(mAb) and Antibody-Drug Conjugates (ADC)

1 downloads 0 Views 1MB Size Report
thus affect ADC PK, efficacy, and toxicity profiles (Fig. 1b). For example, ester hydrolysis was observed with a spliceostatin ADC [47] and a tubulysin ADC [67].
Current Pharmacology Reports https://doi.org/10.1007/s40495-017-0118-x

MOLECULAR DRUG DISPOSITION (H SUN, SECTION EDITOR)

LC–MS Challenges in Characterizing and Quantifying Monoclonal Antibodies (mAb) and Antibody-Drug Conjugates (ADC) in Biological Samples Cong Wei 1 & Dian Su 2 & Jian Wang 3 & Wenying Jian 4 & Donglu Zhang 2

# Springer International Publishing AG, part of Springer Nature 2018

Abstract Monoclonal antibody (mAb) represents majority of protein therapeutics with more than 50 antibodies and 3 antibody-drug conjugates (ADCs) on the market to treat cancers and other diseases. Liquid chromatography mass spectrometry (LC–MS) provides a common tool and has been routinely used to characterize and quantify mAb and ADCs and their catabolites in discovery as well as development of antibody-related therapeutics. The major challenges for LC–MS-based analysis of mAb include limited sensitivity and lack of understanding of the nature of biotransformation and its impact on quantitation data. The analytical challenges associated with ADCs are around characterizing and quantifying the dynamically changing mixture of ADC species in circulation due to catabolism of the antibody, linker, or payload. Tissue collection and analysis, although is practically limited in the clinical research, offers direct assessment of the responsible molecular species at the site of action for the efficacy and toxicity. This review attempts to discuss LC–MS-based analytical challenges and opportunities in discovery and development of mAb and ADC therapeutics. Potential applications of the LC–MS analytical data in relation to the efficacy and toxicity of these molecular entities are also discussed here. Keywords Monoclonal antibody . Antibody-drug conjugate . LC–MS . Catabolism . Exposure–response correlation

Abbreviations Ab ADC ADA

Antibody Antibody-drug conjugate Anti-drug antibody

Cong Wei and Dian Su are first co-authors. This article is part of the Topical Collection on Molecular Drug Disposition * Wenying Jian [email protected] * Donglu Zhang [email protected] 1

Drug Metabolism & Pharmacokinetics, Vertex Pharmaceuticals Inc., 50 Northern Ave, Boston, MA 02210, USA

2

Drug Metabolism and Pharmacokinetics, Genentech, South San Francisco, CA 94080, USA

3

Bristol-Myers Squibb, Princeton, NJ 08543, USA

4

Pharmacokinetics, Dynamics, and Metabolism (PDM), Janssen Research & Development, Johnson & Johnson, 1400 McKean road, Spring House, PA 19477, USA

ADME AUC CBI CDR DAR ELISA Fab Fc HC HRMS TOF IS IV LBA LC– MS LC mAb MMAE MRM PBD PK PD QC SIL Total Ab TK

Absorption, distribution, metabolism, and excretion Area under amount or concentration versus time curve Cyclopropabenzindolone Complementary determining region Drug-to-antibody ratio Enzyme-linked immunosorbent assay Antigen binding fragment of an antibody Crystalizable fragment of an antibody Heavy chain of an antibody High-resolution mass spectrometry Time-of-flight Internal standard Intravenous dosing Ligand binding assay Liquid chromatography mass spectrometry Light chain of an antibody Monoclonal antibody Monomethyl auristatin E Multiple reaction monitoring Pyrrolo[2,1-c][1,4]benzodiazepine-dimer Pharmacokinetics Pharmacodynamics Quality control Stable isotope label Total antibody Toxicokinetics

Curr Pharmacol Rep

Introduction to mAb, ADCs, and Catabolism Nature of mAb and ADME Properties Monoclonal antibodies (mAb) and related products represent one of the most promising and fastest growing classes of therapeutic proteins. Among the five isotypes of human antibodies, namely IgA, IgD, IgE, IgG, and IgM, IgG is the most abundant and all the antibody drugs approved for clinical use have been based on this isotype. A typical IgG molecule has a molecule mass of ~ 150 kDa and is made of two heavy chains (~ 50 kDa each) and two light chains (~ 25 kDa each), which are connected by a number of disulfide bonds to form a Y-shaped molecule containing two Fab (fragment antigen binding) and one Fc (fragment crystallizable) domain [1]. IgG can be further divided into four subclasses, in decreasing abundance in human, IgG1, IgG2, IgG3, and IgG4, which are different in number and location of disulfide bonds [2]. Among them, IgG3 is not used for therapeutic application due to its shorter half-life (~ 7 days) than IgG1, IgG2, and IgG4 (~ 21 days). Over the past 30 years, the approved antibody products have evolved from murine (from mouse), chimeric (murine variable part, human constant part), humanized (human antibody with xenogenic complementary determining region (CDR)), to fully human origin, in an effort to reduce immunoresponse by human body towards foreign proteins. Anti-drug antibody (ADA) elicited by immunoresponse could impact the distribution and clearance of the therapeutic antibody in the body and, in the case of neutralizing antibody, block the binding of the therapeutic antibody to its target and therefore diminish its efficacy [3]. With recent advancement in biotechnology and protein engineering, a variety of novel protein constructs based on antibodies have been developed to achieve more effective treatment of diseases. The antibody derivatives, collectedly known as antibody products generally include the following: (1) antibody-drug conjugate (ADC): conjugates of antibody and potent cytotoxin for targeted delivery of toxin to tumor, (2) antibody fragments [4], (3) bispecific antibody [5, 6], and (4) Fc fusion proteins [7, 8]. Among the multitude of antibody derivatives, this review mainly focuses on characterization of monoclonal antibody-related molecules. Due to their large molecule size, complicated structure, and complex interactions with other molecules in the body, antibody drugs exhibit unique ADME (absorption, distribution, metabolism, and excretion) properties that are different from those of small molecule drugs [9, 10]. (1) Absorption: due to their large size and susceptibility to gut proteases, therapeutic proteins are usually administrated intravenously (iv). In recent years, there is an increased trend of subcutaneous (sc) or intramuscular (im) injection, which can improve patient compliance but also add another layer of complexity in development of the therapeutics. It is generally believed that absorption of mAb following sc or im administration most likely occurs

through convective flow of interstitial fluid to lymphatic system, though the exact mechanism has not been completely elucidated. The extent of absorption is variable and can be impacted by factors such as size and charge of the molecule, formulation, and pre-systemic proteolytic degradation. (2) Distribution: once in the circulation, distribution of mAb is restricted to vasculature with low tissue to blood ratio (usually 0.1–0.5 for mAb) [11]. Next generation antibody products of smaller size such as scFv (single chain variable fragment) and nanobody can more easily cross blood-tissue barrier and has shown better tissue penetration. The exceptional long half-life of IgGs in circulation have been attributed to its binding to FcRn [12]. IgGs circulating in the blood are constantly taken up by endothelial cells or monocytes through fluid-phase pinocytosis or receptor-mediated endocytoses. Following pinocytosis, IgGs bind to FcRn under the acidic pH in endosome (pH < 6.0) and are then transported back to the cell surface, where they are released under neutral pH environment. On the other hand, proteins that are not bound to FcRn are sorted to lysosomes for degradation. Half-life of mAb products can be optimized through Fc engineering, and next-generation protein therapeutics such as Fc-peptide fusion protein are based on strategy of half-life extension by FcRn recycling. (3) Metabolism: due to the protection of FcRn and their intrinsic stability, intermediate catabolites and fragment of mAb are not expected [13, 14]. Instead, biotransformation events such as deamidation, oxidation, glutamate/ pyroglutamate conversion, and C-terminal lysine clipping have been observed [15–17]. However, their impact on the pharmacokinetics (PK) and/or pharmacodynamics (PD) of antibody have not been thoroughly elucidated. For Fc-peptide fusion proteins, proteolytic catabolism of the peptide could significantly impact their stability and efficacy. (4) Excretion: due to their large size, mAb are not eliminated by glomeruli filtration in kidney. However, antibody products less than 60 kDa such as scFv can be excreted with high renal clearance and therefore exhibit greatly reduced half-life than mAb. Target-mediated drug disposition (TMDD), which involves endocytosis and proteolytic degradation of mAb following its binding to the cell-surface targets, is a specific and significant pathway for elimination, particularly at low-dose level when the target is not saturated. It contributes to the non-linear PK observed for some of the mAb in clinical use [18]. Immunogenicity is another key factor determining half-life, and ADA usually causes accelerated clearance of the antibody drug. Unlike small molecule drugs, for which ADME have been investigated using well-established in vitro and in vivo models, there is significant knowledge gap for ADME of antibody products. Liquid chromatography mass spectrometry (LC–MS), as an emerging analytical tool for analyzing and characterizing of therapeutic proteins in vivo, can provide valuable information regarding plasma/tissue exposure, biotransformation, immunogenicity, and target engagement for

Curr Pharmacol Rep

better prediction of PK/PD and designing of novel drug candidates.

ADC Structural Complexity and Catabolism Features ADCs consist of an antibody that targets disease antigen(s) and a payload that is connected to the antibody via a linker, and have proven to be an effective approach of selectively delivering a small molecule payload to a targeted cell. The antibody, linker, and payload of an ADC all play a large and synergistic role in modulating the efficacy and toxicity of a conjugate. Recent approval of ADCETRIS® (brentuximab vendotin), KADCYLA® (ado-trastuzumab emtansine), and BESPONSA® (inotuzumab ozogamicin) has drawn widen interest in expanding the applications of these powerful agents [19–24]. ADCs have historically been prepared as heterogeneous mixtures with a range of drug-to-antibody ratios (DARs). There are over 60 ADCs currently tested in clinical trials, and many of them utilize the random conjugation process involving either the lysine residues or sulfhydryl groups of inter-chain cysteine residues of antibodies [25]. Due to the random nature of the conjugation process, final ADC material is heterogeneous, containing vast number of species with varying DARs as well as drugs attached at various conjugation sites. Next-generation ADCs utilize a variety of new types of antibody platforms, conjugation chemistries, linkers, and drugs [25–31]. New technologies that employ site-specific conjugation of cytotoxic drugs to antibodies are being developed to overcome the issues associated with random conjugation [29, 32, 33]. Currently, three strategies are at the forefront: (1) sitespecific conjugation using a THIOMAB antibody [34, 35], (2) insertion of unnatural amino acids and selenocysteine [36, 37], and (3) enzymatic conjugation, e.g., glycotransferases and transglutaminases [38–40]. Meanwhile, additional tubulinbinders and other novel cytotoxic payloads as well as new linker chemistries have been explored to expand the mechanisms of action (MOAs) of the delivered payloads for ADC development [28, 41, 42]. For example, tubulysin [43, 44] and cryptophycin [45] have been well investigated. There is increasing interest in RNA polymerase inhibitors (e.g., α-amanitin) [46, 47] and DNA-damaging reagents, such as, pyrrolobenzodiazepine (PBD) [48–54], anthracyclines [55–57], and cyclopropabenzindolone (CBI) dimers [58]. The linker connecting the cytotoxic drug to the antibody plays a critical role in the stability and release of the ADC. Several ADC linker types (hydrazone, disulfide, peptide, glucuronide, noncleavable linker) have a corresponding disparate mechanism of release (acid, glutathione, protease, glucuronidase, antibody catabolism), and each typically releases a unique metabolite [73–77]. The mode of release of the active payload from these linkers differs markedly in vivo. Recently, peptide-based linkers (cleavable and noncleavable) have been used routinely because they exhibit higher plasma stability and improved

activity [76, 77]. Overall, linker stability has been improved significantly through the creation of enzymatically cleavable and non-cleavable linkers over the chemically labile hydrazone and certain disulfide linkers used in the first-generation ADC [79]. Disulfide linker chemistry has also been improved significantly with incorporation of protection groups and short linkers [80]. Next generation ADCs are expected to bring new treatment opportunities but also pose new challenges in drug optimization, characterization, and bioanalysis. An ideal ADC would remain intact in circulation prior to internalization and efficiently release cytotoxic payload in the target cell for maximum efficacy with minimum toxicity. However, biotransformation including undesirable drug release or inactivation via linker deconjugation and payload metabolism can occur while in circulation and therefore may compromise ADC efficacy and safety (Fig. 1) [59, 60]. In addition, catabolism such as generation of peptide fragments or linker-drug fragments can also lead to additional DAR modifications and increased complexity of total ADCs in circulation [61–63]. Deconjugation via chemical decoupling of the covalent linker and enzymatic cleavage of linker are common mechanisms of drug release in plasma. For example, THIOMAB ADCs via maleimide and disulfide linkage could undergo linker deconjugation via maleimide exchange and disulfide exchange, respectively, usually resulting in adduct formation of the deconjugated cysteine site with cysteine and glutathione in circulation (Fig. 1a) [15, 62, 64–66]. In addition, enzymatic metabolism (e.g., ester- and amide-bond hydrolysis) can occur with certain payloads in circulation and thus affect ADC PK, efficacy, and toxicity profiles (Fig. 1b). For example, ester hydrolysis was observed with a spliceostatin ADC [47] and a tubulysin ADC [67]. The acetate was not required for the activity of spliceostatin; therefore, the ester hydrolysis did not cause the loss of ADC potency. However, the loss of acetate in tubulysin ADC resulted in a significant loss of potency as the acetate is critical for payload activity [67]. Metabolism of the macrocycle was observed in cryptophycin C52 (LY355703)-ADC in mice in circulation via amide and ester hydrolysis (Fig. 1b), which also reduced the ADC potency [68, 69]. In the case of a CBI-PBD heterodimer, the prodrug functional group phosphate was observed to be removed by the phosphatase in plasma in circulation, followed by the loss of chlorine. The dephosphorylation metabolic pathway resulted in transforming the CBI portion into its active form (data not shown) (Fig. 1b). The complexity of the new generation ADC biotransformation in vivo poses challenges for bioanalytical analysis [59, 70, 71].

ADC PK and Payload Release The PK profile of an antibody is characterized by low clearance, small volume of distribution, long circulating half-life (days), and target or non-target tissue distribution. The

Curr Pharmacol Rep Fig. 1 Major ADC biotransformation pathways. a Linker deconjugation via maleimide exchange and disulfide exchange, usually resulting in adduct formation of the deconjugated site with cysteine and glutathione in circulation. b Enzymatic payload metabolism, which may or may not impact the potency depending on the function of the lost part of the payload. Loss of potency would cause reduction of DAR values. Red: the portion of payload cleaved from the ADC due to metabolism; Blue: the portion of payload retained on the ADC following metabolism. CBI, cyclopropabenzindolone

a

-LD

s Cys, GSH

-LD

o

R

S

N

o

MaleimideLinker

Payload

Cys, GSH

R = H, CH3

S

Disulfide Linker

Payload

Deconjugation (-LD)

s Cys

s GSH

b

comparison of PK and dosing properties of the antibody, ADC, as well as small molecule are listed in Table 1. PK profile of typical ADC is mainly dictated by the antibody. The long half-life of IgGs in circulation have been attributed to FcRn-recycling through its binding to FcRn that prevents the antibody entering into lysosomes for proteolytic degradation [12]. Deconjugation, catabolism together with low clearance of an ADC antibody creates a complex dynamics of various ADC species (conjugated antibodies with various DAR, conjugated payload, free payload etc); each has its own PK profile. An ADC is designed to prevent early payload release to circulation. Consequently, the circulating payload concentration is normally very low and rarely contributes to pharmacological activity. ADCs can be viewed as prodrugs for which circulating concentrations provide a reservoir for the corresponding local active catabolite (payload). Following internalization of an ADC, the payload is released into cells at a site of action to exert its biological activities (e.g., in tumor cells). The associated rate and extent of payload delivery is dependent on both tumor properties (such as antigen type, antigen expression and turnover rate, tumor type) and ADC characteristics including uptake, internalization, and biochemical transformation (proteolytic degradation of antibody, linker

cleavage, and immolation to release payload). The levels of a given payload present at the site of action are determined by the amount of conjugate entering the tissue, the local ADC catabolism rate, and payload tissue-retention properties. Complex ADC structures plus complicated disposition properties often pose great challenges to characterization and quantitation of released payload and other species of ADC-related molecules.

Challenges in Characterization and Quantification of mAb and ADC by LC–MS Application of LC–MS to Characterization and Quantification of mAb and ADC LC–MS analysis has been heavily involved in characterization and quantification of mAb and ADC. Both unit-resolution mass spectrometry (e.g., triple-quadrupole instrument) and high-resolution mass spectrometry (HRMS) have been utilized for this purpose (Table 2). Quantitative analysis is typically performed by LC-triple-quadrupole MS (LC–MS/MS) using multiple reaction monitoring (MRM) by monitoring

Curr Pharmacol Rep Table 1 Pharmacokinetic comparison of small molecule, monoclonal antibody, and ADC

Parameters

SM

mAb

ADC

Size (Da) Active species

~ 500 Parent

~ 150,000 Parent

~ 150,000 Catabolite

Dose (mg/kg)

1–100

0.3–30

0.3–30 (1–100 μg payload)

Dosing route T1/2

PO Hours

IV Days–weeks

IV Days–weeks

Metabolism/catabolism

Cytochrome P450 & others

Proteolysis

Proteolysis

Vd (parent)

Small-large

Small

Small

specific fragmentation from selected precursor ion to product ion, which affords higher sensitivity but limited resolution (unit mass resolution normally with 2 K resolving power). Comparatively, LC–HRMS provides higher resolution with full scan (above 10 K and up to 450 K resolving power) and also offers distinct advantages in that it requires minimal optimization of the acquisition method upfront and can collect information-rich files for post-acquisition data mining. Thus, characterization of mAb and ADC as well as their catabolites and their subspecies metabolites are usually performed by LC–HRMS. In addition, LC–HRMS can also be operated in full scan mode or product ion scan mode [also known as parallel reaction monitoring (PRM)] for selective quantitation of small molecules or surrogate peptides though it is not done routinely. Recently, HRMS has emerged as an alternative tool to quantify intact mAb and intact protein in the full-scan mode [72], which may have the potential to quantify large molecule subspecies of ADC. LC–HRMS can also gain sensitivity by increasing signal-to-noise (S/N) ratios with elimination of isobaric interferences that it has been recruited to perform quantitative analysis on small molecule subspecies of ADC (e.g., unconjugated payload) [73]. While ligand-binding assays (LBA) are the current standard for quantitation of therapeutic antibodies [74]. LC–MS Table 2 ADC

has become an alternative or complementary approach [75]. The nature of mass-based measurement makes LC–MS a powerful tool in characterizing biotransformation of therapeutic antibodies and to measure different variant forms. LC–MS plays a more significant role in ADC bioanalysis and characterization [59]. Immuno-affinity capture-LC–MS, the ligandbinding and LC–MS hybrid approach combining the strength of both technologies, has become a standard methodology in LC–MS applications in analyzing and characterizing antibodies and ADCs [59, 76–78]. The most common approach in LC–MS quantitation of protein therapeutics is through enzymatic digestion followed by LC–MS/MS analysis of one or multiple generated surrogate peptides (or signature peptides) on a triple-quadrupole mass spectrometer [79–81]. It is the major platform for quantitative LC–MS analysis of mAb and the antibody part of ADC. Many common challenges are shared between the two different types of analytes such as lack of sensitivity, matrix interference, and high variability. They will be discussed more extensively in the following section (see the BmAb Quantification by LC–MS and Associated Challenges^ section) for mAb quantification, and it should be noted that these issues and coping strategies are also applicable for ADC.

Applications of different mass spectrometry instruments (triple-quadrupole vs. HRMS) on characterization and quantification of mAb and

Applications

Antibody

Antibody-drug conjugate

Unit mass spectrometry (triple-quadrupole)

High-resolution mass spectrometry

mAb quantification

Yes, via surrogate peptide

Characterization of mAb catabolism Total Ab quantification for ADC

No

Possible by full-scan HRMS of intact molecule and surrogate peptide, but not routine Yes

Yes, via surrogate peptide

Possible by full-scan HRMS of surrogate peptide, but not routine

Yes, via surrogate peptide Yes Yes

Possible by full-scan HRMS of surrogate peptide, but not routine Possible by full-scan HRMS, but not routine Possible by full-scan HRMS, but not routine

No No

Yes Yes

Conjugated Ab quantification Conjugated payload quantification Unconjugated payload quantification Characterization of DAR Characterization of payload metabolism

Curr Pharmacol Rep

Bottom-up method has another drawback that the selected signature peptides may not represent the whole protein molecule. The analysis of intact proteins, in a top-down fashion, in either MS/MS or full-scan high-resolution mass spectrometry (HRMS) mode on time-of-flight (TOF) or orbit-trap mass spectrometers, could maintain the information of the entire protein and monitor its biotransformation [82]. While early examples are limited to small proteins < 10–20 KDa with limited sensitivities (20–500 ng/ml) [83–85], recent advances in immuno-affinity capture-LC–MS analysis of larger protein and intact mAb have shown improved sensitivity to 50– 100 ng/mL [72, 86, 87] equivalent to that achieved in the bottom-up approach. Technology wise, a middle-down approach by reducing mAb to its subunits (e.g., F(ab) and Fc) has seen improved sensitivity for quantitation and characterization of intact proteins [88–90]. Sequential immunoenrichment at both protein and peptide levels [91, 92], micro-, nano-, capillary- and multidimensional chromatography [93–95], are in the tool box to enhance the capabilities of analyzing and characterizing antibodies and ADCs by LC– MS. There is the industry-wide discussion on bioanalytical method validation for quantitation of protein therapeutics using hybrid immuno-affinity capture-LC–MS [75, 96, 97]. The essence of the recommendation is to combine the requirements of validations for small molecules by chromatography methods and for biologics by ligand-binding assays [98–100] while there are currently no guidance from health authorities on bioanalytical method validation for protein therapeutics by LC–MS.

Monoclonal Antibody (mAb) mAb Quantification by LC–MS and Associated Challenges LBA such as ELISA (enzyme-linked immunosorbent assay) has the advantage of being highly sensitive and efficient and has been the gold standard for quantitation of large molecules in biological samples. On the other hand, it may suffer from limitations such as cross-reactivity, requirement for highly specific antibody, and interference from other components in the samples. In the past decade, LC–MS has emerged as a complementary analytical platform for bioanalysis of protein therapeutic in support of drug discovery and development because of its unique advantages such as high specificity, resistance to interferences, less stringent requirement for reagents, and potential for multiplexed analysis for multiple analytes. General workflow of LC–MS analysis of antibody drugs involves enzymatic digestion (usually trypsin) of the protein, followed by LC–MRM analysis of selected peptides from representative regions as surrogate peptides [101]. Tryptic peptides of conservative sequence from constant regions of light chain or heavy chain have been commonly used

as surrogate peptides for quantitation of mAb in samples from preclinical species [81]. For clinical samples, unique peptides from variable region (usually CDR) are usually monitored to avoid interference from endogenous human IgGs. Choice of sample preparation depends on the required sensitivity and biological matrix. Protein precipitation followed by digestion of the pellet, which contains the precipitated mAb, a process known as pellet digestion, has been widely adopted due to its ease of operation, but may have limited sensitivity [102]. When better sensitivity is needed, immuno-affinity capture using immobilized anti-human Fc antibody can provide effective and selective clean-up of human mAb from animal plasma/tissue homogenate. For human sample, anti-idiotype antibody against epitope in CDR needs to be employed to avoid pulling down endogenous human IgGs, which may interfere with the detection. Alternatively, the protein target of the therapeutic antibody can be used as capture reagent to purify the antibody from the biological samples. The unique advantages of using LC–MS for quantitation of mAb products in biological samples have been exhibited in a few areas: (1) Discovery research [103]: at discovery stage when the structures of the drug candidates are not determined or optimized, there may be lack of specific antibody to be used for LBA. In contrast, LC–MS assays do not require special reagent, or just require a generic anti-human Fc antibody for pulling down human mAb from animal samples, which is readily commercially available, and therefore is fast to develop, usually taking a couple of weeks. In comparison, developing a specific antibody for use in LBA may take a few months, which is not compatible with the high paced discovery research. The sequence difference human and animal naturally afford the selectivity when unique human surrogate peptides are monitored. In addition, LC–MS assays can be configured in a multiplexed fashion by monitoring surrogate peptides from different mAb candidates, making it possible for cassette dosing for improved efficiency [104]. (2) Tissue sample analysis: measuring the concentration of the therapeutics at site of action can provide valuable information for better understanding of the mechanism of the drug and predicting PK/PD relationship. However, plasma/serum concentration has been usually used as surrogate due to the difficulty to measure tissue concentration. It is particularly challenging to develop LBA assay for tissue samples due to nonspecific binding and endogenous interference. In comparison, LC– MS assays are less sensitive to matrix interference and have been explored for tissue sample analysis for understanding tissue penetration of different mAb therapeutics [105, 106]. (3) Elucidating free/total drug concentrations: for therapeutics with soluble target or in the case when ADA is formed, it is relevant to differentiate free and total drug concentration, as binding may block the activity or alter the PK. Depending on the reagent and assay conditions, LBA may measure free or total analyte. However, if there is lack of appropriate tests to

Curr Pharmacol Rep

characterize the method specificity, it may not be completely clear what is being measured. In comparison, an LC–MS assay based on pellet digestion is clearly to measure total drug concentration. A divergence between the LBA data and total LC–MS data may indicate presence of ADA [107, 108]. LC– MS assay can also be configured to measure free drug when the appropriate antibody is used for immuno-affinity capture. Recently, there is report showing that ADA-bound drug can be directly measured by LC–MS assay after affinity capture of ADA-drug complex by protein G [109]. In addition, novel approaches to directly detect ADA by LC–MS have been explored and showed the advantage of being free from interference of high concentration of drugs in the samples, a common problem for LBA-based ADA assay [110, 111]. (4) Next generation therapeutics such as bispecific mAb products or Fc fusion proteins: there are usually more than one pharmacologically active moieties on these types of molecules. In these cases, an LC–MS assay with suitable surrogate peptides from each of the active region can efficiently and specifically measure the exposure of each relevant part [112]. In addition, the peptide part of an Fc-peptide fusion protein is usually prone to proteolysis, leading to loss of activity. LC–MS can readily differentiate unchanged form from proteolytic catabolites, whereas LBA may detect both and give overestimated concentration of active moieties [87]. Significant challenges remain for LC–MS-based bioanalysis of large molecules [113, 114]. First of all, LC– MS is currently less sensitive than LBA assays, which is a hurdle for its use when dose or exposure is low, such as first-in-human clinical study or for molecules with high clearance or poor stability. In order to achieve desired sensitivity, extensive and effective sample preparation such as surfactantaided precipitation/on-pellet digestion (SOD) can be applied to eliminate or mitigate matrix interference [115]. In the innovative SOD approach, surfactant treatment before the precipitation for pellet digestion substantially increased peptide recovery and reproducibility from plasma and tissue samples. It is believed that surfactant permits extensive denaturation/reduction/alkylation of proteins and inactivation of endogenous protease inhibitors, as well as facilitates removal of matrix components [115]. When suitable reagents such as antibody against the analyte are available, immuno-affinity capture can specifically purify targeted analyte from complex biological matrix. Particularly, it has been shown that combination of immuno-affinity capture at protein level and peptide level can significantly boost sensitivity of the assay to achieve pg/ mL LLOQ for endogenous biomarker proteins, though this approach has not been applied for therapeutic mAb quantification [91]. The need for better ionization efficiency for improved sensitivity has pushed the application of micro- and nanoscale LC. Though with limited application in routine bioanalytical work due to sophisticated instrumentation, nano-LC has been shown to quantify mAb in tissue samples

and demonstrated its potential for ultra-sensitive detection [106]. It is expected that continued advancements in sample preparation techniques and instrumentation will bring improvement in assay sensitivity. Secondly, LC–MS assays usually involve multiple complicated steps such as affinity-capture, digestion, and LC–MS analysis, which not only increase the length of analysis but also potentially introduce variabilities. Novel approaches such as microwave-assisted digestions, high efficient trypsin, automated liquid handler for samples preparation, and ultra-high-performance liquid chromatography (UPLC) are expected to improve the throughput and robustness of LC–MS assays. Use of internal standard (IS) can be incorporated into LC–MS-based quantitation assay, and well-designed IS can effectively compensate analyte loss and matrix effects to provide more accurate and robust quantitation. The choice of IS strategy can significantly impact the performance of the assay. Extensive research has been done to compare stable isotope-labeled (SIL) IS at peptide level (only compensate for matrix effects), SIL peptide with extended amino acids on each side (track both digestion and matrix effects), and SIL protein (track the whole sample preparation procedure). The data showed that IS at protein level provides best assay performance while IS at peptide level with or without extended amino acids level could result in significant bias in quantitation [116–118]. While SIL peptides can be chemically synthesized, SIL protein IS is usually generated by replacing natural (Blight^) amino acids in cell culture growth medium with stable isotope labeled (Bheavy^), a process known as stable isotope labeling with amino acids in cell culture (SILAC). It may require substantial resources and relatively long time to produce SIL protein IS by SILAC. A relatively more accessible alternative is to use Buniversal^ stable isotope-labeled mAb that are commercially available. These SIL mAbs share common sequences to constant regions of human IgGs and therefore can serve as SIL IS when surrogate peptides are selected from those regions [117]. Likewise, the criteria and consideration for choosing calibration standard are very similar to those employed for IS. Intact protein should be chosen over surrogate peptide because analyte loss during sample preparation procedure cannot be compensated for by peptide reference standard. In addition, it has been shown that evaluation of peptide stability in the matrix before surrogate peptide is critical and use of unstable peptide would lead to biased quantitation. It would be useful to use at least two surrogate peptides to gauge the method reliability [118]. Finally, an intrinsic limitation of the surrogate peptide-based Bbottom-up^ approach is that it may be misleading to represent a complex protein using small fraction of it. Biotransformation to the surrogate peptide or other part of the protein may cause biases in the measured concentrations, particularly if there is lack of understanding of the nature of biotransformation and of its impact on activity and stability. Recently, intact analysis using full-scan high-resolution MS

Curr Pharmacol Rep

without digestion has emerged as a novel trend for protein bioanalysis [82]. There have been reports showing the effectiveness of this approach to quantify mAb at intact level in biological samples [72, 86]. It should be noted that intact analysis requires thorough understanding of protein biotransformation so that it is clear what is being measured. For example, some in vivo modification, such as C-terminal Lys clipping of mAb, may not impact the function of the protein and therefore the Lys clipped forms should be counted for active intact concentration. Characterization of Antibody Biotransformation by LC–MS and Associated Challenges For a long time, the drug metabolism research has been reserved for small molecule therapeutics. For biotherapeutics such as mAb, extensive biotransformation studies are generally not warranted because mAb are intrinsically stable and their catabolites, usually peptides and amino acids, are not considered pharmacological active or toxic. However, in recent years, with the rapid expansion of variety of mAb-based therapeutics, such as ADC and Fc fusion proteins, there is increased need to understand catabolism of protein therapeutics [13, 14]. Biotransformation of those protein drugs could result in toxicity, reduced stability/activity, or undesired immunogenicity. In addition, identification of catabolic labile spots could facilitate the design of more stable structure for improved PK properties. The view from regulatory authorities has also been evolving. In the EMA (European Medicine Agency)’s guideline on clinical investigation of the pharmacokinetics of therapeutic proteins in 2007, it was stated that BThe need for, and the feasibility of specific studies of the route of elimination and metabolism (e.g. microsomal, whole cell or tissue homogenate studies) and identification of metabolites in vitro should be considered and discussed on a caseby-case basis^ [119]. Due to its ability to elucidate structure information, MS has been the instrument-of-choice for catabolism studies. For mAb products, both enzymatic digestion-based Bbottom-up^ and intact analysis-based Btop-down^ approaches have been explored and they showed complementary capability in structure elucidation for large protein therapeutics. BBottom-up^ approach monitoring peptides generated by enzymatic digestion has been primarily used to investigate modification at amino acid level, such as deamidation, oxidation, Asp isomerization, pyroglutamic acid formation, and C-terminal Lys clipping [16, 17]. In one of few reports of in vivo biotransformation studies of mAb, multiple potential biotransformation attributes were monitored for an IgG mAb in Cynomolgus monkeys and it was shown that oxidation and C-terminal clipping did not change overtime, while deamidation increased linearly over a period of 7 weeks [15]. In addition, glycoforms can be monitored at peptide level, and in this study, it showed

that the levels of major glycoforms remained relatively constant [15]. Biotransformation at certain position of mAb could have significant impact on its function. It has been demonstrated that deamidation of trastuzumab, an mAb against human epidermal growth factor receptor-2 (HER2) for treatment of breast cancer, at its CDR region could lead to a loss of recognition to its target. An LC–MS/MS assay has been developed to specifically quantify the level of unchanged, deamidated, and the intermediate for clearly understanding the dynamic relationship of each form and the implication on therapeutic efficacy [120]. Bottom-up-based approach has the benefit of being highly sensitive and selective. However, digesting the protein into peptides significantly increases the complex of the samples while eliminating the context of the sequences. It does not reveal high-level structure information such as whether the different subunits remain connected. When it comes to proteolysis, a common biotransformation for Fc-peptide fusion proteins, peptide mapping is not a practical or efficient approach, because peptides derived from proteolytic catabolites may not be detectable under the employed LC–MS condition or not differentiable from peptides generated by enzymatic digestion. This is the reason why intact analysis has been gaining popularity for its application for in vivo sample analysis. It is highly challenging to analyze large proteins at intact level, due to their large size and complex nature, not to mention from highly complicated environment such as plasma. Recent evolution in sample preparation techniques and instrumentation has made it possible, which usually involves immuno-affinity capture of the targeted protein from biological matrix followed by high-resolution MS analysis. A biotransformation study of Fc-FGF21 (fibroblast growth factor 21) fusion proteins utilizing anti-human Fc capture and MALDI (matrix-assisted laser desorption ionization)-TOF MS analysis revealed proteolytic sites on the fused FGF21, which enabled development of more stable drug candidates by mutating the impacted amino acid [121, 122]. Recently, a workflow for simultaneous intact quantitation and catabolite identification has been proposed [72]. In one example of that workflow, Fc-peptide fusion proteins are immuno-affinity captured by anti-human Fc antibody, eluted from immobilized magnetic beads, and subjected to LC-full scan HRMS analysis on triple TOF instrument. The deconvoluted full MS spectra contain rich information not only of the intact parent protein that can be used for quantitation, but also that of catabolites for elucidation of proteolytic sites on the fused peptide [87]. The simultaneous acquisition of quantitative and qualitive data at intact data provide in-depth understanding of the in vivo fate of the fusion protein. A major challenge of intact analysis is its limited sensitivity for large proteins, because of their low ionization efficiency and dilution of signal among multiple charging states. An effective approach to overcome this limitation is Bmiddle-

Curr Pharmacol Rep

down^ analysis by breaking the molecule into relatively smaller Bintact^ pieces. For example, in a study to quantify a human IgG in monkey serum, a limited Lys-C digestion was utilized to cleave a lysine residue in the hinge region to release Fab fragments, which was subjected to LC–HRMS analysis [89]. Nevertheless, lack of sensitivity is still a major hurdle for intact analysis and breakthroughs in sample preparation techniques and instrumentation are needed to enable more effective application of this approach.

Antibody-Drug Conjugate (ADC) Characterization and quantification of ADC by LC–MS from biological matrices are complicated given the complexity of ADC molecule. The concentration versus time profile is used to calculate PK parameters for the therapeutic and explore potential relationships with safety and efficacy. An ADC therapeutic in vivo is typically a complex and dynamically changing mixture due to biotransformation, differing clearance rates associated with different DAR species, or a combination of these processes [59, 93]. In this context, even the existing PK language for Btherapeutic concentration^ versus time becomes ambiguous. Moreover, the reference standard in the calibration curve samples may no longer represent the analytes present in the study samples in vivo, presenting a unique challenge for quantitative assays. Therefore, bioanalysis of ADC requires a clear definition of each analyte within the in vivo mixture to be measured as well as a corresponding strategy [59]. Despite improvement in ADC design and synthesis, payload deconjugation still occurs following ADC administration, leading to an increase in unconjugated payload levels and changes in the ADC composition (i.e., the DAR distribution) [123]. The concentrations of total antibody (total Ab) may help determine pharmacokinetic (PK) and toxicokinetic (TK) profiles of the carrier antibody during ADC drug development. The quantitative measurement of the conjugated Ab and the conjugated payloads that are attached to the antibody in vivo is considered to be important for evaluation of the ADC efficacy and could be helpful to assess drug (payload) exposure at the target site. Either conjugated Ab or conjugated payload represents the remaining active components available for targeted drug delivery. In addition, quantification of unconjugated payload in circulation may be useful for safety and toxicity investigations. Furthermore, determination of changes in DAR distribution and average DAR values is critical for providing stability profile of ADC and integral assessment of an ADC [59, 62, 90, 124]. Total Antibody Total mAb in ADC bioanalysis includes the antibody conjugated to the payload (conjugated mAb) and those naked mAb

(unconjugated mAb). The mAb part of ADC structure is usually IgG1, IgG2, or IgG4 that shares characteristics with most mAbs in clinical use. The total mAb profile is an important aspect of the overall PK assessment of ADC [70, 125]. Total mAb has been traditionally measured by LBA using antigen or anti-idiotype antibody as reagents [125]. For non-clinical studies, anti-human IgG antibodies have been used for the total mAb assay as well as by LBA. Immuno-affinity capture LC–MS/MS has been increasingly used as an alternative to LBA for protein and antibody quantification [79, 81, 126]. This alternative total Ab assay approach is by using immuno-affinity capture LC–MS/MS followed by enzymatic digestion. A surrogate peptide (or signature peptide) in the heavy chain CDR or Fc region can be used for quantification [100, 125]. Ideally, a corresponding stable-isotope-labeled (SIL) mAb would be used in a total mAb assay, as the IS to track ADC analyte during the entire process of sample preparation, including immuno-affinity capture, trypsin digestion, and LC– MS/MS analysis [100]. There are many IS choices that can be successfully used in a quantitative protein or mAb assay. Trade-offs in potential benefits, cost, and availability must be weighed and the ultimate effectiveness of the IS should be verified during method validation [75]. For non-clinical studies using generic total mAb assay via LC–MS/MS method, the stable isotope-labeled human monoclonal antibody SILu™Mab (Sigma) is usually used as the generic IS for various ADCs for total mAb quantification. However, the same SIL IS is not applicable to clinical assays because the immuno-affinity capture for human samples has to be conducted by using anti-idiotype antibody which does not recognize the SILu™Mab. In the cases where a stable-isotope labeled mAb is not available for the analysis of the ADC of interest, a SIL signature peptide with a few extended amino acids on each of N- and C-terminus would be used as IS and added into the samples prior to trypsin digestion to track the analyte during digestion process, LC separation, and ionization and detection by MS. The exact SIL peptide may also be used as IS, which can only track the LC–MS analysis. It has also been shown that during the immuno-affinity capture where no IS was added, robust performance of standard curves and quality controls (QCs) was consistently achieved [100]. For total mAb assay using anti-idiotype capture, soluble target in circulation may block the binding sites on the ADC, thus when anti-idiotype mAb is used for immunoaffinity capture, it may not be able to capture all the ADC, leading to reduced recovery if the assay is intended to measure the total mAb concentrations. In preclinical species, the soluble target may not be cross-reactive to the ADC, or the level of soluble target may be too low relative to the ADC level to have a significant impact on the measurement [100]. However, the levels of soluble target in the human populations are projected to be high and variable [100].

Curr Pharmacol Rep

Biotransformation may happen on the mAbs in vivo. Isomerization of aspartic acid and deamidation of asparagine are two common amino acid modifications that are of particular concern, especially if either of the amino acids is located in the sequences of the signature peptides which would bring challenges on total mAb quantification by LC–MS. Detection of naïve and modified forms of proteolytic peptides are needed for total Ab quantification if the signature peptide contains the biotransformation sites. Furthermore, subdomain monitoring and multiple signature peptides at different areas of the mAb should be used to understand biotransformation at different regions of the mAb. These data can then be pieced together to provide a complete picture of the biotransformation of the mAb. Conjugated Antibody and Conjugated Payload Conjugated mAb is defined as mAb conjugated with at least one payload. Measurement of conjugated mAb is often employed for obtaining both preclinical and clinical PK profiles of ADC although it is not known whether conjugated mAb or conjugated payload correlates with efficacy and safety [100, 127]. When conjugated payload assays are unavailable with non-cleavable linkers, it has been suggested that DARsensitive conjugated mAb assays can be used to monitor in vivo DAR change [128]. While LBA is widely applied for conjugated mAb quantification by using anti-payload mAb as the primary mAb, hybrid immuno-affinity capture LC–MS/MS analysis may also play a role in conjugated mAb quantification. For this approach, the samples can be processed with anti-payload antibody to achieve immuno-affinity capture of conjugated mAb followed by enzymatic (e.g., trypsin) digestion and a signature peptide is monitored for quantification of the conjugated mAb. A peptide in the human Fc region or in the heavy chain CDR can be used as the signature peptide for a non-clinical assay, while a signature peptide in the heavy chain CDR is needed for a clinical assay. The caveat of this approach is that the anti-payload antibody may preferentially bind to the unconjugated payload in the sample; thus, relatively large excess amount of anti-payload antibody is usually used to ensure the capture of all conjugated mAb. One of the concerns for quantification of ADC is that the calibration curve prepared using the dosed ADC as reference standard may not fully represent the analytes in the study samples over the time course of PK measurement, which is related to the in vivo DAR change. As aforementioned, the ADC in vivo is a mixture of ADC species of different DARs, typically 0 through 8 in the random lysine-conjugated ADCs [59, 70, 125]. Unfortunately, most often, the individual DAR1–8 ADC reference standards are unavailable and only the drug substance with an average DAR of 3 to 4 is used as the reference standard. The consequence for the quantitative

bioanalysis is that the distribution of analyte species with different DAR values in the incurred samples is different from that in the standards [100]. While the conjugated payload measurement will be sensitive to changes in DAR (i.e., DAR-proportional), the conjugated mAb assay measures the antibody portion of ADCs and is theoretically DAR independent [59, 70, 100, 125]. There was one case reporting that for the random-conjugated ADC of interest, the conjugated mAb LBA using anti-payload as capture reagents was DAR sensitive. In contrast, the hybrid conjugated mAb LC–MS assays using anti-payload capture in the cartridge format were proven to be DAR-insensitive [100]. Conjugated payload is defined as payload conjugated to the antibody. The conjugated payload represents the active ADC drug component and is the preferred analyte when possible in a hybrid immuno-affinity capture LC–MS assay [100]. The conjugated payload assay offers direct and sensitive measurement of the bioactive cytotoxic payload molecules linked to the mAb thus maybe providing an assessment of payload exposure at the target site, e.g., in tumor tissues. It has been suggested that conjugated payload assay might be a better analyte in the drug development stage to support regulated preclinical and clinical studies with a focus on efficacy correlation [127]. The conjugated payload assay allows accurate quantification of conjugated payload for the ADC having varying DAR [100]. There is also an increasing interest in measuring the conjugated payload to define the PK of the ADCs [129]. The feature of the linker moiety largely determines the sample processing strategy for conjugated payload bioanalysis. If the linker is enzymatically cleavable (e.g., dipeptide-based cleavable linker), a lysosomal enzyme such as cathepsin B is able to specifically cleave the linker to release the payload for LC–MS detection, following antiidiotype mAb immuno-affinity capture of ADC from matrices. If the linker is a non-cleavable linker which enzyme is not able to cleave the payload off the linker, then following the anti-idiotype mAb capture of ADC from matrices, the protease (e.g., trypsin) digestion on the antibody is to use and the whole piece of peptide-linker-conjugated payload is the surrogate analyte to monitor by LC–MS/MS. An anti-idiotype mAb capture-based LC–MS/MS assay enables the measurement of the payload still conjugated to the mAb. Nevertheless, if using an anti-payload mAb as capture reagent, one could potentially measure various types of payload molecules in the sample, including unconjugated payload, payload conjugated to the mAb, payload attached to the linker, and any catabolite of the mAb with payload attached [129]. In addition, Protein A or Protein G can be used as generic capture reagent, and a Protein A capture LC–MS/MS assay with papain (a cysteine protease) cleavage for conjugated-payload quantification of the valine-citrulline-linked MMAE ADC has recently been reported [130]. Others have reported measuring

Curr Pharmacol Rep

payload in plasma by chemical cleavage of a labile linker [99]. Several challenges exist on the quantification of conjugated payload by LC–MS. First, when the linker is not enzymatically cleavable, the reference standard may not readily be available or requires additional synthesis since the reference standard would be the payload conjugated with the peptide that is enzymatically cleaved from the mAb. In the case of noncleavable linkers, the conjugated payload approach may not be suitable or be very complicated for lysine- or reduced interchain cysteine-linked ADCs. The conjugated payload assay also needs to include the corresponding IS which may also require additional synthesis. Second, the payload molecule and/or the linker may undergo metabolism without deconjugation from the mAb in circulation, which would result in different analytes to monitor by LC–MS/MS. Furthermore, the presence of soluble target may need to be taken into account in conjugated payload assay in human plasma as the target may block binding of the capture antibody [100]. Unconjugated Payload and the Destiny of Released Free Payload In Vivo The Bunconjugated payload^ includes the payload deconjugated in the plasma or tumor tissue during the dosing time course and the payload present in the predose starting material/formulation which is in trivial amount. The levels of the unconjugated payload would usually be measured and reported in PK and TK studies to correlate with toxicity. The bioanalysis of unconjugated payload is often similar to most of the small molecule bioanalysis with LC–MS. It is worth noting that due to the presence of various proteases in matrix, unconjugated payload levels may be artificially elevated during sample preparation should additional deconjugation be triggered by proteases. Therefore, one consideration is to add protease inhibitor cocktails prior to sample extraction or perform the sample extraction in an ice water bath to prevent or minimize payload deconjugation from ADC in sample preparation. Sensitivity is one of the challenges for unconjugated payload quantification as unconjugated payload often present at very low level in the samples. The payloads usually have higher molecular weight (> 700 Da) and are more hydrophobic compared to a conventional small molecule analyte, presenting additional analytical challenges. For example, the LLOQ of unconjugated payload DM1 in human serum was reported as 0.20 ng/mL for clinical samples by a validated bioanalytical assay using online SPE coupled with LCtriple-quadruple mass spectrometry [131]. However, the unconjugated payload DM1 could not be measured in clinical patient samples with 0.3 mg/kg ADC intravenous administration every 3 weeks, as all DM1 signal was below the LLOQ of

the method [131]. In another study, Wei et al. described the development of a sensitive and selective LC–MS/MS method for the quantification of unconjugated DM4 (another maytansinoid derivative with a thiol group, thiol-DM4) in the plasma of Cynomolgus monkey and Sprague-Dawley rat, with LLOQ of 0.50 ng/mL [132]. However, the unconjugated payload DM4 concentrations were only measured up to 24 h in a 3-week time-course study in Cynomolgus monkeys [132]. Another challenge for quantification of unconjugated payload is that the analytes sometimes need to be pretreated or derivatized before the LC–MS/MS analysis. For example, the unconjugated linker-payload of DM4 contains a disulfide bond. The payload DM4 in the samples was released by reduction of the disulfide bond or by disulfide exchange with other thiolcontaining molecules in plasma, resulting in the generation of thiol-DM4 as the analyte for quantification [132]. When payload is deconjugated from ADC in vivo, the released payload may also covalently bind to matrix proteins and form adducts with endogenous proteins. Several studies have identified an albumin-linker-payload adduct forming during in vivo or ex vivo plasma studies of maleimidecontaining ADCs. A work flow for adduct identification and quantification has been proposed [133]. To identify and characterize the unconjugated payload-protein adduct, the ADC would be removed/depleted from the matrix sample by immunoprecipitation using antigen or anti-idiotype antibody, and the ADC-depleted sample is then further immuno-affinity captured with anti-payload Ab followed by LC-full scan HRMS analysis on the eluted samples. The deconvoluted full MS spectra would illustrate the major intact linker-payloadprotein adduct and potentially any other catabolites/metabolites. To quantify how much of the unconjugated payload has formed the protein adduct, the anti-payload captured sample would be further digested with proteases (e.g., cathepsin B) to release the payload from the peptide adduct followed by LC– MS/MS payload quantification. This would allow for the calculation of the molar amount of payload in the adducts. Challenges remain to characterize and quantify the destiny of the released payload in that certain critical reagent (i.e., anti-payload Ab) may not be readily available, and when the linker is not cleavable, payload binding on the adduct may not be released for quantification analysis. When directly analyzing the intact payload-protein adduct in the ADC-depleted and anti-payload-captured samples, limited sensitivity of LC–MS analysis for large molecule is a challenge. ADC Biotransformation Biotransformation data provides critical mechanistic insights into understanding of the stability and biological activity of ADCs in vivo for improvements in drug design. Affinity capture capillary LC–MS was specifically developed for

Curr Pharmacol Rep

characterization of ADCs, DAR distribution and structural change, to gain insights into the mechanisms of in vivo biotransformation [59, 90, 124]. Relative ratios of individual ADC species were obtained based on their peak areas in the deconvoluted mass spectra. Average (avg) DAR was thus estimated with the calculation shown below. Avg DAR ¼ Σð%peak area  No:of conjugated drugsÞ=100

The stability profile plotting Avg DAR over time is used to understand the efficacy results. Using the affinity capture LC– MS method, maleimide exchange has been identified as the mechanism of deconjugation for ADCs with maleimide linkers. It has been proposed that maleimide can exchange with albumin in plasma in vitro based on data from maleimide linkers containing fluorescent tags. In more recent studies using a model THIOMAB ADC, where the linker drugs were specifically conjugated to the engineered cysteine sites, maleimide exchange was observed with several thiolreactive constituents in plasma both in vitro and in vivo [62]. This is evident from the identification of molecular masses corresponding to albumin- and cysteine-linker drug by affinity capture LC–MS. In addition, conjugation site and maleimide hydrolysis have been identified as important factors that impact the rate of deconjugation, which can affect efficacy and safety [35, 62, 134]. In particular, affinity capture LC–MS data suggested that maleimide hydrolysis and subsequent opening of the succinimide ring stabilized the linker drug(s) and prevented further deconjugation [62]. Innovative native MS methods have been developed for characterization of ADCs with non-covalently bound interchains [64, 135, 136]. For example, a novel affinity capture native nano-electrospray ionization (nano-ESI) LC–MS assay showed proof of concept and feasibility of in vivo sample analysis [64]. This is because the capillary LC method is performed under denaturing conditions and non-covalently bound light and heavy chains separate during the analysis. As a result, for ADCs that contain reduced interchain disulfides, LC–MS approaches provide light- and heavychain masses and only the average DAR can be determined with the assumption that each ADC molecule contains two heavy chains and two light chains. In contrast, native LC– MS is performed under non-denaturing or native conditions and is suitable for measuring DAR distributions for ADCs with non-covalently bound chains. However, at this point, it is still challenging to apply the native LC–MS assays to in vivo plasma samples due to insufficient sensitivity. A custom designed affinity capture LC–MS approachLCMS F(ab′)2 assay was recently reported to address the bioanalytical challenges associated with new generation ADCs such as site-specific ADCs conjugated in the Fab [104]. New ADC payloads such as DNA-damaging agents may be more potent than historical tubulin binders leading

to lower dosage, which requires higher sensitivity of MS analysis. Certain ADC payloads may be more metabolically labile than maytansines and auristatins [67, 137], leading to more complexed biotransformation, which demands higher resolution of MS analysis for confident and detailed structural education of various ADC species. The newly developed affinity capture LCMS F(ab′)2 assay used a capture reagent against the Fab region of human IgGs, such as extracellular domain (ECD) or anti-Fab antibody. IdeS digestion was incorporated to remove the glycan-containing Fc fragment and generate the linker-drug containing fragment F(ab′)2 (~ 100 kDa) for analysis. The reduced size of analytes results in improved sensitivity and resolution of mass spectra compared to the intact ADC analytes (~ 150 kDa) produced by PNGaseF treatment for deglycosylation in the original affinity capture LC–MS method. In addition, the reduced and optimized sample preparation time, for example, rapid removal of the Fc fragment by IdeS digestion, minimizes ex vivo payload metabolism and skewed DAR profiles that may result from the prolonged incubation times (e.g., overnight PNGaseF treatment for deglycosylation). The affinity capture LC–MS F(ab′)2 assay enables analysis of low-dose, labile, and complex site-specific ADCs due to its enhanced sensitivity, resolution, and minimized assay artifacts. Further improvement in MS resolution could be achieved by using higher-resolution MS instruments such as orbitraps for characterization of ADC payload metabolism with small mass changes [138]. In addition to helping to optimize ADC drug design, ADC biotransformation information including ADC metabolites and DAR distribution also provide a guide for choosing appropriate analytes and to develop accurate quantitative methods for ADC bioanalysis. Depending on whether there is payload metabolism or not and whether payload metabolism impacts the potency of the drug, the PK analysis of appropriate analytes such as the active unconjugated payloads and conjugates with active payloads could be conducted accordingly (Fig. 2).

Exposure–Response Relation and Tissue Analysis An ADC is neither a small molecule drug nor an antibody drug. The systemic exposures of a mAb or the free drug fraction of a small molecule drug in general predict efficacy if there was no drug transporter effect [22, 139, 140]. In contrast, payload delivery to the site of action by an ADC is limited by pharmacokinetic and dispositional characteristics of the antibody and is slow compared to the delivery of a small molecule drug after oral administration. ADCs attenuate the Cmax of the payload in circulation and tissues and slow down the payload supply. This is a favorable propensity to decrease the toxicity by ADC but limits the pharmacological potential of a payload.

Curr Pharmacol Rep Fig. 2 Selection of appropriate analytes for PK assays based on ADC biotransformations. A Possible THIOMAB™ ADC biotransformations due to linker deconjugation and interested analytes for PK bioanalysis. B Possible THIOMAB™ ADC biotransformations due to linker deconjugation and payload metabolism and proposed interested analytes for PK bioanalysis in the cases of payload metabolism not impacting (a) and impacting (b) ADC potency, respectively. Payloads and active metabolites are shown in red, and inactive metabolites of payloads are shown in black

a

b

The exposure–response (efficacy or toxicity) relation of an ADC could be contrary to the understanding of a small molecule for which a higher systemic exposure would lead to a higher level of efficacy and toxicity. Great efforts have been made to characterize the heterogeneous and dynamic mixture of these ADC species in circulation [124, 141], each of which could have its own pharmacokinetic and biological activity profiles. However, the ADC species in circulation to use for exposure–response correlation (both safety and efficacy) is not currently known [100, 142–144]. An important question is to determine key PK parameters involving in the ADC in vivo efficacy. Distinct efficacy profiles were observed with the CD22conjugates of cyclopropyl-disulfide-PBD and cyclobutyldisulfide-PBD that contained structurally analog linkers following administration in xenograft mice [15, 52]. Catabolite analysis showed that these ADCs released different payloads with the cyclobutyl-disulfide-PBD releasing the PBD payload but the cyclopropyl-disulfide-PBD ADC releasing inactive cyclopropyl-thiol-containing catabolite [15, 52]. These are good examples to demonstrate that the chemical nature and concentration of intratumor catabolites depend on the linker type and in turn determine the ADC efficacy. In this case, total

mAb and catabolite concentrations were measured in plasma, liver, and tumors of xenograft mice. The measured tumor and plasma exposures of total mAb were similar for both ADCs with much higher total mAb concentrations in plasma than in tumors [15, 52]. The drug-to-antibody ratios of the two conjugates were also similar and relatively stable over a 7-day period, and therefore, the conjugated antibody (calculated from total Ab and DAR analyses) should also have similar concentrations between the two ADCs. These results indicated that analysis of ADC species in circulation that is routinely performed is not sufficient to explain or predict ADC efficacy outcomes. Instead, catabolite identification and quantitation (which is not routinely performed for detailed understanding of the catabolites in the tissues) in the plasma and tumors are important to rationalize the ADC efficacy. While an ADC helps deliver the payload to tissues, the payload is ultimately responsible for efficacy and toxicity; therefore, lack of correlation between the systemic exposure and efficacy is not surprising. ADCs with unstable sites of attachment leading to fast clearance and low efficacy might actually never deliver a threshold concentration of payload to tumors to achieve efficacy [62]. Increased doses of a given

Curr Pharmacol Rep

ADC in preclinical models or patients should lead to an increased ADC systemic exposures and deliver more catabolite to tumors; however, a quantitative correlation between systemic exposure and ADC efficacy is not known [142, 145]. The intratumor catabolites appear to have different kinetic profiles than the circulating ADC species for DNA alkylators antimitotic agents [120, 146–148]. PK-PD modeling had limited success to correlate the ADC efficacy with the PK parameters of ADC species in circulation [148, 149]. Until we gain detailed mechanistic understanding of quantitative processing of a given ADC for payload release in tumor cells, any prediction of payload concentration at the site of action and systemic PK-PD relationship for general applications may remain challenging [148, 150]. For a DNA alkylator ADC (e.g., PBD), once released at the site of action following ADC internalization, the payload PBD is Btrapped^ through covalent binding to DNA. Therefore, a DNA alkylator ADC could show extended efficacy period even after the ADC was cleared from systemic circulation. The sustained period of DNA alkylation that correlated with the efficacy may support less frequent dosing of a DNA alkylator ADC than the normally used interval of every 3 weeks [120]. This less frequent dosing should allow for longer time between dose cycles to facilitate normal tissue repair through DNA repair mechanisms [98, 151] and disposition of payload drugs. Although circulating catabolite rarely contributes to ADC efficacy as it is out of site of action (tumor), it could contribute to ADC toxicity. An instable ADC may show a low systemic exposure with less amount of catabolite delivered to tumors to give a low efficacy. Meanwhile, the instability may generate a higher level of catabolite into circulation leading to a higher toxicity. Despite having comparable efficacy, ADCs with maytansinoids linked through instable disulfide linker to anti-HER2 (with lower ADC exposure) showed greater weight loss in rats than a trastuzumab ADC linked through stable non-cleavable ether [152]. For tissue analysis, the tissue (e.g., tumor and liver) samples can be homogenized in control mouse plasma (1:4, tissue weight in g/plasma volume in mL). To characterize and quantify the catabolites in the mouse plasma and tissues, the homogenate can be extracted by an organic solvent to precipitate the proteins. The matrix effects of the tissue samples can be minimized by homogenizing the tissues in blank mouse plasma [120]. For a DNA alkylator, DNA can be isolated and further digested with DNase followed by the separate quantitation of the bound alkylator and DNA. For quantitation of total mAb, an affinity capture approach using protein-A magnetic beads can be used to enrich the ADCs from the mouse tissue homogenate. The bound ADCs were subject to Bonbead^ proteolysis with trypsin following standard protein denaturation, reduction, and alkylation processing steps. Quantification of the total mAb concentration can be achieved by using LC–MS/MS measurement of its surrogate peptide(s)

produced by proteolytic digestion. In addition, several peptides characteristic to the human Fc region can be monitored for the confirmation and troubleshooting purpose [124].

Summary and Future Perspectives LC–MS, as an emerging analytical tool for analyzing and characterizing of mAbs and ADCs in vivo, can provide valuable information regarding biotransformation, catabolism, plasma/tissue exposure, target engagement for better prediction of PK/PD, and designing of novel drug candidates. Immuno-affinity capture (and multi-stage immuno-affinity captures at both protein and peptide levels) coupled to LC– MS has improved selectivity and sensitivity of LC–MS applications in analyzing and characterizing mAbs and ADCs. LC– HRMS is a powerful tool in charactering biotransformation of antibody, linker, and payload of ADCs. Despite recent technological advances in characterization and quantifying ADC species such as total antibody, conjugated antibody, conjugated drug, and payload drug in circulation, challenges remain to correlate the exposures of these circulating species to ADC in vivo efficacy outcomes. With establishment of the correlation between intratumor catabolite exposures and anti-tumor efficacy, it will be valuable to build models to predict intratumor catabolite exposures from the systemic exposure of ADC species. Although LC–MS-based quantitation of mAbs and ADCs are extremely useful in preclinical studies especially in earlier discovery providing adequate sensitivity using generic capture reagents, significant challenges remain. The multi-step enzyme digestion and signature peptide based bottom-up approach is generally less sensitive and with lower throughput comparing to LBAs. The sensitivity of the top-down intact quantitation of protein therapeutics using full-scan HRMS is significantly lower than the bottom-up approach though quantitation and structure change can be obtained simultaneously. Instrumentation and software advancement is warranted for the routine application of quantitation of mAbs using HRMS in biological samples. LC–MS will find great opportunities of contribution in ADC characterization and quantitation. In vivo DAR distribution characterization through immuno-affinity capture LC–HRMS will continue to be the key evaluation of ADC biotransformation. Total-antibody in either LBA or LBA and LC–MS hybrid approach combining DAR distribution assay has been and will be further widely adopted as a preferred approach in screening ADCs in early discovery. Meanwhile, total-antibody and conjugated-drug measured in hybrid approach has become the most efficient way in advancing ADCs in pre-clinical space and will see more acceptances by pharmaceutical companies. Both opportunity and challenges exist for continuing hybrid LBA and LC–MS approach for ADC bioanalysis into early and late clinical space.

Curr Pharmacol Rep Acknowledgements The authors would like to thank Drs. Naidong Weng, Douglas Leipold, Cyrus Khojasteh-Bakht, and Cornelis Hop for their support and review of the manuscript.

Compliance with Ethical Standards Conflict of Interest There is no conflict of interest for all authors. Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors.

References 1.

2. 3.

4. 5.

6. 7.

8. 9.

10.

11.

12.

13.

14.

15.

16.

Beck A, Sanglier-Cianférani S, van Dorsselaer A. Biosimilar, biobetter, and next generation antibody characterization by mass spectrometry. Anal Chem. 2012;84(11):4637–46. https://doi.org/ 10.1021/ac3002885. Vidarsson G, et al. IgG subclasses and allotypes: from structure to effector functions. Front Immunol. 2014;5:520. Wang YM, et al. Immunogenicity and PK/PD evaluation in biotherapeutic drug development: scientific considerations for bioanalytical methods and data analysis. Bioanalysis. 2014;6(1): 79–87. https://doi.org/10.4155/bio.13.302. Nelson AL. Antibody fragments: hope and hype. MAbs. 2010;2(1):77–83. https://doi.org/10.4161/mabs.2.1.10786. Kontermann RE, Brinkmann U. Bispecific antibodies. Drug Discov Today. 2015;20(7):838–47. https://doi.org/10.1016/j. drudis.2015.02.008. Spiess C, et al. Alternative molecular formats and therapeutic applications for bispecific antibodies. Mol Immunol. 2015;67(2 Pt A):95–106. Kontermann RE. Half-life extended biotherapeutics. Expert Opin Biol Ther. 2016;16(7):903–15. https://doi.org/10.1517/14712598. 2016.1165661. Wu B, Sun YN. Pharmacokinetics of peptide-Fc fusion proteins. J Pharm Sci. 2014;103(1):53–64. https://doi.org/10.1002/jps.23783. Lee JW. ADME of monoclonal antibody biotherapeutics: knowledge gaps and emerging tools. Bioanalysis. 2013;5(16):2003–14. https://doi.org/10.4155/bio.13.144. Tibbitts J, Canter D, Graff R, Smith A, Khawli LA. Key factors influencing ADME properties of therapeutic proteins: a need for ADME characterization in drug discovery and development. MAbs. 2016;8(2):229–45. https://doi.org/10.1080/19420862.2015.1115937. Lobo ED, Hansen RJ, Balthasar JP. Antibody pharmacokinetics and pharmacodynamics. J Pharm Sci. 2004;93(11):2645–68. https://doi.org/10.1002/jps.20178. Roopenian DC, Akilesh S. FcRn: the neonatal Fc receptor comes of age. Nat Rev Immunol. 2007;7(9):715–25. https://doi.org/10. 1038/nri2155. Ezan E, Becher F, Fenaille F. Assessment of the metabolism of therapeutic proteins and antibodies. Expert Opin Drug Metab Toxicol. 2014;10(8):1079–91. https://doi.org/10.1517/17425255.2014.925878. Hall MP. Biotransformation and in vivo stability of protein biotherapeutics: impact on candidate selection and pharmacokinetic profiling. Drug Metab Dispos. 2014;42(11):1873–80. https://doi.org/10.1124/dmd.114.058347. Zhang D, Pillow TH, Ma Y, Cruz-Chuh J, Kozak KR, Sadowsky JD, et al. Linker immolation determines cell killing activity of disulfide-linked pyrrolobenzodiazepine antibody-drug conjugates. ACS Med Chem Lett. 2016;7(11):988–93. https://doi.org/10. 1021/acsmedchemlett.6b00233. Ouellette D, Chumsae C, Clabbers A, Radziejewski C, Correia I. Comparison of the in vitro and in vivo stability of a succinimide

intermediate observed on a therapeutic IgG1 molecule. MAbs. 2013;5(3):432–44. https://doi.org/10.4161/mabs.24458. 17. Yin S, Pastuskovas CV, Khawli LA, Stults JT. Characterization of therapeutic monoclonal antibodies reveals differences between in vitro and in vivo time-course studies. Pharm Res. 2013;30(1): 167–78. https://doi.org/10.1007/s11095-012-0860-z. 18. Liu L. Pharmacokinetics of monoclonal antibodies and Fc-fusion proteins. Protein Cell 2017. 19. Chari RV, et al. Antibody-drug conjugates: an emerging concept in cancer therapy. Angew Chem Int Ed Engl. 2014;53(15):3796– 827. https://doi.org/10.1002/anie.201307628. 20. Doronina SO, Toki BE, Torgov MY, Mendelsohn BA, Cerveny CG, Chace DF, et al. Development of potent monoclonal antibody auristatin conjugates for cancer therapy. Nat Biotechnol. 2003;21(7):778–84. https://doi.org/10.1038/nbt832. 21. LoRusso PM, Weiss D, Guardino E, Girish S, Sliwkowski MX. Trastuzumab emtansine: a unique antibody-drug conjugate in development for human epidermal growth factor receptor 2-positive cancer. Clin Cancer Res. 2011;17(20):6437–47. https://doi.org/10. 1158/1078-0432.CCR-11-0762. 22. Sliwkowski MX, Mellman I. Antibody therapeutics in cancer. Science. 2013;341(6151):1192–8. https://doi.org/10.1126/ science.1241145. 23. Shor B, et al. Preclinical and clinical development of inotuzumabozogamicin in hematological malignancies. Mol Immunol. 2015;67(2 Pt A):107–16. 24. Ricart AD. Antibody-drug conjugates of calicheamicin derivative: gemtuzumab ozogamicin and inotuzumab ozogamicin. Clin Cancer Res. 2011;17(20):6417–27. https://doi.org/10.1158/10780432.CCR-11-0486. 25. Beck A, Goetsch L, Dumontet C, Corvaïa N. Strategies and challenges for the next generation of antibody-drug conjugates. Nat Rev Drug Discov. 2017;16(5):315–37. https://doi.org/10.1038/nrd.2016.268. 26. Sochaj AM, Świderska KW, Otlewski J. Current methods for the synthesis of homogeneous antibody-drug conjugates. Biotechnol Adv. 2015;33(6 Pt 1):775–84. https://doi.org/10.1016/j. biotechadv.2015.05.001. 27. Jain N, Smith SW, Ghone S, Tomczuk B. Current ADC linker chemistry. Pharm Res. 2015;32(11):3526–40. https://doi.org/10. 1007/s11095-015-1657-7. 28. Perez HL, Cardarelli PM, Deshpande S, Gangwar S, Schroeder GM, Vite GD, et al. Antibody-drug conjugates: current status and future directions. Drug Discov Today. 2014;19(7):869–81. https:// doi.org/10.1016/j.drudis.2013.11.004. 29. Panowksi S, et al. Site-specific antibody drug conjugates for cancer therapy. mAbs. 2014;6(1):34–45. 30. Bouchard H, Viskov C, Garcia-Echeverria C. Antibody-drug conjugates—a new wave of cancer drugs. Bioorg Med Chem Lett. 2014;24(23):5357–63. https://doi.org/10.1016/j.bmcl.2014.10.021. 31. Beck A, Reichert JM. Antibody-drug conjugates: present and future. MAbs. 2014;6(1):15–7. https://doi.org/10.4161/mabs.27436. 32. Jackson DY. Processes for constructing homogeneous antibody drug conjugates. Org Process Res Dev. 2016;20(5):852–66. https://doi.org/10.1021/acs.oprd.6b00067. 33. Akkapeddi P, Azizi SA, Freedy AM, Cal PMSD, Gois PMP, Bernardes GJL. Construction of homogeneous antibody-drug conjugates using site-selective protein chemistry. Chem Sci. 2016;7(5):2954–63. https://doi.org/10.1039/C6SC00170J. 34. Junutula JR, Bhakta S, Raab H, Ervin KE, Eigenbrot C, Vandlen R, et al. Rapid identification of reactive cysteine residues for sitespecific labeling of antibody-Fabs. J Immunol Methods. 2008;332(1–2):41–52. https://doi.org/10.1016/j.jim.2007.12.011. 35. Junutula JR, Raab H, Clark S, Bhakta S, Leipold DD, Weir S, et al. Site-specific conjugation of a cytotoxic drug to an antibody improves the therapeutic index. Nat Biotechnol. 2008;26(8):925–32. https://doi.org/10.1038/nbt.1480.

Curr Pharmacol Rep 36.

Hofer T, Skeffington LR, Chapman CM, Rader C. Molecularly defined antibody conjugation through a selenocysteine interface. Biochemistry. 2009;48(50):12047–57. https://doi.org/10.1021/ bi901744t. 37. Axup JY, Bajjuri KM, Ritland M, Hutchins BM, Kim CH, Kazane SA, et al. Synthesis of site-specific antibody-drug conjugates using unnatural amino acids. Proc Natl Acad Sci U S A. 2012;109(40):16101–6. https://doi.org/10.1073/pnas. 1211023109. 38. Boeggeman E, Ramakrishnan B, Pasek M, Manzoni M, Puri A, Loomis KH, et al. Site specific conjugation of fluoroprobes to the remodeled Fc N-glycans of monoclonal antibodies using mutant glycosyltransferases: application for cell surface antigen detection. Bioconjug Chem. 2009;20(6):1228–36. https://doi.org/10.1021/ bc900103p. 39. Jeger S, Zimmermann K, Blanc A, Grünberg J, Honer M, Hunziker P, et al. Site-specific and stoichiometric modification of antibodies by bacterial transglutaminase. Angew Chem Int Ed Engl. 2010;49(51):9995–7. https://doi.org/10.1002/anie. 201004243. 40. Anami Y, Xiong W, Gui X, Deng M, Zhang CC, Zhang N, et al. Enzymatic conjugation using branched linkers for constructing homogeneous antibody-drug conjugates with high potency. Org Biomol Chem. 2017;15(26):5635–42. https://doi.org/10.1039/ C7OB01027C. 41. Flygare JA, Pillow TH, Aristoff P. Antibody-drug conjugates for the treatment of cancer. Chem Biol Drug Des. 2013;81(1):113–21. https://doi.org/10.1111/cbdd.12085. 42. Tumey LN, Charati M, He T, Sousa E, Ma D, Han X, et al. Mild method for succinimide hydrolysis on ADCs: impact on ADC potency, stability, exposure, and efficacy. Bioconjug Chem. 2014;25(10):1871–80. https://doi.org/10.1021/bc500357n. 43. Cohen R, Vugts DJ, Visser GWM, Stigter-van Walsum M, Bolijn M, Spiga M, et al. Development of novel ADCs: conjugation of tubulysin analogues to trastuzumab monitored by dual radiolabeling. Cancer Res. 2014;74(20):5700–10. https://doi.org/ 10.1158/0008-5472.CAN-14-1141. 44. Leverett CA, Sukuru SCK, Vetelino BC, Musto S, Parris K, Pandit J, et al. Design, synthesis, and cytotoxic evaluation of novel tubulysin analogues as ADC payloads. ACS Med Chem Lett. 2016;7(11):999–1004. https://doi.org/10.1021/acsmedchemlett. 6b00274. 45. Verma VA, Pillow TH, DePalatis L, Li G, Phillips GL, Polson AG, et al. The cryptophycins as potent payloads for antibody drug conjugates. Bioorg Med Chem Lett. 2015;25(4):864–8. https:// doi.org/10.1016/j.bmcl.2014.12.070. 46. Moldenhauer G, Salnikov AV, Lüttgau S, Herr I, Anderl J, Faulstich H. Therapeutic potential of amanitin-conjugated antiepithelial cell adhesion molecule monoclonal antibody against pancreatic carcinoma. J Natl Cancer Inst. 2012;104(8):622–34. https://doi.org/10.1093/jnci/djs140. 47. Puthenveetil S, Loganzo F, He H, Dirico K, Green M, Teske J, et al. Natural product splicing inhibitors: a new class of antibodydrug conjugate (ADC) payloads. Bioconjug Chem. 2016;27(8): 1880–8. https://doi.org/10.1021/acs.bioconjchem.6b00291. 48. Hartley JA. The development of pyrrolobenzodiazepines as antitumour agents. Expert Opin Investig Drugs. 2011;20(6):733– 44. https://doi.org/10.1517/13543784.2011.573477. 49. Jeffrey SC, Burke PJ, Lyon RP, Meyer DW, Sussman D, Anderson M, et al. A potent anti-CD70 antibody-drug conjugate combining a dimeric pyrrolobenzodiazepine drug with site-specific conjugation technology. Bioconjug Chem. 2013;24(7):1256–63. https:// doi.org/10.1021/bc400217g. 50. Kung Sutherland MS, Walter RB, Jeffrey SC, Burke PJ, Yu C, Kostner H, et al. SGN-CD33A: a novel CD33-targeting antibodydrug conjugate using a pyrrolobenzodiazepine dimer is active in

51.

52.

53.

54.

55.

56.

57.

58.

59.

60.

61.

62.

63.

64.

65.

models of drug-resistant AML. Blood. 2013;122(8):1455–63. https://doi.org/10.1182/blood-2013-03-491506. Flynn M, et al. ADCT-301, a pyrrolobenzodiazepine (PBD) dimer-containing antibody drug conjugate (ADC) targeting CD25-expressing hematological malignancies. Mol Cancer Ther. 2016;15(11):2709–21. https://doi.org/10.1158/1535-7163.MCT16-0233. Zhang D, Yu SF, Ma Y, Xu K, Dragovich PS, Pillow TH, et al. Chemical structure and concentration of intratumor catabolites determine efficacy of antibody drug conjugates. Drug Metab Dispos. 2016;44(9):1517–23. https://doi.org/10.1124/dmd.116. 070631. Mantaj J, Jackson PJM, Rahman KM, Thurston DE. From anthramycin to pyrrolobenzodiazepine (PBD)-containing antibody-drug conjugates (ADCs). Angew Chem Int Ed Engl. 2017;56(2):462–88. https://doi.org/10.1002/anie.201510610. Pillow TH, Schutten M, Yu SF, Ohri R, Sadowsky J, Poon KA, et al. Modulating therapeutic activity and toxicity of pyrrolobenzodiazepine antibody-drug conjugates with selfimmolative disulfide linkers. Mol Cancer Ther. 2017;16(5):871– 8. https://doi.org/10.1158/1535-7163.MCT-16-0641. Junttila MR, et al. Targeting LGR5+ cells with an antibody-drug conjugate for the treatment of colon cancer. Sci Transl Med. 2015;7(314):314ra186. Minotti G, Menna P, Salvatorelli E, Cairo G, Gianni L. Anthracyclines: molecular advances and pharmacologic developments in antitumor activity and cardiotoxicity. Pharmacol Rev. 2004;56(2):185–229. https://doi.org/10.1124/pr.56.2.6. Yu SF, Zheng B, Go M, Lau J, Spencer S, Raab H, et al. A novel anti-CD22 anthracycline-based antibody-drug conjugate (ADC) that overcomes resistance to auristatin-based ADCs. Clin Cancer Res. 2015;21(14):3298–306. https://doi.org/10.1158/1078-0432. CCR-14-2035. John A. Flygare THP, Brian Safina, Visha VERMA, Binqing Wei, William Denny, Anna GIDDENS, Ho Lee, Guo-Liang Lu, Christian Miller, Gordon Rewcastle, Moana Tercel, Muriel Bonnet, 1-(chloromethyl)-2,3-dihydro-1h-benzo[e]indole dimer antibody-drug conjugate compounds, and methods of use and treatment 2015, WO 2015023355 A1. Kaur S, Xu K, Saad OM, Dere RC, Carrasco-Triguero M. Bioanalytical assay strategies for the development of antibodydrug conjugate biotherapeutics. Bioanalysis. 2013;5(2):201–26. https://doi.org/10.4155/bio.12.299. Tumey LN, Rago B, Han X. In vivo biotransformations of antibody-drug conjugates. Bioanalysis. 2015;7(13):1649–64. https://doi.org/10.4155/bio.15.84. Alley SC, Benjamin DR, Jeffrey SC, Okeley NM, Meyer DL, Sanderson RJ, et al. Contribution of linker stability to the activities of anticancer immunoconjugates. Bioconjug Chem. 2008;19(3): 759–65. https://doi.org/10.1021/bc7004329. Shen BQ, Xu K, Liu L, Raab H, Bhakta S, Kenrick M, et al. Conjugation site modulates the in vivo stability and therapeutic activity of antibody-drug conjugates. Nat Biotechnol. 2012;30(2): 184–9. https://doi.org/10.1038/nbt.2108. Jackson D, Atkinson J, Guevara CI, Zhang C, Kery V, Moon SJ, et al. In vitro and in vivo evaluation of cysteine and site specific conjugated herceptin antibody-drug conjugates. PLoS One. 2014;9(1):e83865. https://doi.org/10.1371/journal.pone.0083865. Hengel SM, Sanderson R, Valliere-Douglass J, Nicholas N, Leiske C, Alley SC. Measurement of in vivo drug load distribution of cysteine-linked antibody-drug conjugates using microscale liquid chromatography mass spectrometry. Anal Chem. 2014;86(7): 3420–5. https://doi.org/10.1021/ac403860c. Kellogg BA, Garrett L, Kovtun Y, Lai KC, Leece B, Miller M, et al. Disulfide-linked antibody-maytansinoid conjugates: optimization of in vivo activity by varying the steric hindrance at carbon

Curr Pharmacol Rep atoms adjacent to the disulfide linkage. Bioconjug Chem. 2011;22(4):717–27. https://doi.org/10.1021/bc100480a. 66. Thomas H. Pillow, Donglu Zhang, Shang-Fan Yu, Geoffrey Del Rosario, Keyang Xu, Jintang He, Sunil Bhakta, Rachana Ohri, Katherine R. Kozak, Edward Ha, Jagath R. Junutula and John A. Flygare. Decoupling stability and release in disulfide bonds with antibody-small molecule conjugates. Chem Sci. 2016. 67. Tumey LN, Leverett CA, Vetelino B, Li F, Rago B, Han X, et al. Optimization of tubulysin antibody–drug conjugates: a case study in addressing ADC metabolism. ACS Med Chem Lett. 2016;7(11):977–82. https://doi.org/10.1021/acsmedchemlett. 6b00195. 68. Bouchard H, New cryptophycins as promising payloads for ADC, in 7th World ADC, San Diego 2016. 69. Brun M-P, et al. Abstract LB-053: Towards new cryptophycins as promising payloads for ADC. Cancer Res. 2016;76(14 Supplement):LB-053-LB-53. 70. Gorovits B, Alley SC, Bilic S, Booth B, Kaur S, Oldfield P, et al. Bioanalysis of antibody-drug conjugates: American Association of Pharmaceutical Scientists Antibody-Drug Conjugate Working Group position paper. Bioanalysis. 2013;5(9):997–1006. https:// doi.org/10.4155/bio.13.38. 71. Beck A, Terral G, Debaene F, Wagner-Rousset E, Marcoux J, Janin-Bussat MC, et al. Cutting-edge mass spectrometry methods for the multi-level structural characterization of antibody-drug conjugates. Expert Rev Proteomics. 2016;13(2):157–83. https:// doi.org/10.1586/14789450.2016.1132167. 72. Jian W, Kang L, Burton L, Weng N. A workflow for absolute quantitation of large therapeutic proteins in biological samples at intact level using LC-HRMS. Bioanalysis. 2016;8(16):1679–91. https://doi.org/10.4155/bio-2016-0096. 73. Grafmuller L, Wei C, Ramanathan R, Barletta F, Steenwyk R, Tweed J. Unconjugated payload quantification and DAR characterization of antibody-drug conjugates using high-resolution MS. Bioanalysis. 2016;8(16):1663–78. https://doi.org/10.4155/bio2016-0120. 74. DeSilva B, Smith W, Weiner R, Kelley M, Smolec JM, Lee B, et al. Recommendations for the bioanalytical method validation of ligand-binding assays to support pharmacokinetic assessments of macromolecules. Pharm Res. 2003;20(11):1885–900. https://doi. org/10.1023/B:PHAM.0000003390.51761.3d. 75. Jenkins R, Duggan JX, Aubry AF, Zeng J, Lee JW, Cojocaru L, et al. Recommendations for validation of LC-MS/MS bioanalytical methods for protein biotherapeutics. AAPS J. 2015;17(1):1–16. https://doi.org/10.1208/s12248-014-9685-5. 76. Ackermann BL. Immunoaffinity MS: adding increased value through hybrid methods. Bioanalysis. 2016;8(15):1535–7. https://doi.org/10.4155/bio-2016-0162. 77. Ramagiri S and Moore I, Hybridizing LBA with LC–MS/MS: the new norm for biologics quantification, Future Sci. 2016. 78. Jones BR, Schultz GA. Adaptation of hybrid immunoaffinity LCMS methods for protein bioanalysis in a contract research organization. Bioanalysis. 2016;8(15):1545–9. https://doi.org/10.4155/ bio-2016-0104. 79. van den Broek I, Niessen WMA, van Dongen WD. Bioanalytical LC-MS/MS of protein-based biopharmaceuticals. J Chromatogr B Analyt Technol Biomed Life Sci. 2013;929:161–79. https://doi. org/10.1016/j.jchromb.2013.04.030. 80. Burris HA 3rd, et al. Phase II study of the antibody drug conjugate trastuzumab-DM1 for the treatment of human epidermal growth factor receptor 2 (HER2)-positive breast cancer after prior HER2directed therapy. J Clin Oncol. 2011;29(4):398–405. https://doi. org/10.1200/JCO.2010.29.5865. 81. Furlong MT, Titsch C, Xu W, Jiang H, Jemal M, Zeng J. An exploratory universal LC-MS/MS assay for bioanalysis of hinge region-stabilized human IgG4 mAbs in clinical studies.

Bioanalysis. 2014;6(13):1747–58. https://doi.org/10.4155/bio.14. 64. 82. van den Broek I, van Dongen WD. LC-MS-based quantification of intact proteins: perspective for clinical and bioanalytical applications. Bioanalysis. 2015;7(15):1943–58. https://doi.org/10. 4155/bio.15.113. 83. Ruan Q, Ji QC, Arnold ME, Humphreys WG, Zhu M. Strategy and its implications of protein bioanalysis utilizing high-resolution mass spectrometric detection of intact protein. Anal Chem. 2011;83(23):8937–44. https://doi.org/10.1021/ac201540t. 84. Gucinski AC, Boyne MT. Evaluation of intact mass spectrometry for the quantitative analysis of protein therapeutics. Anal Chem. 2012;84(18):8045–51. https://doi.org/10.1021/ac301949j. 85. Zhao Y, Liu G, Yuan X, Gan J, Peterson JE, Shen JX. Strategy for the quantitation of a protein conjugate via hybrid immunocaptureliquid chromatography with sequential HRMS and SRM-based LC-MS/MS analyses. Anal Chem. 2017;89(9):5144–51. https:// doi.org/10.1021/acs.analchem.7b00926. 86. Lanshoeft C, Cianférani S, Heudi O. Generic hybrid ligand binding assay liquid chromatography high-resolution mass spectrometry-based workflow for multiplexed human immunoglobulin G1 quantification at the intact protein level: application to preclinical pharmacokinetic studies. Anal Chem. 2017;89(4): 2628–35. https://doi.org/10.1021/acs.analchem.6b04997. 87. Kang L, Camacho RC, Li W, D’Aquino K, You S, Chuo V, et al. Simultaneous catabolite identification and quantitation of large therapeutic protein at the intact level by immunoaffinity capture liquid chromatography-high-resolution mass spectrometry. Anal Chem. 2017;89(11):6065–75. https://doi.org/10.1021/acs. analchem.7b00674. 88. Kellie JF, Kehler JR, Mencken TJ, Snell RJ, Hottenstein CS. A whole-molecule immunocapture LC-MS approach for the in vivo quantitation of biotherapeutics. Bioanalysis. 2016;8(20):2103–14. https://doi.org/10.4155/bio-2016-0180. 89. Liu H, Manuilov AV, Chumsae C, Babineau ML, Tarcsa E. Quantitation of a recombinant monoclonal antibody in monkey serum by liquid chromatography-mass spectrometry. Anal Biochem. 2011;414(1):147–53. https://doi.org/10.1016/j.ab. 2011.03.004. 90. Su D, Ng C, Khosraviani M, Yu SF, Cosino E, Kaur S, et al. Custom-designed affinity capture LC-MS F(ab′)2 assay for biotransformation assessment of site-specific antibody drug conjugates. Anal Chem. 2016;88(23):11340–6. https://doi.org/10. 1021/acs.analchem.6b03410. 91. Neubert H, Muirhead D, Kabir M, Grace C, Cleton A, Arends R. Sequential protein and peptide immunoaffinity capture for mass spectrometry-based quantification of total human β-nerve growth factor. Anal Chem. 2013;85(3):1719–26. https://doi.org/10.1021/ ac303031q. 92. Schultz GA, et al. Large-scale implementation of sequential protein and peptide immunoaffinity enrichment LC/nanoLC–MS/MS for human β-nerve growth factor. 2016. 93. Xu K, Liu L, Dere R, Mai E, Erickson R, Hendricks A, et al. Characterization of the drug-to-antibody ratio distribution for antibody-drug conjugates in plasma/serum. Bioanalysis. 2013;5(9):1057–71. https://doi.org/10.4155/bio.13.66. 94. Kleinnijenhuis AJ, Ingola M, Toersche JH, van Holthoon FL, van Dongen WD. Quantitative bottom up analysis of infliximab in serum using protein a purification and integrated muLCelectrospray chip IonKey MS/MS technology. Bioanalysis. 2016;8(9):891–904. https://doi.org/10.4155/bio-2015-0015. 95. Chambers EE, Fountain KJ, Smith N, Ashraf L, Karalliedde J, Cowan D, et al. Multidimensional LC-MS/MS enables simultaneous quantification of intact human insulin and five recombinant analogs in human plasma. Anal Chem. 2013;86(1):694–702. https://doi.org/10.1021/ac403055d.

Curr Pharmacol Rep 96.

Duggan JX, Vazvaei F, Jenkins R. Bioanalytical method validation considerations for LC–MS/MS assays of therapeutic proteins. Bioanalysis. 2015;7(11):1389–95. https://doi.org/10.4155/bio.15. 69. 97. Knutsson M, et al. LC–MS/MS of large molecules in a regulated bioanalytical environment—which acceptance criteria to apply? 2013. 98. Clingen PH, de Silva IU, McHugh PJ, Ghadessy FJ, Tilby MJ, Thurston DE, et al. The XPF-ERCC1 endonuclease and homologous recombination contribute to the repair of minor groove DNA interstrand crosslinks in mammalian cells produced by the pyrrolo[2,1-c][1,4]benzodiazepine dimer SJG-136. Nucleic Acids Res. 2005;33(10):3283–91. https://doi.org/10.1093/nar/ gki639. 99. Buckwalter M, Dowell JA, Korth-Bradley J, Gorovits B, Mayer PR. Pharmacokinetics of gemtuzumab ozogamicin as a singleagent treatment of pediatric patients with refractory or relapsed acute myeloid leukemia. J Clin Pharmacol. 2004;44(8):873–80. https://doi.org/10.1177/0091270004267595. 100. Wang J, Gu H, Liu A, Kozhich A, Rangan V, Myler H, et al. Antibody-drug conjugate bioanalysis using LB-LC-MS/MS hybrid assays: strategies, methodology and correlation to ligandbinding assays. Bioanalysis. 2016;8(13):1383–401. https://doi. org/10.4155/bio-2016-0017. 101. Lee JW. Generic method approaches for monoclonal antibody therapeutics analysis using both ligand binding and LC-MS/MS techniques. Bioanalysis. 2016;8(1):19–27. https://doi.org/10. 4155/bio.15.231. 102. Ouyang Z, Furlong MT, Wu S, Sleczka B, Tamura J, Wang H, et al. Pellet digestion: a simple and efficient sample preparation technique for LC-MS/MS quantification of large therapeutic proteins in plasma. Bioanalysis. 2012;4(1):17–28. https://doi.org/10. 4155/bio.11.286. 103. Zhang Q, Spellman DS, Song Y, Choi B, Hatcher NG, Tomazela D, et al. Generic automated method for liquid chromatographymultiple reaction monitoring mass spectrometry based monoclonal antibody quantitation for preclinical pharmacokinetic studies. Anal Chem. 2014;86(17):8776–84. https://doi.org/10.1021/ ac5019827. 104. Xu K, Liu L, Maia M, Li J, Lowe J, Song A, et al. A multiplexed hybrid LC-MS/MS pharmacokinetic assay to measure two coadministered monoclonal antibodies in a clinical study. Bioanalysis. 2014;6(13):1781–94. https://doi.org/10.4155/bio.14. 142. 105. Sleczka BG, Mehl JT, Shuster DJ, Lewis KE, Moore R, Vuppugalla R, et al. Quantification of human mAbs in mouse tissues using generic affinity enrichment procedures and LC-MS detection. Bioanalysis. 2014;6(13):1795–811. https://doi.org/10. 4155/bio.14.143. 106. Duan X, Abuqayyas L, Dai L, Balthasar JP, Qu J. High-throughput method development for sensitive, accurate, and reproducible quantification of therapeutic monoclonal antibodies in tissues using orthogonal array optimization and nano liquid chromatography/selected reaction monitoring mass spectrometry. Anal Chem. 2012;84(10):4373–82. https://doi.org/10.1021/ ac2034166. 107. Wang SJ, Wu ST, Gokemeijer J, Fura A, Krishna M, Morin P, et al. Attribution of the discrepancy between ELISA and LC-MS/MS assay results of a PEGylated scaffold protein in post-dose monkey plasma samples due to the presence of anti-drug antibodies. Anal Bioanal Chem. 2012;402(3):1229–39. https://doi.org/10.1007/ s00216-011-5527-9. 108. Law WS, Genin JC, Miess C, Treton G, Warren AP, Lloyd P, et al. Use of generic LC-MS/MS assays to characterize atypical PK profile of a biotherapeutic monoclonal antibody. Bioanalysis. 2014;6(23):3225–35. https://doi.org/10.4155/bio.14.167.

109.

110.

111.

112.

113.

114.

115.

116.

117.

118.

119. 120.

121.

122.

123.

Bronsema KJ, Bischoff R, Pijnappel WWMP, van der Ploeg AT, van de Merbel NC. Absolute quantification of the total and antidrug antibody-bound concentrations of recombinant human alphaglucosidase in human plasma using protein G extraction and LCMS/MS. Anal Chem. 2015;87(8):4394–401. https://doi.org/10. 1021/acs.analchem.5b00169. Neubert H, Grace C, Rumpel K, James I. Assessing immunogenicity in the presence of excess protein therapeutic using immunoprecipitation and quantitative mass spectrometry. Anal Chem. 2008;80(18):6907–14. https://doi.org/10.1021/ac8005439. Chen LZ, et al. Development of immunocapture-LC/MS assay for simultaneous ADA isotyping and semiquantitation. J Immunol Res. 2016;2016:7682472. Lanshoeft C, Wolf T, Walles M, Barteau S, Picard F, Kretz O, et al. The flexibility of a generic LC-MS/MS method for the quantitative analysis of therapeutic proteins based on human immunoglobulin G and related constructs in animal studies. J Pharm Biomed Anal. 2016;131:214–22. https://doi.org/10.1016/j.jpba.2016.08.039. An B, Zhang M, Qu J. Toward sensitive and accurate analysis of antibody biotherapeutics by liquid chromatography coupled with mass spectrometry. Drug Metab Dispos. 2014;42(11):1858–66. https://doi.org/10.1124/dmd.114.058917. Qu M, An B, Shen S, Zhang M, Shen X, Duan X, et al. Qualitative and quantitative characterization of protein biotherapeutics with liquid chromatography mass spectrometry. Mass Spectrom Rev. 2017;36(6):734–54. https://doi.org/10.1002/mas.21500. An B, Zhang M, Johnson RW, Qu J. Surfactant-aided precipitation/on-pellet-digestion (SOD) procedure provides robust and rapid sample preparation for reproducible, accurate and sensitive LC/ MS quantification of therapeutic protein in plasma and tissues. Anal Chem. 2015;87(7):4023–9. https://doi.org/10.1021/acs. analchem.5b00350. Bronsema KJ, Bischoff R, van de Merbel NC. Internal standards in the quantitative determination of protein biopharmaceuticals using liquid chromatography coupled to mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2012;893-894: 1–14. https://doi.org/10.1016/j.jchromb.2012.02.021. Li H, Ortiz R, Tran L, Hall M, Spahr C, Walker K, et al. General LC-MS/MS method approach to quantify therapeutic monoclonal antibodies using a common whole antibody internal standard with application to preclinical studies. Anal Chem. 2012;84(3):1267– 73. https://doi.org/10.1021/ac202792n. Nouri-Nigjeh E, Zhang M, Ji T, Yu H, An B, Duan X, et al. Effects of calibration approaches on the accuracy for LC-MS targeted quantification of therapeutic protein. Anal Chem. 2014;86(7): 3575–84. https://doi.org/10.1021/ac5001477. EMA. Guideline on clinical investigation of the pharmacokinetics of therapeutic proteins. 2007. Bults P, Bischoff R, Bakker H, Gietema JA, van de Merbel NC. LC-MS/MS-based monitoring of in vivo protein biotransformation: quantitative determination of trastuzumab and its deamidation products in human plasma. Anal Chem. 2016;88(3): 1871–7. https://doi.org/10.1021/acs.analchem.5b04276. Hager T, Spahr C, Xu J, Salimi-Moosavi H, Hall M. Differential enzyme-linked immunosorbent assay and ligand-binding mass spectrometry for analysis of biotransformation of protein therapeutics: application to various FGF21 modalities. Anal Chem. 2013;85(5):2731–8. https://doi.org/10.1021/ac303203y. Hecht R, Li YS, Sun J, Belouski E, Hall M, Hager T, et al. Rationale-based engineering of a potent long-acting FGF21 analog for the treatment of type 2 diabetes. PLoS One. 2012;7(11): e49345. https://doi.org/10.1371/journal.pone.0049345. Casi G, Neri D. Antibody–drug conjugates: basic concepts, examples and future perspectives. J Control Release. 2012;161(2):422– 8. https://doi.org/10.1016/j.jconrel.2012.01.026.

Curr Pharmacol Rep 124.

Xu K, Liu L, Saad OM, Baudys J, Williams L, Leipold D, et al. Characterization of intact antibody-drug conjugates from plasma/ serum in vivo by affinity capture capillary liquid chromatographymass spectrometry. Anal Biochem. 2011;412(1):56–66. https:// doi.org/10.1016/j.ab.2011.01.004. 125. Stephan JP, Kozak KR, Wong WLT. Challenges in developing bioanalytical assays for characterization of antibody-drug conjugates. Bioanalysis. 2011;3(6):677–700. https://doi.org/10.4155/ bio.11.30. 126. Lesur A, Varesio E, Hopfgartner G. Accelerated tryptic digestion for the analysis of biopharmaceutical monoclonal antibodies in plasma by liquid chromatography with tandem mass spectrometric detection. J Chromatogr A. 2010;1217(1):57–64. https://doi.org/ 10.1016/j.chroma.2009.11.011. 127. Kumar S, King LE, Clark TH, Gorovits B. Antibody-drug conjugates nonclinical support: from early to late nonclinical bioanalysis using ligand-binding assays. Bioanalysis. 2015;7(13):1605–17. https://doi.org/10.4155/bio.15.107. 128. Stephan JP, Chan P, Lee C, Nelson C, Elliott JM, Bechtel C, et al. Anti-CD22-MCC-DM1 and MC-MMAF conjugates: impact of assay format on pharmacokinetic parameters determination. Bioconjug Chem. 2008;19(8):1673–83. https://doi.org/10.1021/ bc800059t. 129. Liu A, Kozhich A, Passmore D, Gu H, Wong R, Zambito F, et al. Quantitative bioanalysis of antibody-conjugated payload in monkey plasma using a hybrid immuno-capture LC-MS/MS approach: assay development, validation, and a case study. J Chromatogr B Analyt Technol Biomed Life Sci. 2015;1002:54–62. https://doi. org/10.1016/j.jchromb.2015.08.007. 130. Sanderson RJ, Nicholas ND, Baker Lee C, Hengel SM, Lyon RP, Benjamin DR, et al. Antibody-conjugated drug assay for proteasecleavable antibody-drug conjugates. Bioanalysis. 2016;8(1):55– 63. https://doi.org/10.4155/bio.15.230. 131. Heudi O, Barteau S, Picard F, Kretz O. Quantitative analysis of maytansinoid (DM1) in human serum by on-line solid phase extraction coupled with liquid chromatography tandem mass spectrometry—method validation and its application to clinical samples. J Pharm Biomed Anal. 2016;120:322–32. https://doi.org/10. 1016/j.jpba.2015.12.026. 132. Wei D, Sullivan M, Espinosa O, Yang L. A sensitive LC–MS/MS method forthe determination of free maytansinoid DM4 concentrations—method development, validation, and application to the nonclinical studies of antitumor agent DM4 conjugated hu-antiCripto MA b B3F6 (B3F6-DM4) in rats and monkeys. Int J Mass Spectrom. 2012;312:53–60. https://doi.org/10.1016/j.ijms.2011. 05.010. 133. Wei C, Zhang G, Clark T, Barletta F, Tumey LN, Rago B, et al. Where did the linker-payload go? A quantitative investigation on the destination of the released linker-payload from an antibodydrug conjugate with a maleimide linker in plasma. Anal Chem. 2016;88(9):4979–86. https://doi.org/10.1021/acs.analchem. 6b00976. 134. Hamblett KJ, Senter PD, Chace DF, Sun MM, Lenox J, Cerveny CG, et al. Effects of drug loading on the antitumor activity of a monoclonal antibody drug conjugate. Clin Cancer Res. 2004;10(20):7063– 70. https://doi.org/10.1158/1078-0432.CCR-04-0789. 135. Chen J, Yin S, Wu Y, Ouyang J. Development of a native nanoelectrospray mass spectrometry method for determination of the drug-to-antibody ratio of antibody-drug conjugates. Anal Chem. 2013;85(3):1699–704. https://doi.org/10.1021/ac302959p. 136. Debaene F, Bœuf A, Wagner-Rousset E, Colas O, Ayoub D, Corvaïa N, et al. Innovative native MS methodologies for antibody drug conjugate characterization: high resolution native MS and IM-MS for average DAR and DAR distribution assessment. Anal Chem. 2014;86(21):10674–83. https://doi.org/10.1021/ ac502593n.

137.

Dorywalska M, Strop P, Melton-Witt JA, Hasa-Moreno A, Farias SE, Galindo Casas M, et al. Site-dependent degradation of a noncleavable auristatin-based linker-payload in rodent plasma and its effect on ADC efficacy. PLoS One. 2015;10(7):e0132282. https:// doi.org/10.1371/journal.pone.0132282. 138. He J, Su D, Ng C, Liu L, Yu SF, Pillow TH, et al. High-resolution accurate-mass mass spectrometry enabling in-depth characterization of in vivo biotransformations for intact antibody-drug conjugates. Anal Chem. 2017;89(10):5476–83. https://doi.org/10.1021/ acs.analchem.7b00408. 139. Polakis P. Antibody drug conjugates for cancer therapy. Pharmacol Rev. 2016;68(1):3–19. https://doi.org/10.1124/pr.114. 009373. 140. Wang W, Wang EQ, Balthasar JP. Monoclonal antibody pharmacokinetics and pharmacodynamics. Clin Pharmacol Ther. 2008;84(5):548–58. https://doi.org/10.1038/clpt.2008.170. 141. Alley SC, Anderson KE. Analytical and bioanalytical technologies for characterizing antibody-drug conjugates. Curr Opin Chem Biol. 2013;17(3):406–11. https://doi.org/10.1016/j.cbpa.2013.03.022. 142. Kamath AV, Iyer S. Preclinical pharmacokinetic considerations for the development of antibody drug conjugates. Pharm Res. 2015;32(11):3470–9. https://doi.org/10.1007/s11095-014-1584-z. 143. Khot A, Sharma S, Shah DK. Integration of bioanalytical measurements using PK-PD modeling and simulation: implications for antibody-drug conjugate development. Bioanalysis. 2015;7(13):1633–48. https://doi.org/10.4155/bio.15.85. 144. Shah DK, King LE, Han X, Wentland JA, Zhang Y, Lucas J, et al. A priori prediction of tumor payload concentrations: preclinical case study with an auristatin-based anti-5T4 antibody-drug conjugate. AAPS J. 2014;16(3):452–63. https://doi.org/10.1208/ s12248-014-9576-9. 145. Lin K, Rubinfeld B, Zhang C, Firestein R, Harstad E, Roth L, et al. Preclinical development of an anti-NaPi2b (SLC34A2) antibodydrug conjugate as a therapeutic for non-small cell lung and ovarian cancers. Clin Cancer Res. 2015;21(22):5139–50. https://doi.org/ 10.1158/1078-0432.CCR-14-3383. 146. Erickson HK, Lambert JM. ADME of antibody-maytansinoid conjugates. AAPS J. 2012;14(4):799–805. https://doi.org/10. 1208/s12248-012-9386-x. 147. Leal M, Wentland JA, Han X, Zhang Y, Rago B, Duriga N, et al. Preclinical development of an anti-5T4 antibody-drug conjugate: pharmacokinetics in mice, rats, and NHP and tumor/tissue distribution in mice. Bioconjug Chem. 2015;26(11):2223–32. https:// doi.org/10.1021/acs.bioconjchem.5b00205. 148. Singh AP, Shin YG, Shah DK. Application of pharmacokineticPharmacodynamic modeling and simulation for antibody-drug conjugate development. Pharm Res. 2015;32(11):3508–25. https://doi.org/10.1007/s11095-015-1626-1. 149. Shah DK, Balthasar JP. PK/TD modeling for prediction of the effects of 8C2, an anti-topotecan mAb, on topotecan-induced toxicity in mice. Int J Pharm. 2014;465(1–2):228–38. https://doi.org/ 10.1016/j.ijpharm.2014.01.038. 150. Singh AP, Maass KF, Betts AM, Wittrup KD, Kulkarni C, King LE, et al. Evolution of antibody-drug conjugate tumor disposition model to predict preclinical tumor pharmacokinetics of trastuzumab-emtansine (T-DM1). AAPS J. 2016;18(4):861–75. https://doi.org/10.1208/s12248-016-9904-3. 151. McHugh PJ, Spanswick VJ, Hartley JA. Repair of DNA interstrand crosslinks: molecular mechanisms and clinical relevance. Lancet Oncol. 2001;2(8):483–90. https://doi.org/10.1016/S14702045(01)00454-5. 152. Lewis Phillips GD, Li G, Dugger DL, Crocker LM, Parsons KL, Mai E, et al. Targeting HER2-positive breast cancer with trastuzumab-DM1, an antibody-cytotoxic drug conjugate. Cancer Res. 2008;68(22):9280–90. https://doi.org/10.1158/0008-5472. CAN-08-1776.