., 2004; Stephenson et al., 2009; Tobinai et al., 1998; Tokuda et al., 1999; Zhou et al., 2007). A similar trend was seen for half-lives in monkeys (about 1–18 day) (Bernett et al., 2013; Lee et al., 2013; Lin et al., 1999; PMDA, 2001, 2002, 2005, 2009, 2011a, 2011b, 2012; Rojas et al., 2005; Vaidyanathan et al., 2011). The half-life of panitumumab in monkey could not be found in PMDA or literature. If the target antigens are membrane proteins, the pharmacokinetics of mAbs may be nonlinear (Amano et al., 2010; Ng et al., 2006). Because tocilizumab, trastuzumab, panitumumab and denosumab target membrane proteins (IL-6 receptor, HER2, EGFR and RANKL, respectively) are known to have clearance, that is antigen-dependent in human, the pharmacokinetics of these mAbs are nonlinear (Doi et al., 2009; Kumagai et al., 2011; Nishimoto et al., 2003; Tokuda et al., 1999). In mice, however, these mAbs do not bind to the target antigens, so the pharmacokinetics is considered to be linear. Since it is useful to understand antigen-independent clearance, we calculated the linear halflives in human and monkey by non-linear pharmacokinetic analysis so that they could be compared with linear half-lives in mice. The estimated linear half-lives in human and monkey are summarized in Table 2. Pharmacokinetic parameters in hFcRn Tgm and WT mice The pharmacokinetics of 11 mAbs and 2 Fc-fusion proteins was evaluated in hFcRn Tgm and WT mice after intravenous administration. The estimated half-lives from noncompartmental analysis are summarized in Table 2. Following intravenous administration, plasma concentrations of mAbs and Fc-fusion proteins exhibited monophasic or biphasic profiles with linearity at the terminal phase. The half-lives of mAbs and Fc-fusion proteins ranged from 1.1 to 13.2 days in hFcRn Tgm and from 1.2 to 30.3 days in
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WT mice. Throughout the study, rapid drop of plasma mAb and Fc-fusion proteins concentrations, which may be caused by anti-drug antibodies, was not observed. Correlation of half-lives between human and hFcRn Tgm or WT mice or monkey To evaluate whether there is any correlation between the half-lives of human and hFcRn Tgm or WT mice or monkey, half-lives of each mouse and monkey were plotted against Table 2. Half-lives (day) of mAbs and Fc-fusion proteins in human, monkey, hFcRn Tgm and WT mice.
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Human
Monkey
Antibody name
High High dose Linear dose Linear hFcRnTgm
Trastuzumab Bevacizumab Infliximab Palivizumab Omalizumab Tocilizumab Golimumab Ustekinumab Rituximab Panitumumab Denosumab Abatacept Etanercept
10.4 18.4 12.3 16.8 18.2 10.1 19.9 28.6 16 6.7 31.5 11.8 2.8
21.6 – – – – 11.9 – – – 18.7 35.8 – –
6.8 13.8 5 7.1 8.5 8.2 17.7 12.1 8 – 1.2 5.4 1.9
16.9 – – – – 9.2 – – – – 4.1 – –
7.7 ± 0.7 9.7 ± 1.8 9.1 ± 1.3 3.5 ± 0.6 9.1 ± 0.8 6.9 ± 0.8 12.3 ± 0.6 13.1 ± 1.2 7.0 ± 1.9 13.2 ± 0.7 12.6 ± 2 1.7 ± 0.6 1.1 ± 0.2
WT mouse 21.5 ± 3.2 18.0 ± 5.5 30.3 ± 0.9 20.5 ± 3.2 28.5 ± 4.9 19.9 ± 0.4 20.4 ± 1.5 26.8 ± 5.7 20.0 ± 3.0 29.3 ± 2.3 21.1 ± 1.1 1.6 ± 0.1 1.2 ± 0.2
Half-lives in hFcRn Tgm and WT mice are represented as mean ± SD.
those in human. The correlations were categorized into four groups. In group 1, half-lives of each mouse and monkey were compared using the highest dosing data in human (Figure 2). In group 2, half-lives of each mouse and monkey were compared using linear data calculated by nonlinear pharmacokinetic analysis in human (Figure 3). In group 3, halflives of each mouse and monkey were compared using only the data of mAbs and Fc-fusion proteins that exhibit linear pharmacokinetics in human (Figure 4). In group 4, half-lives of each mouse and monkey were compared using data from group 2, but excluding those of Fc fusion proteins (Figure 5). First, in group 1, a better correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.57) compared with WT mice (r ¼ 0.35) and monkey (r ¼ 0.26) (Figure 2). Then, in group 2, the correlation coefficient (r) was improved by comparing the linear half-lives of the hFcRn Tgm and WT mice with linear half-lives calculated from data of nonlinear pharmacokinetics in human (Figure 3). Moreover, a better correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.74) compared with WT mice (r ¼ 0.50) and monkey (r ¼ 0.31). Subsequently, in group 3, a further improved correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.80) compared with WT mice (r ¼ 0.66) and monkey (r ¼ 0.75) (Figure 4). Finally, in group 4, a better correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.59) compared with WT mice (r ¼ 0.05) and monkey (r ¼ 0.01) (Figure 5). In fact, in all groups, a better correlation coefficient was obtained using half-lives of hFcRn Tgm compared with WT mice and monkey.
Figure 2. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using highest dosing data in human (group 1, including all mAbs and Fc-fusion proteins).
Figure 3. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using linear data calculated from nonlinear pharmacokinetic analysis (group 2, including all mAbs and Fc-fusion proteins).
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Figure 4. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using only data of mAbs and Fc-fusion proteins exhibiting linear pharmacokinetics in human (group 3, including bevacizumab, infliximab, palivizumab, omalizumab, golimumab, ustekinumab, rituximab, abatacept and etanercept).
Figure 5. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using data from group 2, except those for Fcfusion proteins (group 4, including all mAbs).
Discussion In the drug development process, it is very important to select the optimal clinical candidate. Appropriate tools are required to distinguish the optimal drug from many candidates. In the preclinical development stage, pharmacokinetic screening is essential for the selection of candidates. In in vivo pharmacokinetic tools, monkeys and rodents are commonly used animal species for determining mAb pharmacokinetics. However, as noted above, since there are known species differences in mAb-FcRn binding, rodents are no longer considered suitable animal models for pharmacokinetic screening of mAbs. Moreover, although monkeys are valuable for human prediction, they are too costly and inconvenient to be used for screening. More importantly, it would be almost impossible to use monkey for pharmacokinetic screening of mAbs due to animal ethical issues. There are various factors that impact the pharmacokinetics of mAbs and Fc-fusion proteins, such as FcRn binding (Suzuki et al., 2010), isoelectric point (Igawa et al., 2010b), immunogenicity (Karmiris et al., 2009), off-target binding (Bumbaca et al., 2011; Vugmeyster et al., 2011) and glycosylation (Yu et al., 2012). In particular, FcRn binding has been broadly investigated for the pharmacokinetics of mAbs and Fc-fusion proteins. Engineered mAbs with improved affinity for hFcRn at acidic pH show increased half-lives in monkey (Deng et al., 2010; Yeung et al., 2009) and human (Robbie et al., 2013). Although the
pharmacokinetic improvement of human IgG mutants with increased binding affinities to human FcRn could not be detected in WT mice, they were readily discernible in hFcRn Tgm (Petkova et al., 2006). Therefore, in this study, we compared the pharmacokinetics of mAbs and Fc-fusion proteins in hFcRn Tgm, WT mice and monkey with those in human. Previously, Tam et al. (2013) reported availability of hFcRn Tgm. Although used strain of hFcRn Tgm was different from our report, a significant relationship of half-life between hFcRn Tgm and human was observed using their inhouse mAbs. Half-life was used in this study to evaluate correlativity between mice and human because, compared with clearance, it is unlikely to be affected by variability or error in linear pharmacokinetics. Additionally, mAbs for which there are only subcutaneous data can be included in the analysis because, in linear pharmacokinetics, half-life is not affected by subcutaneous absorption. Theoretically, flip-flop kinetics can affect half-life of drug after subcutaneous absorption. However, because generally mAbs has relatively fast subcutaneous absorption rate (smaller than 0.5 day1) compared with elimination rate, it is unlikely that flip-flop kinetics occurs (Richter et al., 2012). The results, which showed that a better correlation coefficient was obtained using the half-lives of hFcRn Tgm compared to WT mice and monkey, demonstrate the usefulness of hFcRn Tgm as a simple and valuable pharmacokinetic screening tool in the preclinical stage.
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First, in group 1, half-lives of the highest dosing data in human and monkey were used to evaluate correlations (Figure 2). As mAbs and Fc-fusion proteins interact with target membrane antigen, antigen-dependent clearance means that some mAbs exhibit nonlinear pharmacokinetics, the highest dosing data should be used to minimize the influence of antigen-dependent clearance. However, because even the highest dosing data may not completely remove the influence of antigen-dependent clearance, we considered separating the linear half-lives from nonlinear pharmacokinetics in human and monkey. For mAbs exhibiting nonlinear pharmacokinetics, empirical 2-compartmental models with parallel linear and nonlinear clearance (represented by target-mediated drug disposition (TMDD) or the Michaelis–Menten equation) have often been used for pharmacokinetic analysis (Betts et al., 2010; Mould et al., 2007). Because the TMDD model can be applied to either in vivo or in vitro information about the target and affinity to the target, it has been used for mechanism-based prediction of nonlinear pharmacokinetics in human (Luu et al., 2012). However, in many cases, target information is unavailable. In such a case, the Michaelis– Menten equation has been applied despite a lack of mechanistic assumption (Bauer et al., 1999; Cosson et al., 2014; Kloft et al., 2004). In group 2, half-lives of highest dosing data in mAbs and Fc-fusion proteins exhibiting linear pharmacokinetics and linear half-lives obtained by nonlinear pharmacokinetic analysis in mAbs exhibiting nonlinear pharmacokinetics were used for evaluation of correlations (Figure 3). The correlation coefficient in group 2 shows a better value than in group 1, which demonstrates that half-lives in group 1 are not completely removed from the influence of antigen-dependent clearance. Furthermore, the half-lives of hFcRn Tgm in group 2 gave a better correlation coefficient than WT mice and monkey. Subsequently, only the half-lives of mAbs and Fc-fusion proteins exhibiting linear pharmacokinetics were used to evaluate the correlations in group 3 in order to remove the influence of antigen-dependent clearance completely (Figure 4). As a result, the correlation coefficient obtained using half-lives of hFcRn Tgm in group 3 was again better than that of WT mice and monkey. In this report, we used 2 Fc-fusion proteins (etanercept and abatacept). Because Fc-fusion proteins are composed of an IgG Fc domain that is linked to another protein (Glaesner et al., 2010) and have relatively lower affinity to FcRn, their half-lives are typically shorter than those of mAbs (Suzuki et al., 2010). Since the short half-lives of Fc-fusion proteins might show seemingly good correlativity, in group 4 only half-lives of mAbs in group 2 (excluding Fc-fusion proteins) were used for evaluation of correlations (Figure 5). When there are two or more candidates in a project, mAbs and Fcfusion proteins are generally not intermingled, and during the screening process, it is considered reasonable to evaluate correlativity using only the mAbs. In group 4, unlike the results in groups 1, 2 and 3, there was no correlativity of the results in WT mice and monkey, although a positive correlation was obtained using half-lives of hFcRn Tgm. This result suggested that hFcRn Tgm have a definite
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advantage over WT mice and monkey for pharmacokinetic screening of mAbs and Fc-fusion proteins. Although our results demonstrate the applicability of hFcRn Tgm, there is still room for improvement. As mouse IgG binds to human FcRn with very low affinity (Ober et al., 2001), hFcRn Tgm have a low level of endogenous IgG in blood compared with WT mice (Stein et al., 2012). Since humans have high levels of endogenous IgG in blood, in the range of mg/mL (Belldegrin et al., 1980), having competition for human IgG (such as IVIG) may enhance the usefulness of hFcRn Tgm. Additionally, as most of mAbs do not bind to mouse target antigen, hFcRn Tgm cannot be applied for pharmacological and toxicological study. However, if human target antigen and human FcRn double transgenic mice is generated, it can also be useful for other studies. We propose that hFcRn Tgm should be chosen for the first screening in vivo. As antibody candidates are produced and generated by various methods and the pharmacokinetics of mAbs and Fc-fusion proteins is affected by various factors, a high throughput method of in vivo screening is essential. hFcRn Tgm are convenient, cost effective and high throughput in vivo tools compared with monkeys. Therefore, pharmacokinetic studies in hFcRn Tgm should be conducted for in vivo screening prior to pharmacokinetic studies in monkeys. Moreover, hFcRn Tgm can also reduce the number of monkeys used in drug development and improve screening efficiency. Additionally, hFcRn Tgm may be useful when Fc engineering variants with the same variable region are evaluated because evaluation can be conducted in the situation where target antigen type, affinity to target antigen and physicochemical factor of variable region are in same conditions. In particular, as noted above, species differences of FcRn binding should be overcome using hFcRn Tgm. Therefore, hFcRn Tgm should be optimal animal for screening of Fc by engineering FcRn binding. We assessed the applicability of hFcRn Tgm for pharmacokinetic screening of mAbs and Fc-fusion proteins in the preclinical stage by looking at correlations across four groups and comparing the correlation coefficients. A better correlation coefficient was obtained by using half-lives of hFcRn Tgm compared with WT mice and monkey; therefore, hFcRn Tgm can routinely be used in the pharmacokinetic screening of mAbs and Fc-fusion proteins in the preclinical stage. Currently, there are many challenges in the development of mAbs-based therapeutics such as bispecific antibody (Kitazawa et al., 2012), antibody drug conjugate (Burris et al., 2011), antibody-dependent cell cytotoxicity (ADCC) enhancing technology (Mori et al., 2007) and pH-dependent antigen binding (Igawa et al., 2010a). MAbs-based therapeutics have also been protected from endosomal degradation by recycling via FcRn. This study demonstrates that not only hFcRn Tgm are a valuable and useful tool for preclinical pharmacokinetic screening of mAbs and Fc-fusion proteins, they are also broadly applicable as preclinical pharmacokinetic screening tools for mAbs-based therapeutics.
Acknowledgements We thank colleagues in Chugai Research Institute for Medical Science, Inc, and Chugai Pharmaceutical Co. Ltd:
DOI: 10.3109/00498254.2014.941963
M. Kawaharada, T. Yokoyama and T. Nishimura for carrying out the bioanalytical assays; T. Tachibe, H. Tateishi, Y. Kawase and K Jishage for breeding hFcRn Tgm.
Declaration of interest The authors report no declarations of interest.
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RESEARCH ARTICLE
Application of human FcRn transgenic mice as a pharmacokinetic screening tool of monoclonal antibody Kenta Haraya1,2, Tatsuhiko Tachibana1,2, Masahiko Nanami2, and Masaki Ishigai2 Chugai Pharmabody Research Pte. Ltd., Singapore and 2Research Division, Chugai Pharmaceutical Co., Ltd., Gotemba, Shizuoka, Japan
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Abstract
Keywords
1. For drug discovery, useful screening tools are essential to select superior candidates. Here, we evaluated the applicability of transgenic mice expressing human neonatal Fc receptor (FcRn) (hFcRn Tgm) as a pharmacokinetic screening tool of therapeutic monoclonal antibodies (mAbs) and Fc-fusion proteins that overcomes the species difference in FcRn binding. 2. Marketed 11 mAbs and 2 Fc-fusion proteins were intravenously administered to hFcRn Tgm and WT mice. The half-lives in hFcRn Tgm and WT mice were compared with those in human obtained from literature. The linear half-lives in human and monkey were also calculated by nonlinear pharmacokinetic analysis. For comparison, correlations of half-lives between monkey and human were also evaluated. 3. The half-lives of mAbs and Fc-fusion proteins after intravenous administration ranged from 1.1 to 13.2 days in hFcRn Tgm and from 1.2 to 30.3 days in WT mice. The half-lives in human correlated more closely with those in hFcRn Tgm than in WT mice and monkey. 4. Our results suggest that hFcRn Tgm are a valuable and useful tool for pharmacokinetic screening of mAbs and Fc-fusion proteins in the preclinical stage. Furthermore, we believe that hFcRn Tgm are broadly applicable to preclinical pharmacokinetic screening of mAbsbased therapeutics.
FcRn, monoclonal antibody, preclinical pharmacokinetic screening, transgenic mice
Introduction Therapeutic monoclonal antibodies (mAbs) and Fc fusion proteins have been successfully developed for various diseases (Chan & Carter, 2010; Weiner et al., 2010). Currently, about 30 mAbs are being marketed in the US or the EU, and the pipeline includes 350 mAbs being evaluated in clinical trials around the world (Nelson et al., 2010; Reichert, 2012). Although in human there are 5 subclasses of immunoglobulins (IgA, IgD, IgE, IgG and IgM), most mAbs are IgG. MAbs are characterized by high specificity and affinity to the target antigen and a long half-life in vivo (Morell et al., 1970; Waldmann & Strober, 1969). Generally, although therapeutic proteins exhibit a short half-life of up to 2 days (e.g. erythropoietin (McMahon et al., 1990), growth hormone (Tanaka et al., 1999) and granulocyte colonystimulating factor (Hernandez-Bernal et al., 2005)), mAbs and Fc-fusion proteins exhibit a long half-life of 10–30 days (Black et al., 2010; Lopez et al., 2010). Therefore, the greatest advantage of mAbs and Fc-fusion proteins over other
Address for correspondence: Kenta Haraya, Chugai Pharmabody Research Pte. Ltd., 3 Biopolis Drive, #04-11 to 17 Synapse 138623, Singapore. Tel: (+65)-6933-4847. Fax: (+65)-6684-2257. E-mail: [email protected]
History Received 17 April 2014 Revised 30 June 2014 Accepted 2 July 2014 Published online 17 July 2014
therapeutic proteins is in reducing the dosing frequency. The long half-life of mAbs and Fc-fusion proteins has largely been attributed to the protective role of neonatal Fc receptor (FcRn). FcRn was first detected in the intestine of rodents as the protein which transfers maternal IgG from mother to infant via ingestion of milk (Jones & Waldmann, 1972; Rodewald, 1973). It is a heterodimeric protein consisting of class I major histocompatibility complex (MHC-I) like-protein (a-FcRn) and b2-microglobulin (b2m) (West & Bjorkman, 2000) and is widely expressed in various organs (Israel et al., 1997). The binding of IgG to FcRn is reported to be strictly pH-dependent (Martin et al., 2001; Vaughn & Bjorkman, 1998; West & Bjorkman, 2000); that is, IgG binds to FcRn at acidic pH (pH 6.0–6.5) but not at neutral pH (pH 7.4). As IgG binds to FcRn in the endosome under acidic pH, it is recycled to the cell surface as part of the IgG-FcRn complex and then, since FcRn cannot bind to IgG at neutral pH, is released to plasma. As a result, IgG has a long half-life in blood. Studies in FcRn-deficient mice have illustrated that clearance of IgG was greatly increased, demonstrating the important role of FcRn (Ghetie et al., 1996; Israel et al., 1996; Junghans & Anderson, 1996). Although IgG-FcRn binding has been demonstrated in various species such as mouse, rat, rabbit, bovine, monkey
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and human, it is subject to species differences (Andersen et al., 2010; Ober et al., 2001). For human IgG-based drugs such as mAbs and Fc-fusion proteins, human IgG Fc is known to bind to human and monkey FcRn with similar affinity, but to bind to rodent FcRn with significantly higher affinity (Datta-Mannan et al., 2007; Deng et al., 2010; Yeung et al., 2009). Moreover, most mAbs and Fc-fusion proteins bind to monkey target antigens because sequence homology of target antigen between human and monkey is extremely high in many cases. Therefore, cynomolgus monkey has frequently been used as a predictive method for human pharmacokinetics and as an evaluation tool for pharmacology and toxicology (Deng et al., 2011; Dong et al., 2011; Ling et al., 2009). In the drug development process, selecting a promising candidate is critically important and needs screening tools that have high predictive accuracy to select candidates with the desired pharmacokinetics in human. As noted above, predictions in cynomolgus monkey have proved reliable; however, it involves considerable expense and there are animal ethical concerns that limit their routine use. Since optimal pharmacokinetic properties can improve the quality of life (QOL) of patients, a screening tool that is highly predictive, high throughput and simple to handle is required for pharmacokinetic evaluation for mAbs and Fc-fusion proteins. In this report, we focused on transgenic mice expressing human FcRn (hFcRn Tgm) as an in vivo pharmacokinetic screening tool for mAbs and Fc-fusion proteins. hFcRn Tgm developed by Jackson Laboratory are deficient in mouse a-FcRn and carry human a-FcRn (Petkova et al., 2006), making them a valuable tool for pharmacokinetic screening. Marketed 11 mAbs and 2 Fc fusion proteins were used for evaluation. Half-lives of mAbs and Fc-fusion proteins were assessed in hFcRn Tgm and WT mice following intravenous administration and were then compared with those in human. For comparison, the half-lives in monkey obtained from literature were also compared with those in human. We found that there was a better correlation of half-lives to human in hFcRn Tgm rather than WT mice or monkey, which supports the applicability of hFcRn Tgm as a pharmacokinetic screening tool for mAbs and Fc-fusion proteins.
Materials and methods
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Table 1. List of mAbs and Fc-fusion proteins used in this study. Antibody name Trastuzumab Bevacizumab Infliximab Palivizumab Omalizumab Tocilizumab Golimumab Ustekinumab Rituximab Panitumumab Denosumab Abatacept Etanercept
Target
Subclass
PK linearity
HER2 VEGF TNFa RSV IgE IL-6R TNFa IL-12/23 CD20 EGFR RANKL CD80/86 TNFa
IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG1 IgG2 IgG2 Fc-fusion Fc-fusion
Nonlinear Linear Linear Linear Linear Nonlinear Linear Linear Linear Nonlinear Nonlinear Linear Linear
trastuzumab in human were obtained by scanning the data from PMDA (2005) and Tokuda et al. (1999). Also, the plasma concentration–time profiles of tocilizumab, trastuzumab and denosumab in monkey were obtained by scanning the data from PMDA (2001, 2005, 2012). The plasma concentration–time profiles were analyzed by empirical 2-compartmental models with parallel linear and nonlinear clearance represented by the Michaelis–Menten model (Figure 1). Nonlinear clearance from central compartment was assumed in this model. The linear half-life was obtained according to the following equations ( > ): þ ¼ k12 þ k21 þ kel ¼ k21 þ kel 1 ¼ ½ðkel þ k12 þ k21 Þ 2 qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðkel þ k12 þ k21 Þ2 4 kel k21 Half-life ¼
ln 2
The pharmacokinetic parameters of linear elimination for panitumumab and denosumab in human were obtained from literature (Gibiansky et al., 2012; Ma et al., 2009a).
Data collection
MAbs and Fc-fusion proteins
In this study, marketed 11 mAbs and 2 Fc-fusion proteins were selected for evaluation (Table 1) by choosing those for which pharmacokinetic data in human could be obtained and that had diverse target antigens (soluble or membrane and monomer or multimer). Eleven mAbs consisted of 9 IgG1 and 2 IgG2 subtype. Pharmacokinetic parameters of those mAbs and Fc-fusion proteins in human and monkey were obtained from information on Pharmaceuticals and Medical Devices Agency (PMDA) or literature. For mAbs and Fc-fusion proteins with multiple sources of data, the half-life data from the highest given dose was selected.
Tocilizumab, trastuzumab, bevacizumab and rituximab were obtained from within Chugai Pharmaceuticals Co., Ltd. Other mAbs and Fc fusion proteins were purchased from Komtur Pharmaceuticals (Freiburg, Germany).
Nonlinear pharmacokinetic analysis Tocilizumab, trastuzumab, panitumumab and denosumab exhibited nonlinear pharmacokinetics in clinical trials. The plasma concentration–time profiles of tocilizumab and
Pharmacokinetic study in WT mice and human FcRn transgenic mice Pharmacokinetic studies for mAbs were conducted in male C57BL/6J WT mice (Charles River, Yokohama, Japan) and human FcRn homozygous transgenic mice (line 276) (B6. mFcRn/. hFcRn Tg line 276+/+ mouse, Jackson Laboratories, Bar Harbor, ME) (Roopenian et al., 2010). MAbs (1 mg/kg) were administered intravenously to WT mice (n ¼ 3) and hFcRn Tgm (n ¼ 3) via the tail vein. Blood samples were collected at 15 min, 7 h, 1, 2, 4, 7, 14, 21, 28, 35, 42, 49 and 56 days after administration. Blood samples
DOI: 10.3109/00498254.2014.941963
In vivo PK screening tool for monoclonal antibody
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Data analysis The plasma concentration–time profiles were analyzed by non-compartmental analysis with pharmacokinetic analysis software Phoenix WinNonlin (Ver. 6.2, Pharsight Corporation, Mountain View, CA), to calculate the PK parameters. Terminal elimination rate constants (kel) were estimated by linear regression of the log-linear plasma concentration–time profiles. Half-life was calculated by dividing natural logarithm of two by the kel. The correlation coefficient (r), the mean value and the standard deviation (SD) were calculated using Microsoft Excel 2007.
Results
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Pharmacokinetic parameters in human and monkey
Figure 1. Two-compartmental models with parallel linear and nonlinear clearance after intravenous administration. kel, k12, k21, V1, V2, Vmax and Km represent linear elimination rate constant, transfer rate constant from central compartment to peripheral compartment, transfer rate constant from peripheral compartment to central compartment, volume of distribution of central compartment, volume of distribution of peripheral compartment, maximum rate of nonlinear elimination and Michaelis– Menten constatnt, respectively.
were centrifuged at 12 000 rpm for 15 min at 4 C to obtain plasma samples, which were kept at 40 C until assay. All animal experiments in this study were performed according to the Guidelines for the Care and Use of Laboratory Animals at Chugai Pharmaceutical Co., Ltd. Bioanalytical assay Plasma concentrations of mAbs and Fc-fusion proteins were determined using an anti-human IgG bioanalytical assay. ELISA 96-well plates (Nunc-Immuno plates with a MaxiSorp surface; Nalge Nunc International, Rochester, NY) were precoated with 1 mg/ml anti-human IgG (g-chain specific) F(ab0 )2 fragment of antibody (Sigma, Tokyo, Japan). The plates were blocked with 0.5% bovine serum albumin (BSA, Roche Applied Science, Penzberg, Germany) and 10% Block Ace (Dainippon Sumitomo Pharma, Japan) in Tris-buffered saline (TBS, Sigma, Japan) for 2 h. Plasma samples were added and incubated for 1 h, followed by incubation with biotinylated goat anti-human IgG (Southern Biotechnology Associates, Birmingham, AL) for 1 h. Subsequently, Streptavidin-PolyHRP80 (Stereospecific Detection Technologies, Baesweiler, Germany) was added to react for 1 h, and chromogenic reaction was carried out using TMB One Component HRP Microwell Substrate (BioFX Laboratories, Owings Mills, MA) as a substrate. After stopping the reaction with 1 N sulfuric acid (Showa Chemical, Tokyo, Japan), the absorbance at 450 nm was measured by a microplate reader. The plates were washed 3–5 times with PBS containing 0.05% Tween 20 (Sigma, Tokyo, Japan) after each step.
Half-lives of mAbs and Fc-fusion proteins in human and monkey were obtained from PMDA or literature (Table 2). Although most of the half-lives were obtained from intravenous data, some half-lives were obtained from subcutaneous data. In human, half-lives of mAbs and Fc-fusion proteins exhibited a wide range of values (about 3–30 days) (Gottlieb et al., 2007; Hayashi et al., 2007; Herbst et al., 2005; Klotz et al., 2007; Korth-Bradley et al., 2000; Ma et al., 2009b; Marathe et al., 2008; Nishimoto et al., 2003; Saez-Llorens et al., 2004; Stephenson et al., 2009; Tobinai et al., 1998; Tokuda et al., 1999; Zhou et al., 2007). A similar trend was seen for half-lives in monkeys (about 1–18 day) (Bernett et al., 2013; Lee et al., 2013; Lin et al., 1999; PMDA, 2001, 2002, 2005, 2009, 2011a, 2011b, 2012; Rojas et al., 2005; Vaidyanathan et al., 2011). The half-life of panitumumab in monkey could not be found in PMDA or literature. If the target antigens are membrane proteins, the pharmacokinetics of mAbs may be nonlinear (Amano et al., 2010; Ng et al., 2006). Because tocilizumab, trastuzumab, panitumumab and denosumab target membrane proteins (IL-6 receptor, HER2, EGFR and RANKL, respectively) are known to have clearance, that is antigen-dependent in human, the pharmacokinetics of these mAbs are nonlinear (Doi et al., 2009; Kumagai et al., 2011; Nishimoto et al., 2003; Tokuda et al., 1999). In mice, however, these mAbs do not bind to the target antigens, so the pharmacokinetics is considered to be linear. Since it is useful to understand antigen-independent clearance, we calculated the linear halflives in human and monkey by non-linear pharmacokinetic analysis so that they could be compared with linear half-lives in mice. The estimated linear half-lives in human and monkey are summarized in Table 2. Pharmacokinetic parameters in hFcRn Tgm and WT mice The pharmacokinetics of 11 mAbs and 2 Fc-fusion proteins was evaluated in hFcRn Tgm and WT mice after intravenous administration. The estimated half-lives from noncompartmental analysis are summarized in Table 2. Following intravenous administration, plasma concentrations of mAbs and Fc-fusion proteins exhibited monophasic or biphasic profiles with linearity at the terminal phase. The half-lives of mAbs and Fc-fusion proteins ranged from 1.1 to 13.2 days in hFcRn Tgm and from 1.2 to 30.3 days in
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WT mice. Throughout the study, rapid drop of plasma mAb and Fc-fusion proteins concentrations, which may be caused by anti-drug antibodies, was not observed. Correlation of half-lives between human and hFcRn Tgm or WT mice or monkey To evaluate whether there is any correlation between the half-lives of human and hFcRn Tgm or WT mice or monkey, half-lives of each mouse and monkey were plotted against Table 2. Half-lives (day) of mAbs and Fc-fusion proteins in human, monkey, hFcRn Tgm and WT mice.
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Human
Monkey
Antibody name
High High dose Linear dose Linear hFcRnTgm
Trastuzumab Bevacizumab Infliximab Palivizumab Omalizumab Tocilizumab Golimumab Ustekinumab Rituximab Panitumumab Denosumab Abatacept Etanercept
10.4 18.4 12.3 16.8 18.2 10.1 19.9 28.6 16 6.7 31.5 11.8 2.8
21.6 – – – – 11.9 – – – 18.7 35.8 – –
6.8 13.8 5 7.1 8.5 8.2 17.7 12.1 8 – 1.2 5.4 1.9
16.9 – – – – 9.2 – – – – 4.1 – –
7.7 ± 0.7 9.7 ± 1.8 9.1 ± 1.3 3.5 ± 0.6 9.1 ± 0.8 6.9 ± 0.8 12.3 ± 0.6 13.1 ± 1.2 7.0 ± 1.9 13.2 ± 0.7 12.6 ± 2 1.7 ± 0.6 1.1 ± 0.2
WT mouse 21.5 ± 3.2 18.0 ± 5.5 30.3 ± 0.9 20.5 ± 3.2 28.5 ± 4.9 19.9 ± 0.4 20.4 ± 1.5 26.8 ± 5.7 20.0 ± 3.0 29.3 ± 2.3 21.1 ± 1.1 1.6 ± 0.1 1.2 ± 0.2
Half-lives in hFcRn Tgm and WT mice are represented as mean ± SD.
those in human. The correlations were categorized into four groups. In group 1, half-lives of each mouse and monkey were compared using the highest dosing data in human (Figure 2). In group 2, half-lives of each mouse and monkey were compared using linear data calculated by nonlinear pharmacokinetic analysis in human (Figure 3). In group 3, halflives of each mouse and monkey were compared using only the data of mAbs and Fc-fusion proteins that exhibit linear pharmacokinetics in human (Figure 4). In group 4, half-lives of each mouse and monkey were compared using data from group 2, but excluding those of Fc fusion proteins (Figure 5). First, in group 1, a better correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.57) compared with WT mice (r ¼ 0.35) and monkey (r ¼ 0.26) (Figure 2). Then, in group 2, the correlation coefficient (r) was improved by comparing the linear half-lives of the hFcRn Tgm and WT mice with linear half-lives calculated from data of nonlinear pharmacokinetics in human (Figure 3). Moreover, a better correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.74) compared with WT mice (r ¼ 0.50) and monkey (r ¼ 0.31). Subsequently, in group 3, a further improved correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.80) compared with WT mice (r ¼ 0.66) and monkey (r ¼ 0.75) (Figure 4). Finally, in group 4, a better correlation coefficient (r) was shown in hFcRn Tgm (r ¼ 0.59) compared with WT mice (r ¼ 0.05) and monkey (r ¼ 0.01) (Figure 5). In fact, in all groups, a better correlation coefficient was obtained using half-lives of hFcRn Tgm compared with WT mice and monkey.
Figure 2. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using highest dosing data in human (group 1, including all mAbs and Fc-fusion proteins).
Figure 3. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using linear data calculated from nonlinear pharmacokinetic analysis (group 2, including all mAbs and Fc-fusion proteins).
DOI: 10.3109/00498254.2014.941963
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Figure 4. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using only data of mAbs and Fc-fusion proteins exhibiting linear pharmacokinetics in human (group 3, including bevacizumab, infliximab, palivizumab, omalizumab, golimumab, ustekinumab, rituximab, abatacept and etanercept).
Figure 5. Correlations of half-lives between human and hFcRn Tgm (a), WT mice (b) and monkey (c) using data from group 2, except those for Fcfusion proteins (group 4, including all mAbs).
Discussion In the drug development process, it is very important to select the optimal clinical candidate. Appropriate tools are required to distinguish the optimal drug from many candidates. In the preclinical development stage, pharmacokinetic screening is essential for the selection of candidates. In in vivo pharmacokinetic tools, monkeys and rodents are commonly used animal species for determining mAb pharmacokinetics. However, as noted above, since there are known species differences in mAb-FcRn binding, rodents are no longer considered suitable animal models for pharmacokinetic screening of mAbs. Moreover, although monkeys are valuable for human prediction, they are too costly and inconvenient to be used for screening. More importantly, it would be almost impossible to use monkey for pharmacokinetic screening of mAbs due to animal ethical issues. There are various factors that impact the pharmacokinetics of mAbs and Fc-fusion proteins, such as FcRn binding (Suzuki et al., 2010), isoelectric point (Igawa et al., 2010b), immunogenicity (Karmiris et al., 2009), off-target binding (Bumbaca et al., 2011; Vugmeyster et al., 2011) and glycosylation (Yu et al., 2012). In particular, FcRn binding has been broadly investigated for the pharmacokinetics of mAbs and Fc-fusion proteins. Engineered mAbs with improved affinity for hFcRn at acidic pH show increased half-lives in monkey (Deng et al., 2010; Yeung et al., 2009) and human (Robbie et al., 2013). Although the
pharmacokinetic improvement of human IgG mutants with increased binding affinities to human FcRn could not be detected in WT mice, they were readily discernible in hFcRn Tgm (Petkova et al., 2006). Therefore, in this study, we compared the pharmacokinetics of mAbs and Fc-fusion proteins in hFcRn Tgm, WT mice and monkey with those in human. Previously, Tam et al. (2013) reported availability of hFcRn Tgm. Although used strain of hFcRn Tgm was different from our report, a significant relationship of half-life between hFcRn Tgm and human was observed using their inhouse mAbs. Half-life was used in this study to evaluate correlativity between mice and human because, compared with clearance, it is unlikely to be affected by variability or error in linear pharmacokinetics. Additionally, mAbs for which there are only subcutaneous data can be included in the analysis because, in linear pharmacokinetics, half-life is not affected by subcutaneous absorption. Theoretically, flip-flop kinetics can affect half-life of drug after subcutaneous absorption. However, because generally mAbs has relatively fast subcutaneous absorption rate (smaller than 0.5 day1) compared with elimination rate, it is unlikely that flip-flop kinetics occurs (Richter et al., 2012). The results, which showed that a better correlation coefficient was obtained using the half-lives of hFcRn Tgm compared to WT mice and monkey, demonstrate the usefulness of hFcRn Tgm as a simple and valuable pharmacokinetic screening tool in the preclinical stage.
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First, in group 1, half-lives of the highest dosing data in human and monkey were used to evaluate correlations (Figure 2). As mAbs and Fc-fusion proteins interact with target membrane antigen, antigen-dependent clearance means that some mAbs exhibit nonlinear pharmacokinetics, the highest dosing data should be used to minimize the influence of antigen-dependent clearance. However, because even the highest dosing data may not completely remove the influence of antigen-dependent clearance, we considered separating the linear half-lives from nonlinear pharmacokinetics in human and monkey. For mAbs exhibiting nonlinear pharmacokinetics, empirical 2-compartmental models with parallel linear and nonlinear clearance (represented by target-mediated drug disposition (TMDD) or the Michaelis–Menten equation) have often been used for pharmacokinetic analysis (Betts et al., 2010; Mould et al., 2007). Because the TMDD model can be applied to either in vivo or in vitro information about the target and affinity to the target, it has been used for mechanism-based prediction of nonlinear pharmacokinetics in human (Luu et al., 2012). However, in many cases, target information is unavailable. In such a case, the Michaelis– Menten equation has been applied despite a lack of mechanistic assumption (Bauer et al., 1999; Cosson et al., 2014; Kloft et al., 2004). In group 2, half-lives of highest dosing data in mAbs and Fc-fusion proteins exhibiting linear pharmacokinetics and linear half-lives obtained by nonlinear pharmacokinetic analysis in mAbs exhibiting nonlinear pharmacokinetics were used for evaluation of correlations (Figure 3). The correlation coefficient in group 2 shows a better value than in group 1, which demonstrates that half-lives in group 1 are not completely removed from the influence of antigen-dependent clearance. Furthermore, the half-lives of hFcRn Tgm in group 2 gave a better correlation coefficient than WT mice and monkey. Subsequently, only the half-lives of mAbs and Fc-fusion proteins exhibiting linear pharmacokinetics were used to evaluate the correlations in group 3 in order to remove the influence of antigen-dependent clearance completely (Figure 4). As a result, the correlation coefficient obtained using half-lives of hFcRn Tgm in group 3 was again better than that of WT mice and monkey. In this report, we used 2 Fc-fusion proteins (etanercept and abatacept). Because Fc-fusion proteins are composed of an IgG Fc domain that is linked to another protein (Glaesner et al., 2010) and have relatively lower affinity to FcRn, their half-lives are typically shorter than those of mAbs (Suzuki et al., 2010). Since the short half-lives of Fc-fusion proteins might show seemingly good correlativity, in group 4 only half-lives of mAbs in group 2 (excluding Fc-fusion proteins) were used for evaluation of correlations (Figure 5). When there are two or more candidates in a project, mAbs and Fcfusion proteins are generally not intermingled, and during the screening process, it is considered reasonable to evaluate correlativity using only the mAbs. In group 4, unlike the results in groups 1, 2 and 3, there was no correlativity of the results in WT mice and monkey, although a positive correlation was obtained using half-lives of hFcRn Tgm. This result suggested that hFcRn Tgm have a definite
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advantage over WT mice and monkey for pharmacokinetic screening of mAbs and Fc-fusion proteins. Although our results demonstrate the applicability of hFcRn Tgm, there is still room for improvement. As mouse IgG binds to human FcRn with very low affinity (Ober et al., 2001), hFcRn Tgm have a low level of endogenous IgG in blood compared with WT mice (Stein et al., 2012). Since humans have high levels of endogenous IgG in blood, in the range of mg/mL (Belldegrin et al., 1980), having competition for human IgG (such as IVIG) may enhance the usefulness of hFcRn Tgm. Additionally, as most of mAbs do not bind to mouse target antigen, hFcRn Tgm cannot be applied for pharmacological and toxicological study. However, if human target antigen and human FcRn double transgenic mice is generated, it can also be useful for other studies. We propose that hFcRn Tgm should be chosen for the first screening in vivo. As antibody candidates are produced and generated by various methods and the pharmacokinetics of mAbs and Fc-fusion proteins is affected by various factors, a high throughput method of in vivo screening is essential. hFcRn Tgm are convenient, cost effective and high throughput in vivo tools compared with monkeys. Therefore, pharmacokinetic studies in hFcRn Tgm should be conducted for in vivo screening prior to pharmacokinetic studies in monkeys. Moreover, hFcRn Tgm can also reduce the number of monkeys used in drug development and improve screening efficiency. Additionally, hFcRn Tgm may be useful when Fc engineering variants with the same variable region are evaluated because evaluation can be conducted in the situation where target antigen type, affinity to target antigen and physicochemical factor of variable region are in same conditions. In particular, as noted above, species differences of FcRn binding should be overcome using hFcRn Tgm. Therefore, hFcRn Tgm should be optimal animal for screening of Fc by engineering FcRn binding. We assessed the applicability of hFcRn Tgm for pharmacokinetic screening of mAbs and Fc-fusion proteins in the preclinical stage by looking at correlations across four groups and comparing the correlation coefficients. A better correlation coefficient was obtained by using half-lives of hFcRn Tgm compared with WT mice and monkey; therefore, hFcRn Tgm can routinely be used in the pharmacokinetic screening of mAbs and Fc-fusion proteins in the preclinical stage. Currently, there are many challenges in the development of mAbs-based therapeutics such as bispecific antibody (Kitazawa et al., 2012), antibody drug conjugate (Burris et al., 2011), antibody-dependent cell cytotoxicity (ADCC) enhancing technology (Mori et al., 2007) and pH-dependent antigen binding (Igawa et al., 2010a). MAbs-based therapeutics have also been protected from endosomal degradation by recycling via FcRn. This study demonstrates that not only hFcRn Tgm are a valuable and useful tool for preclinical pharmacokinetic screening of mAbs and Fc-fusion proteins, they are also broadly applicable as preclinical pharmacokinetic screening tools for mAbs-based therapeutics.
Acknowledgements We thank colleagues in Chugai Research Institute for Medical Science, Inc, and Chugai Pharmaceutical Co. Ltd:
DOI: 10.3109/00498254.2014.941963
M. Kawaharada, T. Yokoyama and T. Nishimura for carrying out the bioanalytical assays; T. Tachibe, H. Tateishi, Y. Kawase and K Jishage for breeding hFcRn Tgm.
Declaration of interest The authors report no declarations of interest.
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