Impact of Payload Hydrophobicity on Stability of Antibody-Drug

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Impact of Payload Hydrophobicity on Stability of Antibody-Drug-Conjugates Jakob W. Buecheler, Matthias Winzer, Jason Tonillo, Christian A Weber, and Henning Gieseler Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.8b00177 • Publication Date (Web): 29 May 2018 Downloaded from http://pubs.acs.org on May 29, 2018

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Molecular Pharmaceutics

Impact of Payload Hydrophobicity on Stability of Antibody-Drug-Conjugates Jakob W. Buecheler †ǁǁ, Matthias Winzer ǁǁ, Jason Tonillo ǁǁ, Christian Weber ǁǁ, Henning Gieseler ‡* † Division of Pharmaceutics, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen ǁǁ Discovery and Development Technologies, Merck KGaA, Darmstadt ‡ GILYOS GmbH, Würzburg, Germany

ACS Paragon Plus Environment

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Molecular Pharmaceutics 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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KEYWORDS: Antibody-drug conjugates, protein aggregation, stability, conjugation, thermal analysis, physicochemical properties.


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ABSTRACT:

In silico screening of toxin payloads typically employed in ADCs revealed a wide range of hydrophobicities and sizes as measured by logP and topological polar surface area (TPSA) values.

These descriptors were used to identify three non-toxic surrogate payloads that

encompass the range of hydrophobicity defined by the ADC toxin training set. Uniform drug to antibody ratio (DAR) ADCs were prepared for each surrogate payload by conjugation to the interchain cysteine residues of a model IgG1 subtype mAb. Linkage of these surrogate payloads to a common mAb with a matched DAR value allowed for preliminary analytical interrogation of the influence of payload hydrophobicity on global structure, self-association and aggregation properties.

The results of differential scanning fluorimetry and dynamic light scattering

experiments revealed clearly a direct correlation between destabilization of the native mAb structure and increasing payload hydrophobicity. Also, self-association / aggregation propensity examined by self-interaction bio-layer interferometry or size exclusion HPLC was consistent with increased conversion of the monomeric mAb to higher order aggregated species, with the degree of conversion directly proportional to payload hydrophobicity. In summary, these findings prove that payload-dependent structure destabilization and enhanced propensity to selfassociate / aggregate driven by increasing payload hydrophobicity contribute to reduced ADC stability and more complex behavior when assessing exposure and safety / efficacy relationships.


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Table of Contents Graphic (TOC)


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INTRODUCTION Monoclonal antibodies (mAb) represent a promising therapeutic modality for the treatment of a variety of cancers1. An alternative approach to apply mAbs in therapeutic treatments is to create pro-drugs, by conjugating pharmaceutically active small molecules like cytotoxic agents to the surface of the antibodies (antibody drug conjugates – ADCs). This combines specific targeting mediated by a monoclonal antibody and the efficacy of chemotherapy with the goal of improving the therapeutic index. Currently four ADC´s have received marketing approval, gemtuzumabozogamicin (Mylotarg), inotuzumab ozogamicin (Besponsa), brentuximab vedotin (Adcetris) and ado-trastuzumab emtansine (Kadcyla) and more than 75 additional ADC molecules are currently in clinical trials2. ADCs created by conjugation to lysine residues represent approximately 25% of all ADCs which are currently in clinical trials3. Although it is possible to control the average drug to antibody ratio (DAR) of a lysine conjugate, one systematic study of the DAR species distribution revealed partial modification of approximately 40 distinct surface exposed lysine residues (47% of total mAb lysine residues)4. ADCs created by conjugation to inter-chain cysteine residues represent more than 50% of all ADCs which are currently in clinical trials3. In contrast to the high degree of heterogeneity introduced by lysine conjugation, modification of mAb inter-chain cysteines only affords a total of twelve species of drug load and positional isomers5. Essential properties of small molecule therapeutics are permeability, clearance, stability and solubility6. The risks and benefits associated with the individual physicochemical properties and their translation to pharmacokinetic and pharmacodynamic behavior represents an essential component of the drug discovery process.


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Approximately 70 % of toxins currently employed for ADCs inhibit tubulin polymerization2 but the class of toxins, which target DNA such as calicheamicins, campthothecins, duocarmycins and pyrrolobenzodiazepines (PBDs), is rapidly emerging in the ADC field. Hydrophobicity represents an important factor contributing to the overall physicochemical properties of small molecule drugs6, 7. Although an increase in hydrophobicity often results in an improvement of in vitro potency, it also comes with the risks of poor solubility, metabolic instability and with a greater probability of non-specific off target effects8. Commonly used ADC toxins such as auristatins, maytansinoids and calicheamicins2,9 typically have 100-1000 times higher in vitro potency than traditional chemotherapeutic agents with IC50 values in the sub-nanomolar range10,11. This increase in potency is necessary to enable effective tumor cell killing by ADCs where the delivery to the intracellular drug target is linked to antigen expression level on the surface of the tumor cell and internalization efficiency. The use of such highly potent cytotoxic agents presents novel challenges in the safe handling and manufacturing of ADCs11,12. These novel challenges limit research activities to high containment facilities which can impede progress to further understand the properties, behavior and therapeutic mechanisms of ADCs. The bioconjugation of cytotoxic substances can alter the overall properties of the substrate antibody. Changes in secondary or tertiary structure13, charge profile14, hydrophobicity15 and light sensitivity16 have all been reported. These changes have subsequently been suggested to affect thermal stability13, serum half-life17 and aggregate formation13 of the ADC. The increase in susceptibility of ADCs to aggregation could directly impact the efficacy, toxicity and immune reaction of patients.


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Beckley et al.13 showed a destabilizing effect of increasing DAR resulting in a higher susceptibility to generate aggregates. Increasing DAR corresponds to higher occupancy of potential conjugation sites on the mAb. For interchain cysteine conjugation this results in a reduction in intact disulfide bridges which can potentially further destabilize the mAb in addition to the hydrophobic impact of the payload. In this study, the physical properties of commonly used ADC toxins were investigated in silico in order to identify non-toxic payload surrogates exhibiting comparable physical properties. Three surrogate payloads exhibiting a range of physical properties encompassed by typical ADC toxins were used to form ADCs with a uniform DAR (approximately 8). These surrogate ADCs were then used to probe the impact of payload hydrophobicity on ADC properties such as structure, self-association and aggregation propensity. Knowledge gained from this work will greatly contribute to the understanding of physicochemical destabilization of antibody conjugates and provide representative non-toxic model ADCs to investigate formulation or manufacturing challenges.


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MATERIAL AND METHODS Material L-Histidine, sodium perchlorate, sodium chloride, DPBS, acetonitrile, tris (2-carboxyethyl) phosphine hydrochloride solution (TCEP), formic acid and 5-maleimido-eosin were purchased from Merck (Darmstadt, Germany). BDP-FL-maleimide (Lumiprobe, FL, USA), fluorescein-5maleimide from Molecular Probes (Eugene, OR, USA). Human Fc (Acro Biosystems, Newark, USA). The model monoclonal IgG1 antibody with an pI of 8.48 was formulated at 1 mg/mL in 10 mM histidine buffer pH 5.5. Property Screen of Toxins in Silico Physical properties of toxins and non-toxic surrogates were determined using the prediction software Chemicalize of ChemAxon Ltd. LogP, tPSA and molecular weight were calculated and chemical structures were created using Accelrys Draw 4.2 (Accelrys Software Inc.). Synthesis of Conjugates 5 mg/mL model mAb was formulated in 1x DPBS pH7.4 and reduced with an 1.25 fold excess TCEP (Calbiochem, San Diego, CA, USA) per interchain cysteine at 37°C for 2h. Following reduction, the dyes BDP-FL-maleimide, fluorescein-5-maleimide or 5-maleimido-eosin were added to 10-fold excess per mAb and the headspace was overlayed with nitrogen. The conjugation was conducted at 2-8°C for 16h. The sample was diafiltatered in vivaspin colums 30.000 MWCO PES (Satorius, Stonehaous, United Kingdom) against 10mM histidine buffer pH 5.5. Residual unconjugated toxin surrogate and TCEP-related impurities were removed by this procedure. The final protein concentration was adjusted to 1 mg/ml.


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DAR Determination by LC-MS LC-MS analysis was performed using a Dionex U3000 HPLC system coupled to a SynaptG2vmass spectrometer (Waters). The protein solution was diluted with 0.1% TFA to 1 mg/mL and reduced by adding 3 µl TCEP (500mM) to 30µl Sample, followed by a 3 min incubation period at room temperature. 30 µg protein were injected on a Proteomix RP-1000 4.6x100mm (Sepax) column. Wavelength 214 nm was used to detect the heavy and light chain proteins. Identification was done by the on-line coupled mass spectrometer. After 1 min washing with 75% Buffer A (0.1% formic acid in distilled water) and 0.5 mL/min flow rate at 50 °C column oven temperature, the protein was eluted with a gradient from 25 % to 50% Buffer B (0.1 % formic acid in 85 % acetonitrile) within 14 min. Data were acquired in resolution mode with positive polarity and in a mass range from 400 to 6000 m/z. Additional instrument settings were set as follows: capillary voltage 2.8 kV, sampling cone to 40 V, extraction cone to 4.1 V, source temperature 150 °C, desolvation temperature 500 °C, cone gas 40 L/h, and desolvation gas 400 L/h. Spectra were deconvoluted with the MaxEnt1 algorithm within the MassLynx software. The DAR was calculated using the following equation: ∑ × , ∑ × , + = 2 × , + , = 2 × ∑ , ∑ , The variables An,L and An,H represent the peak area of the reverse phase chromatography of the light chain (L0 and L1) and heavy chain (H0, H1, H2 and H3) with the numbers representing the surrogate load per protein heavy chain (H) or light chain (L). Nano Differential Scanning Fluorimetry (nanoDSF) In thermal unfolding experiments, 10 µl of 1mg/ml protein formulations were loaded into UV


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transparent capillaries and mounted in a Prometheus NT.48 (both from Nanotemper Technologies, Germany). The temperature gradient was set to rise 1 °C/min in the range from 20 °C to 95 °C. Protein unfolding was measured by detecting the temperature-dependent change in tryptophan fluorescence at emission wavelengths of 330 and 350 nm. Melting temperatures were determined by detecting the maximum of the first derivative of the fluorescence ratios (F350/F330). Data was processed using the ThermControl software (Nanotemper Technologies, Munich Germany). Size Exclusion Chromatography (SEC) The relative amount of monomer and fragments was determined by SEC-HPLC with a TSKgel Super SW3000 column (Tosoh Bioscience, Germany) with peak area integration operated in an Agilent 1100 Module (Agilent Technologies) with UV detection at 214 nm. Undiluted samples at a concentration of 1 mg/ml were used. The mobile buffer consisted of 0.05 M sodium phosphate pH 6.3 with 0.4 M sodium perchlorate. The flowrate was 0.35 mL/min and the injection volume was 10 µl. Dynamic Light Scattering (DLS) DLS was measured at 1 mg/ml in UV-transparent 96-well plates with 70 µL sample volume using a DynaPro platereader II (Wyatt Technologies Europe GmbH, Dernbach, Germany) with incident light at 633 nm, measured at an angle of 173°. Samples were equilibrated at 25 ± 0.1 °C for 600 s prior to the measurements and this temperature was held constant throughout the experiments. All samples were measured in triplicate with 10 acquisitions and 5 s acquisition time. The change in cumulant fitted hydrodynamic radius in nanometers was monitored during


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storage period. Results were calculated using the Dynamics 7.1.7 software (Wyatt Technologies). Payload Dependent Self-Interaction by Bio-Layer Interferometry (PDSI-BLI) The Self-interaction as an indicator of attractive behavior of mAb or ADCs were investigated by BLI21 by using the Octet RED 96 (FortéBio). BLI is an optical analytical technique that analyses the interference pattern of white light reflected from two surfaces; a layer of immobilized protein on the biosensor tip and an internal reference layer. Changes in the number of molecules bound to the biosensor tip causes a shift in the interference pattern that was measured in real-time. Before each assay, the AHC sensor tips (anti-human Fc-capture, Fortebio) were hydrated in PBS for 10min. A baseline was established for the biosensors in PBS pH 7.4 for 20 s. The mAb or ADCs were then loaded onto the AHC sensor at a concentration of 0.033 µmol L−1 in PBS for 350 s and a second baseline in PBS was generated for 20 s. The sensor was then quenched by incubating in human Fc at a conc. of 0.8 µmol L−1 in PBS for 300 s followed by an incubation in 10mM histidine buffer at pH 5.5 for 30 s to determine a final baseline. The self-interaction of mAb or ADC at a concentration of 2 µmol L−1 in 10mM histidine pH 5.5 was then assayed using an association time of 400 s. The differences between the final baseline and the association was determined to be the self-interaction signal. The Software Data Acquisition 8.2 (Fortebio) was used to operate the BLI system and the Data Analysis 8.2 program (Fortebio) was applied to read out and interpret the data. Statistical Data Analysis


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Data were expressed as mean and standard deviation of three independent measures. The statistical analysis was performed by a One way ANOVA (Shapiro-Wilk) followed by a pairwise comparison (Tukey test). The results were considered statistically significant when P ≤ 0.05. For statistical analysis, SigmaPlot software (Systat Software, San Jose, CA, USA) was used. RESULTS In Silico Screen of ADC Payload Properties Traditional toxins targeting tubulin such as auristatins as well as novel payloads targeting DNA such as PBDs have been identified in literature2,18,19. Prediction tools available via the Chemicalize web resource were employed to calculate the hydrophobicity (expressed via LogP), permeability (expressed via topological polar surface area (tPSA)) and molecular weight of 20 representative toxin structures. Results are summarized in Table 1 ranked by increasing predicted hydrophobicity. This population of toxins covered a wide range of predicted hydrophobicities represented by LogP values ranging from 0.5 up to 5.7 with an average LogP value of 3.2 for this payload cohort. Predicted permeabilities, as determined by tPSA levels also exhibited a wide range of values from 57.2 to 308.4 angstroms with an average of 140.0. Finally, the molecular weights were distributed from 248.3 Da to 1368.3 Da with an average of 626.9 Da. Based on literature reports suggesting that payload hydrophobicity is the property with major impact on antibody drug conjugate stability, this physical property was a major driver in the selection of suitable payload surrogates for further study. Table 1. Toxin/ Payload Properties Determined in silico Toxines

LogP

tPSA [Å]

MW [Da]

CC-1065/

0.5

136.3

507


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Duocarmycin Abbeymycin

0.8

61.8

248

Doxorubicin

0.9

206.1

544

Camptothecin

1.2

79.7

348

Colchicine

1.5

83.1

399

SN38

1.9

100.0

392

Discodermolide

2.3

160.5

594

Maytansine

3.0

156.5

692

Combretastatin A-4

3.4

57.2

316

Paclitaxel

3.5

221.2

854

Rhizoxin

3.7

133.2

626

Dolastatin 10

3.8

142.4

785

DM1

3.9

156.5

738

Epothilone B

4.1

109.3

508

Vinblastine

4.2

154.1

811

Halichondrin B

4.5

216.2

1,111

Ansamitosin P-3

4.6

136.2

635

Calicheamicin

4.8

308.4

1,368

Dictyostatin

5.5

107.2

533

Hemiasterlin

5.7

91.6

526

Rationale for Selection of Payload Surrogates Guiding principles for the selection of payload surrogates included (1) encompassing the ranges of the key properties revealed by the in silico assessment of toxic payloads, (2) low toxicity potential to allow safe handling of large amounts without the need for high potency containment and (3) commercial availability as maleimide derivatives to facilitate conjugation to a model


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mAb. A particular focus on hydrophobicity guided the selection process, given the documented influence of hydrophobicity on the physical properties of ADCs13. Three suitable payload surrogates were identified based on these selection criteria and they are summarized in Table 2. These three reporter molecules largely encompassed the predicted hydrophobicity range of the toxin training set (Table 1, 0.5 to 5.7), with calculated LogP values of 1.1, 2.7 and 5.6. Also, these 3 reporter molecules showed predicted tPSA values in the range 74.4 to 121 angstroms and molecular weights in the range 414.2 to 742.9 Da, reasonable matches to the average values obtained using the toxin set. The selected payload surrogates were all commercially available in the maleimide activated forms, which enabled direct conjugation to partially reduced mAbs. Also, the presence of the polyaromatic fluorescent reporter groups in the final ADCs provides further mimics the anthracyclines toxins subset of the training set and provides a convenient handle to study ADC physical properties. The nomenclature for the model antibody dye conjugates containing these surrogate payloads employed throughout this publication is BodipyFL-maleimide = ADC1, Fluorescein-5-maleimide = ADC2 and 5-Maleimido-eosin = ADC3. Table 2. Structure and Properties of the ADC Toxin Surrogates Model

ADC1

ADC2

ADC3

Payload

Bodipy-fl-maleimide

Fluorescein-5-maleimide 5-Maleimido-eosin

Structure


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LogP

1.1

2.7

5.6

tPSA

74.7

121.2

121.0

Molecular weight [g/mol]

414.2

427.4

742.9

Construction of Matched Model ADCs Containing Each the Surrogate Payloads To facilitate an investigation of the surrogate payload influence on the physical properties and behavior of the corresponding ADCs, a single IgG1 subtype mAb was selected as the substrate for conjugation with each individual surrogate payload. Furthermore, a target DAR value of 8 was selected so that the payload density in all three constructs was similar. By targeting a DAR of 8 for an IgG1 subtype mAb, a single ADC species was constructed, eliminating the usual DAR distribution polydispersity typically observed in ADCs prepared by disulfide partial reduction. For construction of the model ADCs, the inter-chain disulfide bonds in the model IgG1 mAb were completely reduced and the corresponding reduced mAb intermediate was conjugated with excess of the appropriate surrogate payload. Following removal of excess unconjugated surrogate payload, the DAR values for each construct were quantified by reverse phase HPLC with tandem UV and mass spectroscopy (RP-MS). DAR values were calculated


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using the area percentage of peaks in the UV chromatogram from the RP-HPLC (S1). The payload density for each fragment peaks were identified by MS (S2). The DAR analysis revealed the expected modification of inter-chain cysteines, with values of 7.34, 7.86 and 7.63 for ADC1, ADC2 and ADC3, respectively. These results confirm a DAR in the model ADCs which is close to the theoretical DAR of 8, confirming a similar ADC species distribution between the model conjugates. Effect of Payload Hydrophobicity on the Tm Values for Model ADCs Differential scanning fluorimetry (DSF) measures the thermally induced unfolding of a protein and its local domains based on changes in the intrinsic fluorescence of selected hydrophobic core amino acids. Specifically, temperature dependent unfolding events of a protein domain are assessed by shifts in the emission wavelength ratios at 350 / 330 nm as the polarity of the local environment of the reporter amino acids changes. Here DSF was used to investigate differences in thermal stability and indirectly, the three-dimensional structure of the mAb and its corresponding ADCs caused by conjugation to payload surrogates with different hydrophobicity values. Each test article was subjected to a defined temperature ramp while monitoring the intrinsic fluorescence ratio at 330 nm and 350 nm, expressed as F350 / F330 and the results are shown in Figure 1A. Controls were included in this study, which contained mAb mixed with free dye. These controls showed no impact of the dye on the unfolding signals determined by nanoDSF (S3). The mAb and the three ADCs do not exhibit comparable starting levels in the ratio plot since the payload surrogates could also contribute to the ratio. This impact of the ratio levels appeared to be constant throughout the measurement and was therefore neglected in the analysis of the ratio data. The first derivative of the emission wavelength ratio allows detection of unfolding events of the mAb CH2 domain and of the Fab and CH3 domains. The results are


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shown in Figure 1B. The melting temperature (Tm) of the unconjugated mAb CH2 domain was 63.5°C while the Tm values for the corresponding ADCs with surrogate payloads of different hydrophobicities showed significant reductions (58.1°C, 56.5°C, and 52.6°C, for ADC1, ADC2 and ADC3, respectively. Furthermore, the signal associated with the CH2 domain unfolding event displayed lower intensities with increasing payload hydrophobicity (mAb > ADC1 > ADC2 > ADC3). Tm values of the Fab or CH3 domain showed no relevant changes up on conjugation of the different payloads. The Tm values of the CH2 domain unfolding events were plotted against the LogP value of the payloads and the results are shown in Figure 1C. The plot further confirms the correlation between payload hydrophobicity and the unfolding event of the CH2 domain.


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Figure 1. DSF thermograms of unconjugated mAb ( and ADC 3 (

) and ADC 1 (

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), ADC 2 (

)

). (A) The fluorescence ratio (F350 / F330) during a temperature gradient and

(B) the corresponding first derivative are shown. (C) The Tm of the CH2 domain is plotted over LogP values of the payload surrogates. Significance (p < 0.05) is represented by *. The error bars represent the standard deviation between three individually prepared samples and if not shown are smaller than the symbols. Increased Self-Interaction with Increased Surrogate Payload Hydrophobicity To investigate mAb or payload dependent self-interaction bio-layer interferometry (PDSI-BLI) was used in order to compare self-association intensities or attractive behavior of the


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unconjugated mAb or the three model ADCs. BLI is a label-free method commonly used to detect antibody or antibody conjugate binding to cognate antigens20, mAb quantification out of complex protein mixtures and quantification of antibody self-interaction21. A biosensor containing immobilized anti-human Fc antibody was loaded with mAb or ADC and subsequently exposed to a higher concentration of the identical mAb or ADC during the association phase. The BLI response in nanometers is proportional to the self-interaction intensity of the test article and the results for the mAb and ADCs are shown in Figure 2. All samples showed detectable BLI responses, consistent with varying degrees of self-association propensities. The mAb showed the lowest BLI value, 0.22 nm, consistent with a minimal degree of self-association potential. Alternatively, the ADCs showed increasing BLI responses that correlated with increasing surrogate payload hydrophobicity. Specifically, BLI values of 0.36 nm, 0.72 nm and 0.88 nm for ADC1, ADC2 and ADC3, respectively (surrogate payload LogP values of 1.1, 2.7 and 5.6, respectively). The results are consistent with an increase in self-interaction propensity compared to the starting mAb driven by a global increase in ADC hydrophobicity and structural changes introduced following reduction and loading of hydrophobic payloads onto the mAb inter-chain cysteine residues.


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Figure 2. Semi quantitative self-Interaction analysis by PDSI-BLI. Significance (p < 0.05) is represented by *. The error bars represent the standard deviation of values determined from four independent measurements.

Payload Hydrophobicity Induced Aggregation of ADCs The ADC structural changes documented by DSF and BLI following conjugation of the mAb to different payload surrogates could impact stability. The stability of the unconjugated mAb and model ADCs formulated in 10 mM Histidine at pH 5.5 was measured by size-exclusion chromatography (SEC) following incubation at 5, 25, or 40°C for up to 8 weeks. ADC samples incubated at 40°C showed a temporal increase in aggregate formation while the unconjugated mAb appeared to remain largely monomeric over time under these conditions (Figure 3A). Also, the extent of monomer depletion appeared proportional to increasing hydrophobicity of the surrogate payload with 7.9%, 18.6% and 37.2% loss at the 8 week time point for ADC1, ADC2 and ADC3, respectively. The monomer decay kinetics translate to average losses of 0.23% 1.02%, 2.40% and 5.00% per week for the mAb, ADC1, ADC2 and ADC3, respectively. In contrast, the mAb and ADCs maintained at either 5 or 25°C showed minimal aggregation over the same time frame under these conditions (data not shown). Representative SEC profiles of the mAb or ADC3 before or after treatment at 40°C for 4 weeks shows that the loss in monomer was primarily due to the formation of high molecular weight species (HMWS). These results suggest that for model ADCs, there is a correlation between the payload hydrophobicity and rate of aggregation during thermal stress under the conditions employed.


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Figure 3. (A) Monomer quantification by SEC-HPLC over 8 weeks at 40°C. Unconjugated mAb (

), ADC 1 (

), ADC 2 (

) and ADC 3 (

) were measured in triplicates after

0, 2, 4 and 8 weeks of incubation. The error bars represent the standard deviation of values determined from three separate vials and, if not shown are smaller than the symbols. (B) SEC chromatogram of mAb (black) and ADC3 (grew) pre-exposure (solid line) and after 4 weeks at 40°C (dashed line).

The Impact of Surrogate Payload Hydrophobicity on Colloidal Stability Prior experiments indicated clear differences in physical behavior and stability profile between the unconjugated mAb and model ADCs. These differences were further investigated by examining the impact of payload properties on the colloidal stability during thermal stress as measured by dynamic light scattering (DLS). DLS can be used to quantify the hydrodynamic diameter of the protein particles where increasing values are indicative of conformational changes and aggregation. DLS recordings of mAb, ADC1, ADC2 or ADC3 before and after incubation at 5, 25 and 40°C for 8 weeks were used as an indicator for colloidal stability and the


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data is summarized in Figure 4. All ADCs showed a significant increase in hydrodynamic diameter based on comparative analysis of DLS data derived from pre-exposure samples and samples treated at 40°C for 8 weeks. The observed increases in the hydrodynamic diameters (ADC3 > ADC2 > ADC1) were also consistent with an increased propensity to aggregate upon thermal stress as the hydrophobicity of the surrogate payload was increased. Alternatively, the unconjugated mAb showed no significant changes in hydrodynamic diameter following treatment at 40°C while incubation at 5 and 25°C had no significant impact on hydrodynamic diameter of any sample tested. The large standard deviation (DLS quantification of three independent samples) of the sample ADC3 after 8 weeks at 40°C, could be explained by the variability in the size of induced aggregates. Each bar represents measurements of three individual vials. The combined results from DSF, BLI, SEC HPLC and DLS are all consistent with a correlation between surrogate payload hydrophobicity and aggregate formation during thermal stress.

Figure 4. Aggregation screen using DLS. The pre-exposure ( samples incubated for 8 weeks at 5°C (

), 25°C (

) sample was compared to

) and 40°C (

).The error bars


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represent the standard deviation of values determined from three separate vials and, if not shown are smaller than the symbols.


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DISCUSSION In this study, the properties of cytotoxic drugs used for ADCs were assessed in silico in order to select non-toxic payload surrogates which are representative of the toxin population regarding hydrophobicity and size. Production of ADCs containing these non-toxic ADC payload surrogates at matched DAR values enabled investigations on impact of payload hydrophobicity on the biophysical and physiochemical properties of model ADCs. Experimental linkage of the changes in these properties to alterations in antibody domain structure and physical stability was performed. The high potency of therapeutic antibody drug conjugates requires clearly defined containment and safety procedures to ensure limited exposure of cytotoxic agents to personnel and the environment. Accordingly, processes that require relatively large quantities of ADCs are typically restricted to facilities that specialize in the safe handling of highly potent cytotoxic agents. For example, this may be one reason why there are currently only a limited number of publications in formulation science and drug product process development available in the field of antibody drug conjugates. Non-toxic payload surrogates enable the generation of model ADCs with biophysical properties and stability profiles comparable to ADCs. Such non-toxic model ADCs can be handled in an efficient and safe manner in a conventional lab environment for formulation and drug product process development purposes. The surrogate payloads identified in this study were selected to mimic the hydrophobicity, permeability and size properties of an extensive training set of highly potent ADC toxins typically used to construct ADCs. Specifically, LogP, tPSA and molecular weight were chosen as parameters to describe key properties that play a major role in both solubility and stability of


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small molecule drugs6. The screen of ADC toxin properties revealed a wide variety in hydrophobicity as determined by calculated LogP values over the range 0.5 to 5.7. For small molecules, increased hydrophobicity comes with the risk of poor aqueous solubility8. Furthermore, linker – payload hydrophobicity has been suggested to be a dominant factor leading to ADC instability9 and poor pharmacokinetic behavior17. The availability of ADCs containing three distinct non-toxic surrogate payloads with low, middle and high hydrophobicity levels provides unique tools to probe changes in ADC behavior across this spectrum of predicted LogP values. Previous studies revealed that an increase in DAR for lysine (primary amines)22,23 or interchain cysteine conjugates13 can result in decreased stability in the corresponding ADCs. These two conjugation approaches result in positive charge neutralization for lysine conjugation14 or elimination of multiple disulfide bonds for interchain cysteine conjugation. These changes are exaggerated with increasing DAR and hence could have a direct impact on ADC stability13,24, structure25,26 and pharmacokinetics27. The model payloads were covalently attached to the mAb by interchain cysteine conjugation using reduction conditions that afforded the maximum DAR value for an IgG1 subtype mAb. Under typical conditions, a partial reduction approach is employed, which creates a payload distribution covering up to 5 DAR species with 0, of 2, 4, 6 and 8 payloads per antibody5. Additional heterogeneity is caused by positional isomers with the same DAR value. These isoforms show different hydrophobic behavior as revealed by resolution of various ADC species by hydrophobic interaction chromatography (HIC)28. Since different ADC species can exhibit different stabilities, the final distribution of ADC species can profoundly influence overall ADC stability29. Linker properties and design elements can alter solubility30, overall hydrophobicity of


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the payload-linker intermediates31,32 or impact the physical distance between the payload and the mAb. These modifications in turn could alter ADC stability and serum half-life33. The linker / spacer was eliminated in this study for the model ADCs to maximize the contribution of the surrogate payload properties to the corresponding ADC and avoid influence of the linker portion on the overall properties of the payload. Construction of ADCs with DAR values in the range of 7.34 to 7.86 afforded a much simpler DAR species distribution, allowing for more straightforward interpretation of the experimental findings. Furthermore, the high DAR was also selected with the intention to force destabilization of model ADCs by higher overall hydrophobicity and complete elimination of the native inter-chain disulfide linkages13. The observed decreases in transition temperature (Tm) of the model ADCs as measured by DSF revealed an increased tendency of conjugates to undergo protein unfolding or aggregation. Prior studies revealed a destabilization by conjugation of payload toxins to ADCs compared to the corresponding unconjugated mAb34-36. Furthermore, the CH2 domain was dominantly affected by conjugation and a rise in DAR caused a reduction in transition temperature13,24-26,34. It is unclear whether these changes are the result of increased hydrophobicity, a higher degree of reduced interchain disulfide bonds or a combination of both properties. The findings from the present study are consistent with previous literature reports employing ADCs. The unconjugated mAb shows superior thermal stability compared to the model ADCs, all of which displayed significant decreases in stability as measured by thermal induced denaturation. These differences in unfolding behavior are consistent with global alterations in tertiary structure, likely influenced by covalent attachment of the different surrogate payloads as well as elimination of the interchain sulfides during the conjugation process. Specifically, the CH2 domain unfolding event, as measured by Tm, revealed a destabilizing impact of the


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conjugated surrogate payloads that was proportional to increasing hydrophobicity. The decrease in signal intensity and peak widening of the CH2 domain unfolding event are also consistent with a direct correlation between hydrophobicity and thermal stability. Changes in protein surface properties caused by conjugation have the potential to also influence the dynamics of protein-protein-interactions driven by changes in charge or hydrophobicity. Even positioning of the payloads on the mAb could have a direct effect on self-association behavior of ADCs36. Self-interaction has been associated with increased aggregation37, a reduction of solubility or an increase in solution viscosity21. The PDSI-BLI analysis confirmed that the propensity for self-association was significantly increased following conjugation of surrogate payloads and this behavior directly correlated with increased hydrophobicity of the surrogate payload. Therefore, payload properties may not only play a major role on ADC structure but also their self-association tendencies with increasing hydrophobicity resulting in a higher risk for aggregate formation or reduced solubility. We also demonstrate that the application of BLI is not limited to determination of protein binding affinity but can also afford insights into the ADC candidate selection process for ADCs. For example, as a moderate throughput approach for assessment of the properties of ADC constructs containing different linker toxin combinations or conjugation sites. Combined with information on essential ADC quality attributes such as potency and monomer content, a more comprehensive dataset can be utilized to assess ADC manufacturability and increase the probability of successful ADC drug development. The conclusion that ADCs are more prone to aggregate formation compared to their unconjugated mAb counterparts has been well documented24,35 and this behavior has been


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extended to include ADCs containing surrogate payloads in the present study. Data derived from multiple orthogonal experimental approaches all point to reduced thermal and colloidal stability and increased propensity to self-associate and aggregate of the model ADCs containing surrogate payloads compared to the un-conjugated starting antibodies. Furthermore the trending of these changes parallels the increase in payload hydrophobicity, consistent with this property being a major driver in the composite behavior of the final conjugate. Beckley et al.13 previously showed a correlation of drug load density and aggregation rate at higher temperatures and concluded that the destabilization of the CH2 domain caused by conjugation was responsible for an increase of aggregation13,38. Thermally induced aggregation in short-term stability ADC surrogate samples stored at 40°C for 8 weeks were monitored by SE-HPLC and DLS to assess both soluble and insoluble protein aggregates. The data trends obtained using these orthogonal methods correlated, consistent with the conclusion that model ADCs are more susceptible to form aggregates than the unconjugated antibody. Furthermore the propensity to form aggregates and increased hydrodynamic diameter directly correlated with increasing hydrophobicity of the surrogate payload. This data confirms the indications derived from DSF and PDSI-BLI investigation of the same sample set. Samples maintained at temperatures below 40°C (e.g. 5 or 25°C) showed no detectable degradation over the 8 week investigation period. This observation correlates with the findings of Adem et al.24, reporting no significant increase of aggregates of an IgG1 with covalently bound vcMMAE (DAR 3.5) and stored at 5 °C and 30 °C for up to 4 weeks. Susceptibility of ADCs to aggregation with highly hydrophobic payloads and / or ADC species with high DAR loads could not only affect shelf life of the pharmaceutical product, but these aggregates could induce an immune response in vivo or affect pharmacokinetics39.


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CONCLUSION This study has introduced three rationally selected non-toxic surrogate payloads to mimic properties of toxin payloads used for antibody-drug conjugates. In addition a narrow and homogeneous conjugation at almost the maximum theoretical DAR could be shown for the model ADCs, which enabled a payload dependent investigation. Hydrophobicity is the parameter with the highest variability between different ADCs, so a low, medium and high level of hydrophobicity described by LogP was selected. It was demonstrated that an increase of payload hydrophobicity causes changes in tertiary structure, which decrease thermal stability of the CH2 domain. Additionally, it was demonstrated that the susceptibility of ADCs to self-associate or to form aggregates rise with payload hydrophobicity independently of the DAR. Stability and structural data correlated with real ADC data reported in literature, which underlines the predictive power of the payload surrogate approach. The observations are applicable beyond ADCs and can enable insight into antibodysmall molecule conjugates in general like antibody-antibiotic conjugates (AAC) or antibodyfluorophore conjugates (AFC) . Non-toxic antibody conjugates can support addressing the gaps in the understanding of physical stability for ADCs in the manufacturing, formulation and process development. Non-toxic antibody conjugates allow safe handling of large quantities of antibody conjugates without the requirement of high potent facilities or equipment. Finally we suggested the method PDSI-BLI for early candidate selection of linker screenings or site selection for conjugation of antibody drug conjugates to evaluate manufacturability in an early development stage.


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AUTHOR INFORMATION Corresponding Author * Email: [email protected]. Phone: +49 931 90705678. Fax: +49 931 90705679. ACKNOWLEDGMENT We specially thank to Hendrik Nieraad and Bernhard Valldorf for their great work supporting the BLI analytics, Carl Deutsch and Verena Buback for the productive discussions and finally, we would like to thank Michael Bienkowski for reviewing this manuscript. ABBREVIATIONS ADC, antibody drug conjugate, DAR, drug- or dye-to-antibody ratio, IgG, immunoglobulin G, mAb, monoclonal antibody, TPSA, topological polar surface area, CH2, constant heavy chain domain 2, CH3, constant heavy domain 3, Fab, fragment antigen-binding, Tm, melting Temperature, HIC, hydrophobic interaction chromatography, RP-HPLC, reverse phase high performance liquid chromatography, SEC, size-exclusion chromatography, PDSI-BLI, payload dependent self-interaction by bio-layer interferometry, DSF, differential scanning fluorimetry, Tm, transition temperature, DLS, dynamic light scattering, HMWS, high molecular weight species.

SUPPORTING INFORMATION S1 The control antibody and three ADCs were reduced with TCEP, separated by reversed phase chromatography, and detected at 214 nm wavelength, respectively. In each sample two major peaks were detected and subsequently identified by a coupled mass spectrometer (see S2). S2 The reversed phase chromatography (see S1) was coupled to a mass spectrometer to identify the proteins. The molecular weight of the detected molecules were compared with their theoretical values. In the control the light chain (23424 Da) and heavy chain (52922 Da) were identified. Each ADC subunit


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was detected with higher molecular weight than the corresponding subunit of the control antibody. The mass difference correlates with the mass and number of conjugated molecules. S3 The impact of fluorescent dyes on the nanoDSF measurement was investigated by spiking the three dyes to a blank 10mM histidine buffer at pH5.5 and one containing unlabeled mAb. Samples were analyzed by nanoDSF (see S3) and compared to samples containing no dyes. No wavelength shift from 350 to 330nm was detected for any dye in the protein free buffer. Furthermore, none of the three dyes showed a relevant impact on the unfolding signals of the mAb.

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(29) Strop, P.; Liu, S. H.; Dorywalska, M.; Delaria, K.; Dushin, R. G.; Tran, T. T.; Ho, W. H.; Farias, S.; Casas, M. G.; Abdiche, Y. Location matters: site of conjugation modulates stability and pharmacokinetics of antibody drug conjugates. Chem. & Bio. 2013, 20, 161-7. (30) Sapra, P.; Zhao, H.; Mehlig, M.; Malaby, J.; Kraft, P.; Longley, C.; Greenberger, L. M.; Horak, I. D. Novel delivery of SN38 markedly inhibits tumor growth in xenografts, including a camptothecin-11G-Refractory model. Clin. Cancer Res. 2008, 14, 1888-96. (31) Zhao, R. Y.; Wilhelm, S. D.; Audette, C.; Jones, G.; Leece, B. A.; Lazar, A. C.; Goldmacher, V. S.; Singh, R.; Kovtun, Y.; Widdison, W. C. Synthesis and evaluation of hydrophilic linkers for antibody-maytansinoid conjugates. J. Med. Chem. 2011, 54, 3606-23. (32) Yurkovetskiy, A. V.; Yin, M.; Bodyak, N.; Stevenson, C. A.; Thomas, J. D.; Hammond, C. E.; Qin, L.; Zhu, B.; Gumerov, D. R.; Ter-Ovanesyan, E. A Polymer-Based Antibody-Vinca Drug Conjugate Platform: Characterization and Preclinical Efficacy. Cancer Res. 2015, 75, 3365-72. (33) Lyon, R. P.; Bovee, T. D.; Doronina, S. O.; Burke, P. J.; Hunter, J. H.; Neff-La Ford, H. D.; Jonas, M.; Anderson, M. E.; Setter, J. R.; Senter, P. D. Reducing hydrophobicity of homogeneous antibody-drug conjugates improves pharmacokinetics and therapeutic index. Nat. Biotechnol. 2015, 33, 733-5. (34) Acchione, M.; Kwon, H.; Jochheim, C. M.; Atkins, W. M. Impact of linker and conjugation chemistry on antigen binding, Fc receptor binding and thermal stability of model antibody-drug conjugates. MAbs 2012, 4, 362-72.


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(35) Wakankar, A. A.; Feeney, M. B.; Rivera, J.; Chen, Y.; Kim, M.; Sharma, V. K.; Wang, Y. J. Physicochemical stability of the antibody-drug conjugate trastuzumab-DM1: changes due to modification and conjugation processes. Bioconjugate Chem. 2010, 21, 1588-95. (36) Tumey, L. N.; Li, F.; Rago, B.; Han, X.; Loganzo, F.; Musto, S.; Graziani, E. I.; Puthenveetil, S.; Casavant, J.; Marquette, K. Site Selection: a Case Study in the Identification of Optimal Cysteine Engineered Antibody Drug Conjugates. AAPS J. 2017, 4, 1123-35. (37) Sahin, E.; Grillo, A. O.; Perkins, M. D.; Roberts, C. J. Comparative effects of pH and ionic strength on protein-protein interactions, unfolding, and aggregation for IgG1 antibodies. J. Pharm. Sci. 2010, 99, 4830-48. (38) Ross, P. L.; Wolfe, J. L. Physical and chemical stability of antibody drug conjugates: current status. J. Pharm. Sci 2016, 105, 391-397. (39) Mahler, H.; Friess, W.; Grauschopf, U.; Kiese, S. Protein aggregation: pathways, induction factors and analysis. J. Pharm. Sci 2009, 9, 2909-34.


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Figure 1. DSF thermograms of unconjugated mAb and ADC 1, ADC 2 and ADC 3. (A) The fluorescence ratio (F350 / F330) during a temperature gradient and (B) the corresponding first derivative are shown. (C) The Tm of the CH2 domain is plotted over LogP values of the payload surrogates. Significance (p < 0.05) is represented by *. The error bars represent the standard deviation between three individually prepared samples and if not shown are smaller than the symbols. 310x235mm (300 x 300 DPI)



Figure 2. Semi quantitative self-Interaction analysis by PDSI-BLI. Significance (p < 0.05) is represented by *. The error bars represent the standard deviation of values determined from four independent measurements. 84x63mm (220 x 220 DPI)


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Figure 3. (A) Monomer quantification by SEC-HPLC over 8 weeks at 40°C. Unconjugated mAb, ADC 1, ADC 2 and ADC 3 were measured in triplicates after 0, 2, 4 and 8 weeks of incubation. The error bars represent the standard deviation of values determined from three separate vials and, if not shown are smaller than the symbols. (B) SEC chromatogram of mAb (black) and ADC3 (grew) pre-exposure (solid line) and after 4 weeks at 40°C (dashed line). 308x121mm (300 x 300 DPI)



Figure 4. Aggregation screen using DLS. The pre-exposure sample was compared to samples incubated for 8 weeks at 5°C, 25°C and 40°C. The error bars represent the standard deviation of values determined from three separate vials and, if not shown are smaller than the symbols. 84x64mm (220 x 220 DPI)


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TOC 140x73mm (300 x 300 DPI)


Impact of Payload Hydrophobicity on Stability of Antibody-Drug

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