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An examination of thermal unfolding and aggregation profiles of a series of developable therapeutic monoclonal antibodies Mark Brader, Tia Estey, Shujun Bai, Roy Alston, Karin Lucas, Steve Lantz, Pavel Landsman, and Kevin Maloney Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/mp400666b • Publication Date (Web): 16 Feb 2015 Downloaded from http://pubs.acs.org on February 18, 2015

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Molecular Pharmaceutics

An examination of thermal unfolding and aggregation profiles of a series of developable therapeutic monoclonal antibodies Mark Brader*, Tia Estey, Shujun Bai‡, Roy Alston, Karin Lucas†, Steven Lantz, Pavel Landsman, Kevin Maloney Protein Pharmaceutical Development, Biogen Idec, 14 Cambridge Center, Cambridge MA 02142 †

Current address: Sarepta Therapeutics, Cambridge MA 02142

‡

Current address: Synageva Biopharma, Lexington MA 02421

*Corresponding Author: Email [email protected]

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ABSTRACT: Screening for pharmaceutically viable stability from measurements of thermallyinduced protein unfolding and short-term accelerated stress underpins much molecule design, selection and formulation in the pharmaceutical biotechnology industry. However, the interrelationships between intrinsic protein conformational stability, thermal denaturation and pharmaceutical stability are complex. There are few publications in which predictions from thermal-unfolding-based screening methods are examined together with pharmaceutically relevant long-term storage stability performance. We have studied eight “developable” therapeutic IgG molecules under solution conditions optimized for large-scale commercial production and delivery. Thermal unfolding profiles were characterized by differential scanning calorimetry (DSC) and intrinsic fluorescence recorded simultaneously with static light scattering (SLS). These molecules exhibit a variety of thermal unfolding profiles under a common reference buffer condition and under individually optimized formulation conditions. Aggregation profiles by SE-HPLC and bioactivity upon long-term storage at 5oC, 25oC and 40oC establish that IgG molecules possessing a relatively wide range of conformational stabilities and thermal unfolding profiles can be formulated to achieve pharmaceutically stable drug products. Our data suggest that a formulation design strategy that increases the thermal unfolding temperature of the Fab transition may be a better general approach to improving pharmaceutical storage stability than one focused on increasing Tonset or Tm of the first unfolding transition.

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Keywords: developability, developable, stability, antibody therapeutics, thermal denaturation, protein aggregation, protein formulation, high throughput screening

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INTRODUCTION Monoclonal antibodies (mAbs) are a prominent class of therapeutics constituting the

overwhelming majority of protein drugs currently in development. There are more than thirty mAb therapeutics approved for human use1, 2 and the emergence of biosimilar3 mAbs and more exotic mAb-based constructs such as bispecifics4 and single domain molecules appears imminent5. MAbs are extensively engineered to achieve favorable binding affinities, pharmacokinetics, effector function, immunogenicity and pharmaceutical properties including stability and solubility6-8. MAbs are susceptible to a variety of degradation mechanisms of which aggregation is one of the most pervasive9, 10. To achieve therapeutic viability, proteins must be robust to the multitude of stresses encountered during production, fill-finish, long-term storage, shipping, in-use handling and administration11. Poor protein stability can limit the therapeutic viability of an otherwise medically significant product. For many mAbs in the biotech pipeline, a minimal target product profile will require solution stability of at least two years at 5oC plus a subsequent period of inuse stability ranging from several hours to several weeks at room temperature. Stabilization of the molecule against interfacial damage, freeze-thaw, shear, agitation, temperature excursion and photo-degradation is also required. Prior to clinical candidate selection, candidate molecules should be screened for their likelihood of fulfilling manufacturing, dosing, and product stability requirements (“developability”). Significant therapeutic and commercial benefits can be realized if more favorable stability can be achieved: these include an improved safety profile, longer shelf-life, greater supply chain flexibility and less restrictive drug handling and administration requirements for the patient. 4


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The putative connection between protein conformational stability and pharmaceutical stability continues to play a major role in guiding protein engineering and formulation design efforts for therapeutic proteins. This approach is based on the premise that conditions that favor the native folded state of the protein will most effectively inhibit degradation pathways that proceed via unfolded or partially unfolded intermediates12. Despite awareness that temperatureinduced protein aggregation is often non-Arrhenius over even relatively small temperature ranges relevant to drug product development13, and rank order obtained at denaturation temperatures might not correspond to that at lower temperatures14-18, automated high throughput techniques that monitor protein conformation while applying a thermal ramp have become fashionable tools in the biotech industry’s quest for more efficient molecule design, developability assessment and expanded formulation design space19-23. Such methods measure onset (Tonset) and midpoint (Tm) temperatures of protein thermal unfolding transitions thereby providing a convenient means to rank samples20, 22, 24-27. Studies based on elevated temperatures and thermal denaturation screens have been applied extensively to support the development of mAb therapeutics. MAbs are multi-domain proteins that have been shown to exhibit a wide range of conformational stabilities even within a given subclass28. Engineering mAbs to increase domain stabilities indicated by Tm and thereby improve overall pharmaceutical stability is an established tenet of therapeutic antibody design and optimization6. Isolated immunoglobulin heavy chain variable domains and isolated CH2 domains have been found to be highly aggregation prone, however, sequence modification resulting in greater thermal stability measured by Tm has been shown to significantly improve aggregation resistance29. Case studies on mAbs are reported where screening for effects on the thermally-induced unfolding profile has been central to identifying favorable formulation 5



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conditions30-36. Several of these studies have used Tm values to screen and identify favorable excipients32, 35-37. For example, a strong inverse correlation between aggregation rate at 40oC versus Tm for various excipient and formulation conditions was reported for an IgG1 mAb32. Bajaj et al.38 examined in detail the significance of conformational versus colloidal stability indicated by the second virial coefficient (B22). These authors concluded that protein structural conformation and not B22 related to the long-term irreversible aggregation of an IgG2 mAb. Another study examined the stability of eight mouse mAbs and concluded that DSC was predictive of accelerated and long term storage for six out eight of the mAbs studied39. Cases in which conformational stability did not clearly predict physical stability of mAbs have also been reported. Matheus et al.40 found that Tm did not necessarily correspond to storage stability at 40oC measured by SE-HPLC and SDS-PAGE for an IgG1 mAb. Fesinmeyer et al.41 identified significant differences in the agitation-induced and 45oC accelerated stability of three IgG2 mAbs, yet these proteins were not readily differentiated by their Tm(1) values. Moreover, numerous studies have examined mAb aggregation kinetics and conformational stability under harsh conditions of acidic pH values (pH 3-4) and/or forced degradation temperatures in the range 45-73 oC15, 18, 33, 34, 37, 41-44. The use of very high temperature stress (viz. 65oC) for identifying favorable mAb excipient conditions has occasionally been demonstrated37, 45. Although it is stated frequently that enhanced conformational stability should lead to decreased aggregation rates upon long term storage, there are few published reports that have tested this hypothesis directly using pharmaceutically authentic stability protocols and formulation compositions26. Consequently, there is a limited frame of reference to relate mAb accelerated screening data to long term storage stability and pharmaceutical robustness. Despite the widespread application and apparent success of accelerated temperature- and Tm-based screening 6


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methods as a practical development approach, the connection between conformational stability parameters obtained from thermal unfolding experiments and the pharmaceutical storage stability of mAbs seems ambiguous. In view of: (i) the lack of published literature for mAbs reporting both the thermal unfolding parameters and corresponding pharmaceutical storage stability data (ii) the questionable connection between stability toward thermal denaturation and stability at pharmaceutical storage temperatures and (iii) apparent ambiguity regarding the practical utility of thermal unfolding-based methods applied to mAbs - we were prompted to examine the thermal unfolding and long term aggregation profiles of a series of mAbs established as pharmaceutically developable molecules. We designed stable, pharmaceutically robust formulations, conducted long term stability studies then characterized retrospectively the thermal unfolding profiles using DSC and intrinsic fluorescence collected simultaneously with static light scattering (SLS). Here we report these thermal unfolding profiles recorded under a common “screening buffer” (or reference formulation) condition and under formulation conditions optimized individually and independently for each molecule.

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MATERIALS AND METHODS

Monoclonal Antibodies. The monoclonal antibodies used in this study were produced at Biogen Idec (Cambridge, Massachusetts). mAbs1-6 are IgG1 and mAbs7-8 are IgG4 subtypes. MAb6 and mAb7 are aglycosylated. For DSC and Optim1000 thermal scanning studies, mAb samples were prepared in a single common screening buffer and respectively in eight individually optimized formulation buffers.

These solutions were prepared by dialysis using a 10-kDa

NMWCO membrane at 2-8oC for at least 24 hours then diluted to 1.0 mg/mL using the corresponding dialysis buffers. The composition of the screening buffer was 20 mM sodium citrate, 150 mM NaCl at pH 6.0. Formulation excipients, buffers and salts were USP grade (or higher) and purchased from Sigma Aldrich. The screening buffer composition and the DSC data collection procedure used herein were selected to correspond to the conditions under which DSC data for 17 monoclonal antibodies were reported previously28.

The compositions of the

individually optimized formulations are not disclosed, but comprised typical generally recognized as safe (GRAS) pharmaceutical excipients. The term “optimized formulation” is used herein to denote that each formulation was designed to confer acceptable overall stability with respect to all stresses and degradation products applicable to a commercial therapeutic mAb. The optimized formulations were designed independently of one another and did not follow a common formulation design paradigm. Differential scanning calorimetry. Differential scanning calorimetry measurements were performed using a MicroCal capillary VP-DSC system (Northampton, Massachusetts) with Origin VPViewer2000 version 2.0.64 controlling software. Sample measurements in the DSC 8


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were made at a concentration of 1.0 mg/mL total protein. The thermograms were generated by scanning the temperature from 20oC to 95oC at a rate of 1oC/min using the medium feedback mode. Multipeak fitting/deconvolution of the DSC thermograms and calculation of unfolding transition points (Tm values) as deconvoluted peak maxima were performed using Origin 7 software. The number of peaks in the deconvolution model was increased from 2 peaks until a satisfactory fit was reached as estimated by the chi-square test. The numeric data for the DSC thermograms and their deconvoluted components were then exported from Origin into Excel and SigmaPlot 12.3 software, in order to perform Gaussian fitting of the first deconvolution component of each thermogram. This enabled estimation of the first thermal transition onset (Tonset), defined as 10% of (CPmax - CPmin), where CPmax is CP peak value and CPmin is the background value at the thermogram start. Intrinsic fluorescence and SLS thermal scanning measurements. The Optim-1000 instrument (Pall Corporation, Port Washington, New York) was used to perform thermal scans in fluorescence and static light scattering output modes. In a typical run, two multiple cuvette arrays (MCAs) of 16 cuvettes each and of 9 µL cuvette capacity were loaded with 1.0 mg/mL sample solutions. The total array of 16 duplicate samples was formed with the eight mAbs in two assay solution conditions (screening buffer and optimized formulation). The thermal ramping was then performed simultaneously for all array samples in a single 2 hour run from 35°C to 95°C, at a scan rate of 30°C per hour. Thermal scan data from protein intrinsic fluorescence and light scattering outputs were thus acquired during the single run, at excitation laser wavelength 266 nm. Upon the acquisition, the raw spectral data from the instrument were pre-processed into the thermoscan light scattering and fluorescence emission intensity ratio 350:330nm (F350/330) output modes using the ”Primary Analysis” suite of Optim-1000 analytical 9



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software (Avacta, York, UK). For further processing and analysis, the pre-processed data were then exported in numeric form into Microsoft Excel. For non-linear (sigmoid) fits and calculations of thermal inflection temperatures (i.e. midpoint (Tm) and onset (Tonset) temperatures) the data were further exported into SigmaPlot 12.3 software in order to achieve satisfactory non-linear fits (estimated by their R2 values). In cases where multiple transitions were apparent from the Optim-1000 thermograms, the thermoscan data sets were divided into the corresponding subsets, so as to apply satisfactory sigmoid fits to the individual transitions in a multi-transition thermal unfolding/aggregation model. The midpoint temperatures of the thermal transitions were then obtained as solutions of the respective sigmoid fit equations at ½×(Ymax - Ymin). The onset temperatures of the first thermal fluorescence or light scattering transitions were estimated as solutions of the respective sigmoid fit equations at 10%×(Ymax - Ymin), where Y is the corresponding output value (either scatter intensity or F350/330); Ymin is the saturation output value at the respective sigmoid start plateau and Ymax – the value at the sigmoid end plateau. Four run repeats, of the same sample array at the same thermal scan rate, demonstrated high precision and accuracy of measurements, with run-to-run variability of calculated onsets and midpoints not exceeding ±2°C for the test mAb samples (not shown). Isothermal storage stability studies.

Formulation stability studies were conducted

independently for each of the eight mAbs using type I glass vials with elastomeric stoppers in a variety of container closure and fill volume configurations. Vials were autoclaved and filled under sterile conditions representative of commercial drug product manufactured under cGMP (current good manufacturing practice) conditions.

Samples at respective formulation

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concentrations were incubated in stability chambers maintained at 5±3ºC, 25±2ºC with 60% relative humidity and 40±2ºC with 75% relative humidity and protected from light. SE-HPLC conditions (mobile phase, column, buffer and run parameters) were used as per assay protocols developed individually for the respective mAb products (not disclosed herein). The SE-HPLC profiles were analyzed for relative content (%) of high molecular weight (HMW) soluble aggregates in the mAb product. The latter was determined as area-under-curve of the respective high molecular weight (HMW) peak relative to that of the main peak of the chromatogram assigned to the mAb product. Biological (pharmaceutical) activity of each product was assessed in the individual assay targeting the pharmaceutically relevant property of the product – typically a binding assay against the relevant model target. The individual assay protocols used in these assessments are not described herein.

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RESULTS

Differential scanning calorimetry. DSC thermograms measured for the eight mAbs are shown in the upper panels of Figure 1 and Figure 2 together with the mathematical deconvolution of each profile into Gaussian components. Each mAb was evaluated under two solution conditions: the “screening buffer” condition of 20 mM citrate, 150 mM NaCl, pH 6.0 and an “optimized formulation” condition which refers to a formulation optimized specifically for each molecule to confer acceptable overall pharmaceutical stability. Thermograms recorded in the screening buffer are shown in the left panels (labeled I) and those recorded in optimized formulations are shown on the right panels (labeled II). Tm values obtained from the Gaussian components are listed in Table 1 together with transition onset values corresponding to the first thermal transition (Tonset). For mAb1, mAb2, mAb3, mAb5, and mAb8 satisfactory fits using three components were obtained under both formulation conditions, whereas four components were required to fit mAb4 and mAb7. A satisfactory three component fit was obtained for mAb6 under the screening buffer condition whereas a four component fit was required under the optimized formulation condition. Thermal unfolding monitored by intrinsic fluorescence. Thermograms generated by monitoring F350/330 as a function of temperature are shown in the lower panels of Figure 1 and Figure 2 (purple curves). Transition mid-points and onsets are given in Table 1. The basis of this detection method is the change in polarity of the microenvironment around the aromatic amino acids (predominantly tryptophan) as the protein unfolds which leads to a change in the 12


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average emission wavelength of the fluorescence. Typically a red-shift occurs from 330 nm in a protein where a tryptophan is fully buried to 350 nm where it is exposed completely to water46 resulting in an increase in F350/330. This red-shift behavior was indeed observed for seven of the eight mAbs studied here, however, mAb4 (Figure 1) exhibited a decrease in F350/330 upon heating to 70oC followed by an increase upon further heating. For several of the mAbs, more than one F350/330 transition was resolved and fit to sigmoid curves. Simultaneous monitoring by SLS and intrinsic fluorescence. The Optim1000 instrument provides the capability to record simultaneously the intrinsic fluorescence and static light scattering (SLS) outputs in a single run which are presented together with the corresponding DSC thermograms in Figure 1 and Figure 2. The lower panels of Figure 1 and Figure 2 (orange curves) show the SLS signals for each protein over the course of the thermal ramp. For some of these samples (mAb1, mAb2, mAb5, mAb6) the SLS data could be fit with a single transition and for others (mAb3, mAb4, mA7, mAb8) two or three transitions were apparent. Because SLS is sensitive to apparent molecular weight, the rapid increase in SLS at the transition onset indicates that aggregation begins to occur at that temperature under the specific conditions of this experimental measurement. This signal adds an orthogonal indication of thermal stability such that aggregation and spectral microenvironments of the intrinsic fluorophores are probed simultaneously as the protein unfolds. Because these signals correspond to distinct structural and kinetic phenomena, the transitions detected by each method are not expected to coincide. From close inspection of Figure 1 and Figure 2 it is apparent that many of these molecules show significant spectroscopic perturbations at temperatures where no increase in SLS has occurred. Similarly, comparison of the SLS thermal profiles with the DSC profiles shows 13



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that for certain molecules a domain unfolds before an increase in SLS signal occurs (e.g. mAb2 and mAb7). These observations highlight the value of recording the SLS signal as it is possible to distinguish spectroscopic- and DSC-detected transitions that may not be associated with an aggregation event (e.g. the unfolding of an aggregation-relevant mAb domain). One example of this is mAb4 which shows an initial intrinsic fluorescence transition over the range of ~45-60oC with no concomitant increase in SLS. However, the second fluorescence transition (Tm(2) = 66.4oC, screening buffer) corresponds closely to first the SLS transition (Tm(1) = 67.0±1, screening buffer). This observation is supported by the corresponding DSC data which shows no enthalpy detected for the first fluorescence transition. These results are in accord with previous studies of IgG molecules that have found that the least conformationally stable regions of a multidomain protein are not necessarily the most aggregation-prone47. This demonstrates the value of the SLS signal to help pinpoint which domain needs attention from a protein engineering or formulation optimization viewpoint. The Optim1000 instrument provides a convenient way to generate this data using a small quantity of protein. Pharmaceutical storage stability. It is beyond the scope of this report to present stability data for the entire set of pharmaceutical quality attributes. Nevertheless, aggregation and biological activity are critical quality attributes associated closely with the integrity of protein higher-order structure and therefore are central to overall pharmaceutical stability. Aggregation time-course profiles measured by SE-HPLC of the eight mAbs in their individually optimized formulations stored quiescent in glass vials at 5oC, 25oC and 40oC are shown in Figure 3. Overall, these data show that each of these molecules exhibit adequate pharmaceutical stability characteristics with respect to aggregation during long term storage. After two years at 5oC and after six months at 25oC, aggregate levels for all these molecules increase by less than 2%. An inspection of linear 14


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fits to these data indicate that the 40oC data conform quite well to zero order kinetics as do the 25oC data (although less so than the 40oC data). Aggregation rates calculated as monthly degradation rates from the slopes of linear fits are included in Table 1. In contrast, several of the 5oC datasets appear to depart from zero order kinetics and the time-course profiles are generally more irregular. The aggregate quantities formed at 5oC are relatively small and the impact of analytical and experimental variability is greater for the two year duration of this time-course, thus the overall relative error in the 5oC SE-HPLC data is expected to be much higher. Storage stability data for mAbs1-7 as measured by percent biological activity in the respective assay specified for each of the mAbs (see Methods) are shown in Figure 4. The levels of biological activity after storage respectively at 25oC for 6 months and after 3 months at 40oC are shown (except for mAb5 for which the 40oC data was not collected). These data show that after 6 months at 25oC mAb1, mAb2, mAb3, mAb4, mAb6, and mAb7 retained ≥ 90% of initial biological activity, and mAb5 retained 81%. After 3 months at 40oC, the biological activity values ranged from 56% for mAb2 to 97% for mAb7. A typical bioassay specification for biologic products requires the product to retain at least 80% biological activity at end of shelflife. Applying this criterion, it can be concluded that good pharmaceutical stability could be claimed for these molecules for several months at room temperature and for at least two years at 5oC (data not shown). It is noteworthy that the range of stabilities observed across this series of molecules is quite large at 40oC both for the SE-HPLC data and for the biological activity after 3 months. These data show that a mAb candidate molecule exhibiting an aggregation rate as high as 3.6% per month at 40oC, can achieve good storage stability at 5oC and 25oC.

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DISCUSSION The antibody molecule is a heterotetramer composed of two identical heavy chains (~450 residues each) and two identical light chains (~220 residues each). Each light chain forms a variable domain (VL) and constant domain (CL) and each heavy chain forms a variable domain (VH) and three constant domains (CH1, CH2, CH3). A complex thermal unfolding behavior is thus expected due to the multi-domain nature of these molecules. The variable region is the main source of antibody diversity and is considered primarily responsible for stability variations between IgGs of identical subclass28. A DSC thermal scan of an IgG1 mAb typically resolves three unfolding transitions comprising a large enthalpy peak attributed to unfolding of the Fab segment, flanked by two smaller peaks attributed to the CH2 domain at lower temperature and the CH3 domain at higher temperature28. This profile can vary and can be difficult to assign unambiguously. Sometimes only two peaks are apparent31, 32, 48 with the largest enthalpy peak occurring at either lower or higher temperature. Occasionally four transitions are resolved7, 49 which is believed to occur if the Fab domains do not unfold cooperatively. It has been shown that the stability of the Fab segment is significantly affected by the sequence of the variable domains49. Diversity amongst the DSC profiles is apparent from the data of Figure 1 and Figure 2 for the six IgG1 mAbs (mAbs1-6) and two IgG4 mAbs studied here. Temperature Dependence of Conformational Stability and Pharmaceutical Stability The thermodynamic stability of a globular protein is given by the Gibbs energy difference, ∆Gu, between the denatured and native states. Formulation excipients can increase ∆Gu either by increasing the free energy of the unfolded state or decreasing the free energy of the native state. There are well characterized examples of rational formulation strategies utilizing excipients to 16


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increase ∆Gu with a resulting favorable impact on aggregation rates50. Thus there is a valid logic for utilizing a read-out of protein conformational stability as a practical approach to screening and ranking formulations and candidate molecules24, 25, 51. However, using thermal denaturation as the basis for assessing conformational stability introduces some complications. It is evident from inspection of the modified Gibbs-Helmholz equation (Equation 1) why two proteins with the same Tm could have different thermodynamic stabilities at a temperature lower than the Tm, because this will depend on ∆Cp, the heat capacity change between the native and denatured forms, which could be different. Equation 1

∆Gu(T) = ∆Hm (1-T/Tm) + ∆Cp[(T-Tm) – Tln(T/Tm)]

Where ∆Hm is the value of ∆Hu at Tm. It is also worth noting that although changes in free energy are widely used to evaluate the effect of temperature on the stability of proteins, the hydrophobic interaction, its temperature dependence and its role in stabilizing proteins is still an evolving and incompletely understood aspect of fundamental biochemistry52. Temperatures relevant to protein pharmaceuticals span a wide range: -70oC and -20oC for frozen bulk storage, 5oC for long term storage, room temperature and above for patient use. There is much scope for the temperature dependence of the hydrophobic interaction to influence the outcome of the thermal denaturation process in an unpredictable manner, especially if one extends this range further for accelerated stability testing (e.g. ~40-70oC). There are additional reasons why prediction of low temperature stability from accelerated temperatures is not straightforward. Proteins can aggregate via a variety of mechanisms which may change as temperature changes. Not all aggregation mechanisms proceed via an unfolded or partially unfolded state53. The multi-domain nature of mAbs further 17



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complicates the unfolding process giving rise to the possibility of interactions between the multiple transition states or domains. The relationship between conformational stability and aggregation propensity is also more complex as the least conformationally stable domain may not necessarily be the aggregation-prone domain. In the context of a pharmaceutical drug product, stability refers to meeting pre-defined acceptance criteria (specifications) pertaining to quality attributes. The desire for rapid screening (< 1 month) with small protein quantities early in development encourages approaches that push (beyond) the limits of reasonable accelerated temperatures in an attempt to find molecules and conditions most likely to meet or exceed ultimate acceptance criteria. Although Arrhenius behavior is sometimes observed for proteins, predicting aggregation rates is difficult and (unlike small molecules) use of Arrhenius approaches has made little impact12, 13, 18. As a vivid illustration for a therapeutic mAb, Drenski et al. showed that an Arrhenius extrapolation from aggregation kinetics measured in the 50-60oC temperature range would predict a pharmaceutical shelf-life for this molecule greater than the age of the Earth15. Kayser et al.54 studied the aggregation of five different therapeutic monoclonal antibodies at temperatures 10-15oC below Tm and found non-Arrhenius behavior. The expectation of non-Arrhenius protein aggregation over even relatively small temperature windows relevant for product development is the general rule, as has been reviewed elegantly by Wang and Roberts13. It is, nevertheless, instructive to consider to what extent less aggressive accelerated temperatures further removed from the first unfolding transition, and the possibility of comparative excipient screening for a given protein, could be helpful. Even if aggregation rates at 40oC are poorly predictive of those at 5oC and 25oC, robustness to brief exposures of ~40oC is 18


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certainly an important pharmaceutical attribute in and of itself. Datasets presented herein pertain to the stability of these molecules upon isothermal incubation at 40oC (SE-HPLC and bioactivity) and under thermal denaturing conditions thus providing a perspective on how indicative these measurements were with respect to long term storage stability. Stability Ranking From Isothermal Accelerated Temperature Data An examination of the DSC first transition onset values (Tonset) in screening buffer and the linear aggregation rates at 40oC in optimized formulations shows there is a strong inverse correlation (R2=0.90) between these measurements (Figure 5). This suggests that the aggregation rates measured for quiescent storage at 40oC are influenced significantly by unfolded species corresponding to the first DSCdetectable unfolding transition (Tm(1)). The Tonset values in optimized formulations and the linear aggregation rates in optimized formulations show a more modest correlation (R2=0.63) (Figure 5). This implies that some of the optimized formulations contain excipients that confer a stabilizing effect with respect to quiescent storage yet shift the unfolding transitions to lower temperatures. This interpretation is supported by the plots of Figure 6(a) and (b) which show the shift in DSC Tm(1) and Tonset values respectively for the optimized formulations relative to the screening buffer. These plots show that mAbs1-8 exhibit a collection of positive, negative and negligible shifts. If the first DSC transition were a significant correlate of improved pharmaceutical storage stability, then a greater preponderance of positive transition shifts would be expected from these plots. Plotting the SE-HPLC linear aggregation rates at 40oC versus 25oC indicates no correlation between rates at these two temperatures and accordingly there is no correlation (R2=0.22) between the DSC first transition and the linear aggregation rates at 25oC) (supplementary material Figure S1). The lack of correlation of Tonset and Tm(1) to 5oC storage data is also apparent and is exemplified by mAb3 and mAb8 which represent the most and least 19



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stable of the series with respect to long term storage stability at 5oC. However, the first DSC transitions of these molecules coincide with one another to within experimental error (67.2±0.1 and 67.0±0.1, respectively for the optimized formulations). Overall we infer that Tonset and first Tm from DSC measurements correlate well with protein aggregation rates at high temperatures because there is expected to be a significant population of unfolded protein as one approaches the first Tm. However, at lower temperatures (i.e. at the pharmaceutically relevant temperature 25oC and below), there is expected to be a much smaller fraction of the unfolded species and it is likely that other aggregation pathways/mechanism contribute significantly to the observed aggregation rate, particularly aggregation mechanisms that are driven by colloidal mechanisms. Complexity in the relationship between 40oC stability and long term storage stability is also apparent from the biological activity data of Figure 4. MAb6 exhibits impressive stability at 25oC and 40oC, retaining 96% of initial activity after 3 months at 40oC. This excellent stability is mirrored by its favorable long term storage stability at 5oC and 25oC as measured by SE-HPLC (Figure 3). However, based on thermal unfolding screening data, the relatively early initial unfolding onsets detected by DSC, intrinsic fluorescence and SLS, would rank this molecule as one of the least stable of the series. Furthermore, its long term storage stability at 40oC as measured by SE-HPLC (Figure 3) also ranks it relatively unfavorably. MAb6 thus represents an example of a mAb that possesses excellent pharmaceutical stability yet ranks relatively poorly in this series based on screening measurements of aggregation and unfolding at temperatures ≥40oC. MAb7 shows a similar lack of correlation in this series. Both mAb6 and mAb7 are aglycosylated which has been shown to decrease CH2 stability and affect rates of aggregation under acidic conditions8, 42. The relatively low Tm(1) values for mAb7 of 54.6±0.1oC (screening buffer) and 59.4±0.5 oC (optimized formulation) are consistent with this Tm-lowering effect, 20


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however, the data of Figure 3 and Figure 4 show that this molecule possesses excellent pharmaceutical storage stability at 5oC and 25oC and ranks as one of the most stable relative to the other molecules studied here. It is evident from the 5oC storage stability data in Figure 3 that some of the aggregation profiles do not conform well to linear kinetics. This observation gives a clue that the mechanisms of aggregation prevailing at this temperature can differ from those that dominate at 25oC and 40oC which are approximated well by linear equations. Some of the mAbs show trends that would suggest that the order of the reaction has changed at 5oC (i.e mAb1, mAb2, mAb3). As noted previously, it is well recognized that Arrhenius kinetics usually don’t apply to protein aggregation thus extrapolation from accelerated stability to long term storage conditions is not practicable. The origins of the non-Arrhenius behavior are not always known, however, the most likely possibilities are that the rate determining step changes with temperature or that the enthalpy of unfolding is a function of temperature13. Previous degradation studies of mAbs have also shown linear aggregation kinetics at very high temperatures and shown that two proteins can have nearly the same Tm yet orders of magnitude difference in the aggregation rates, presumably because one unfolds to create a more aggregation-competent surface than the other15. Collectively the data for these eight mAbs showed that the 40oC quiescent aggregation rates and DSC first transition onsets and Tm(1) values were not helpful parameters for ranking pharmaceutical storage stability of these eight mAbs at 5oC and 25oC. With respect to accelerated screening by isothermal incubation at 40oC, the mAbs in their optimized formulations exhibited linear degradation rates no more than 3.6% per month. This value may provide some empirical reference for identifying developable mAbs based on their 40oC aggregation rates.

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Thermal Unfolding Monitored by Intrinsic Fluorescence. The F350/330 profiles exhibited a single sigmoidal transition for mAb1, mAb2, mAb5 and mAb6, whereas two or three transitions were resolved for the other molecules. The single transition exhibited by mAb2 in the screening buffer resolved into two transitions in the optimized formulation. For the series of eight mAbs, the Tonset and first Tm values detected by DSC correlated closely with the respective parameters detected by intrinsic fluorescence (Supplementary Material Figure S3). Curiously, one of the eight mAbs studied here (mAb4) displays a decreasing fluorescence emission ratio (F350/330 ) indicative of a blue shift upon heating. This resolved as two descending sigmoidal transitions over the temperature range ~40 to 70oC. This behavior appears to be unusual for mAbs, although a similar phenomenon has been reported previously55. The blue-shift implies that the average tryptophan environment becomes more hydrophobic, or more shielded from the solvent as the temperature increases over this range. Generally the expectation is that unfolding results in greater solvent exposure to hydrophobic residues buried in the native fold which produces a fluorescence red-shift. However, the intrinsic fluorescence profile represents the global average of all intrinsic fluorophores in different local environments in the molecule which includes approximately twenty tryptophan groups distributed throughout the mAb structure. In our experiment the excitation wavelength of 266 nm also excites tyrosine fluorescence which contributes to the profile. Fluorescence intensity is affected by quenching effects which can arise both from solvent and intramolecularly from various Trp-neighboring amino acid residues. During thermal protein denaturation, aggregated species are formed in which the Trps are buried in hydrophobic regions not exposed to the polar water phase. Thus multiple competing effects contribute to the resultant fluorescence emission intensity profile and wavelength maximum. This is exemplified by the data for mAb4 where two descending F350/330 transitions are resolved 22


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followed by an increasing F350/330 transition. The first transition occurs with a Tonset of 47.7oC and is observed only in the intrinsic fluorescence profile. Examination of the emission spectra acquired during the run (data not shown) reveals that the first transition originates from 350 nm emission decrease with no shift in peak maximum. Whereas the second F350/330 transition involves an emission maximum blue shift. This profile is observed for both screening and optimized formulations. However, the accompanying SLS profile for mAb4 shows that the first F350/330 transition is not accompanied by an aggregation event and the corresponding DSC profile indicates that it does not give rise to an enthalpy change detected by DSC. Evidently this first F350/330 emission ratio decrease arises from a perturbation in the extrachromophoric environment of the fluorophores which involves quenching of some of the 350 nm-emitting (buried) tryptophan chromophores. The underlying conformational event (possibly a rearrangement of structure and/or solvent at an initial unfolding stage) is, however, structurally subtle enough to be thermally invisible to the DSC measurement. The second F350/330 transition exhibits a mid-point of 66.4oC and originates from a moderate (~2 nm) blue shift in emission maximum at excitation wavelength of 266 nm (not shown). This occurs at a similar value to the first enthalpy component of the DSC profile (Tm = 68.6oC) suggesting that this blue shift transition is related to the CH2 or Fab unfolding. Previously it has been shown that differences in the extent of protein aggregation, in structural compactness, or simply in the structural arrangement of tryptophan residues in unfolded states can significantly change the magnitude of the shift observed during the unfolding transition46. It has also been shown that hydrophobic clusters, α-helices, β-sheets, and other native-like structures can exist even under strongly denaturing conditions56. In view of the diversity of structures represented by the mAbs studied here, it is likely that at least some of the 23



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variation in fluorescence-detected thermal unfolding profiles arises from differences in the respective unfolded states and aggregates formed. Thakkar et al. examined the blue-shift behavior of an IgG1 and showed that this effect occurred in the absence of excipients as well as in the presence of 100 mM arginine and 500 mM sucrose55. Similarly, our results show that the qualitative DSC and fluorescence profiles are highly comparable for mAb4 in screening buffer and optimized formulation. The transition midpoints are shifted to higher temperatures for mAb4 in the optimized formulation, consistent with conformational stabilization. Even though the spectroscopic origins of this blue-shifted fluorescence phenomenon are unclear, evidently the transitions are sensitive to the nature of the excipients. Importantly, the stability data in Figure 3 and 4 show that despite this unusual spectroscopic behavior, mAb4 could indeed be stabilized as a pharmaceutically viable formulation, achieving pharmaceutical stability comparable to the other mAbs studied here including remarkably good stability at 40oC. It is concluded that the observation of a decreasing fluorescence emission ratio F350/330 profile upon heating or a pre-unfolding fluorescence-detected transition does not necessarily translate into a pharmaceutical stability problem. Clearly, the dynamic nature of proteins and their capacity for subtle conformational effects can give rise to significant and unusual spectroscopic effects that may have little or no bearing on ultimate pharmaceutical stability. Selecting Developable Molecules. One major challenge of biopharmaceutical development is to select clinical candidate molecules robust to ultimate manufacturing and product stress requirements while achieving rapid progression from the Discovery organization into phase I clinical trials. Consequently, key decisions on candidate molecules and formulation conditions 24


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may need to be made based on accelerated screening data and only a few weeks of real-time stability monitoring even though the ultimate storage requirement of the drug product is a timescale of years. Often it is the long-term storage stability that is the most challenging to achieve, optimize and predict. It is instructive to examine the DSC Tm values in the context of developable mAb molecules. A previously reported DSC study of 17 humanized mAbs used an identical screening buffer composition and DSC methodology as the present study28 and therefore provides an excellent comparison to our results. In that study the thermal stability of the Fab transition (Tm) was found to span a broad range from 57 to 82oC, however, storage stability data was not presented and pharmaceutical “developability” for the series was unclear. For the DSC profiles shown in Figure 1 and Figure 2, we have tentatively assigned transitions to the Fab segment based on the relative magnitudes of the component endotherms49, 57. Under the screening buffer condition these values range from 63.3±0.1 for mAb6 to 77.7±0.1oC for mAb3. It is noteworthy that only one of the 17 mAbs characterized by Garber and Demarest28 exhibited a lower Fab Tm than the lowest reported here (mAb6). The onset temperatures for the first transition span a range from 47.5 ±1.6oC for mAb7 to 63.1±0.2oC for mAb1 under the screening buffer condition. The significant implication of these data is that mAbs exhibiting a relatively broad range of Fab Tm values can be formulated into pharmaceutically stable liquid drug products. Recently Neergaard et al. reported a detailed study comparing IgG1 and IgG4 mAbs possessing identical variable regions58. These authors found an inherent lower conformational stability and higher propensity for soluble aggregate formation for the IgG4 molecule (albeit at 40oC). The lower conformational stability of the IgG4 subclass versus IgG1 has been noted previously28, and the Tm values of the two IgG4 molecules in our study (mAb7 and mAb8) 25



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conform to this expectation. However, it is noteworthy that both the IgG4 molecules included in our series achieved excellent pharmaceutical storage stability profiles under optimized formulation conditions. Although the 40oC stability of mAb7 is the poorest of the eight mAbs studied, this is likely attributed to its comparatively low first unfolding transition (Tm(1 )= 54.6oC). This illustrates a key broader conclusion from our study: while the Tm of the first unfolding transition correlates quite well with aggregation rates measured at accelerated temperatures (Figure 5) it does not correlate well with stability at pharmaceutical storage temperatures. Collectively, these results show that despite lower conformational stability of the IgG4 subclass measured by thermal unfolding, pharmaceutical stability comparable to that attainable with IgG1 molecules can be attained for IgG4 molecules in optimized formulations. Implications For Formulation Design. Commonly used excipients that stabilize proteins against aggregation include sugars, polyols, surfactants and amino acids. These additives exert their stabilization effects via different and incompletely understood mechanisms 50, 59, 60. Stabilitylimiting aggregation of mAbs can be mediated via different domains depending upon solution conditions and the structure of the aggregate formed depends on the denaturation method. For example, the Fab segment has been shown to be more sensitive to heat whereas the Fc segment is more sensitive to decreasing pH57. Because protein formulation development requires balancing a multitude of competing degradation pathways, it is understandable that optimal stability for different mAbs may be achieved at different pH values and ionic strengths. Specific buffer ion effects, territorial ion binding61 and the effect of stabilizers on unfolded and folded states add further to the diversity of formulation conditions creating the design space for a specific molecule. Protein solubility appears to be another important factor. In a formulation study of an IgG1 mAb, Banks et al. showed recently that the stabilizing effect of the excipients derived from 26


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their ability to solubilize the native state, not by the increase of protein conformational stability induced by their presence62. These authors found there was little correlation between the mAb-1 Tm values and the percent dimer determined after 11 months storage at 4◦C whereas at 63◦C the rank order of aggregation by SE-HPLC in the presence of these excipients followed the DSC data more closely. The propensity for non-covalent aggregation is related to hydrophobic surface topography, charge distribution and charge complementarity, so it is plausible that different formulation conditions (e.g. high versus low ionic strength) could differentially affect aggregation-prone regions of a mAb. In view of the multifaceted nature of mAb aggregation and excipient stabilization mechanisms, it is instructive to consider whether any generalizable interpretations could be made from the thermal unfolding and pharmaceutical storage data presented herein. The optimized formulations possess commercially viable pharmaceutical stabilities and it is assumed that they confer pharmaceutical stabilities superior to the screening buffer conditions, although these were not compared directly. Nevertheless, several pertinent observations arise from comparison of the DSC profiles obtained under these optimized formulation conditions relative to the screening buffer. As noted previously, the DSC Tonset and Tm(1) values show a variety of positive, negative and negligible shifts for the optimized formulations relative to the screening buffers (Figure 6(a) and (b)). Similarly, positive, negative and negligible shifts were evident from the Tonset values measured by SLS (Figure 6c)). These results suggest that neither the temperature of the first thermal unfolding transition nor the shift in SLS Tonset were particularly good indicators of whether or not the overall pharmaceutical stability had been improved in this series. The highest temperature DSC transition (likely CH3) generally shows little or no shift associated with the change from screening buffer to optimized formulation (Table 1). Intriguingly, the transitions 27



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assigned tentatively to the Fab unfolding show a shift to higher temperature for the optimized formulation for all except mAb2 (no shift) and mAb3 which exhibits a shift to lower temperature (Figure 6d). This observation suggests that the thermal shift associated with the Fab segment represents a more generalized indicator of pharmaceutical formulation stabilization. Further insight into the origins of the formulation stabilization is apparent from inspection of the individual DSC, intrinsic fluorescence and SLS profiles. The effect of optimizing the mAb2 formulation (Figure 1) was to resolve the first and second DSC thermal transitions, creating a shift to higher temperatures for Tm(2) and a shift to lower temperatures for Tm(1). The SLS data show that Tm(1) does not correspond to an aggregation event whereas the second thermal unfolding does. Similarly, the intrinsic fluorescence profile for mAb2 also resolves into two transitions in the optimized formulation - the first with a lower Tm and the second with a higher Tm than in the screening buffer. The DSC and intrinsic fluorescence data for mAb2 suggests that the effect of the optimized formulation condition was to alter domain unfolding cooperativity and thereby decouple the unfolding of a domain, or part of a domain, (likely CH2) from the Fab domains. The result was to stabilize the Fab segment and significantly shift the aggregation onset temperature to a higher value. A similar effect is apparent for mAb6 (Figure 2) where the formulation optimization resulted in the resolution of an additional transition in the DSC profile, with a decrease in the first Tm but an increase in the Fab Tm. Our observation that the Fab transition correlates best with overall pharmaceutical stability of this series of eight mAbs is consistent with the recent findings of Kim et al. who performed a detailed study of the global aggregation behavior of an IgG1 across a broad range of pH and NaCl conditions relevant to pharmaceutical formulations63. These workers found that although different structural features

28


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were apparent for aggregates from different solution conditions, commonality of the thioflavin T binding characteristics suggested Fab unfolding as a key step in non-native aggregate formation. In summary, these studies demonstrate that DSC, intrinsic fluorescence and SLS can be combined to provide useful insights into the mAb thermal unfolding profile by identifying aggregation prone transitions and better discerning the impact of formulation conditions on conformational stability. Both mAb2 (Figure 1) and mAb6 (Figure 2) illustrate how a rapidscreening or simplistic analysis of first transition thermal shifts would fail to recognize the stabilization associated with the optimized formulations. Rather than considering thermal shift methodologies as a rapid screen for formulation ranking, our study shows the value of characterizing the entire DSC thermal unfolding profile for its overall response to formulation variables. A careful deconvolution of the DSC profile into components can help reveal subtleties of the thermal unfolding process and the differential impact of excipients on individual domains. Specifically, the shift associated with the Fab segment appears to be a useful indicator of improved formulation stability. The first DSC unfolding transition is also valuable in the context of a strong correlation to SE-HPLC data at 40oC and robustness toward high temperature excursions which in itself is a desirable product attribute. The SLS signal recorded simultaneously with intrinsic fluorescence can help identify aggregation prone domains and thus help pinpoint which domain needs attention from a protein engineering or formulation optimization viewpoint. All mAbs in this study, except one, exhibited spectral red-shifts in intrinsic fluorescence emission upon heating. The exception being mAb4 which produced a blue-shift transition over the range ~60-70oC followed by a red-shift transition upon further heating. This molecule was also distinguished by a fluorescence transition in the pre-unfolding range of ~40-50oC. We infer that these unusual spectroscopic characteristics are not necessarily 29



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harbingers of adverse pharmaceutical stability, but can indeed be associated with a candidate that represents a stable developable molecule.

CONCLUSIONS A series of eight monoclonal antibodies established as “developable” molecules were

characterized. The DSC thermograms of this series exhibit appreciable diversity with three transition components apparent in some cases and four in others. We observed that formulation optimization shifts transition midpoints, can impact the cooperativity of unfolding between domains, and formulation ingredients can differentially influence domains. Considerable diversity was also observed in the intrinsic fluorescence profiles accompanying the thermal unfolding of these molecules. Current understanding of protein formulation design recognizes that not all excipient stabilization mechanisms are based on enhancement of folded stability and not all aggregation mechanisms involve an unfolded or partially unfolded state. Both conformational stability and colloidal protein interactions need to be considered in the selection and development of viable candidates32, 64. Consequently, the expectation that a Tm value can reflect the integral of these effects as a global correlate to mAb pharmaceutical stability seems unlikely. Nevertheless, we observed that a positive thermal shift of the Fab segment occurred for six out of eight mAbs for an optimized formulation relative to a single common screening buffer. Whereas the shift associated with the first unfolding transition appeared a lot more random. It is inferred that a formulation design strategy that increases the thermal unfolding temperature of the Fab transition may be a better general approach than one focused on increasing Tonset or Tm of the first unfolding transition. Overall, we conclude that IgG molecules possessing a relatively

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wide range of conformational stabilities and thermal unfolding profiles can be formulated to achieve pharmaceutically stable drug products.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the Biogen Idec Analytical Department for analytical test support and the Biogen Idec Technology Investment program. We wish to thank Ping Yeh for knowledgeable discussions and support regarding the development of the optimized formulations. We thank Laura Silvian, Steven Berkowitz and Wayne Reed for reviewing draft versions of the manuscript and helpful suggestions.

SUPPORTING INFORMATION AVAILABLE

Plot of aggregation rate by SE-HPLC at 25oC versus 40oC for optimized formulations; Plot of Tm(1) by DSC versus aggregation rate by SE-HPLC at 25oC for optimized formulations; Plots for optimized and screening buffer conditions of Tm(1) measured by intrinsic fluorescence versus Tm(1) measured by DSC. This information is available free of charge via the Internet at http://pubs.acs.org/.

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Abstract/TOC Graphic for: An examination of thermal unfolding and aggregation profiles of a series of developable therapeutic monoclonal antibodies Mark Brader*, Tia Estey, Shujun Bai, Roy Alston, Karin Lucas†, Steven Lantz, Pavel Landsman, Kevin Maloney 35x14mm (300 x 300 DPI)


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Figure 1. Thermal unfolding profiles for four mAbs: mAb1, mAb2, mAb3, mAb4 measured in a screening buffer (I) and in individually optimized formulations (II). The upper panels for each molecule show the measured DSC thermal unfolding profile (black) and the mathematically deconvoluted component transitions. The lower panels for each molecule show the thermal unfolding profiles detected by intrinsic fluorescence (purple) and static light scattering (brown). The vertical dashed lines indicate the thermal transition midpoints and the vertical solid lines indicate the transition onsets. 191x138mm (150 x 150 DPI)



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Figure 2. Thermal unfolding profiles for four mAbs: mAb5, mAb6, mAb7, mAb8 measured in a screening buffer (I) and in an individually optimized formulation (II). The upper panels for each molecule show the measured DSC thermal unfolding profile (black) and the mathematically deconvoluted component transitions. The lower panels for each molecule show the thermal unfolding profiles detected by intrinsic fluorescence (purple) and static light scattering (brown). The vertical dashed lines indicate the thermal transition midpoints and the vertical solid lines indicate the transition onsets. 189x137mm (150 x 150 DPI)


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Figure 3. Storage stability data measured by SE-HPLC showing increase in percent aggregate at (a) 40oC with linear regression lines (b) 25oC with linear regressions lines and (c) 5oC with lines connecting data points. 248x749mm (300 x 300 DPI)



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Figure 4. Bioactivity of mAbs in optimized formulations after storage at 25oC for 6 months (black bars) and 40oC for 3 months (gray bars). Data is not shown for mAb8 or mAb5 at 40oC. 89x48mm (300 x 300 DPI)


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Figure 5. First transition onset measured by DSC for optimized formulations (diamonds) and screening buffer (circles) plotted versus aggregation rate at 40oC measured by SE-HPLC on the optimized formulations. Least squares regression lines are shown yielding R2 values of 0.90 and 0.63 for the screening buffer and optimized formulation conditions respectively. 122x84mm (300 x 300 DPI)



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Figure 6. Shift in thermal unfolding transitions calculated as the difference between value recorded in optimized formulation and value recorded in screening buffer corresponding to (a) The first Tm value measured by DSC (b) The Tonset value measured by DSC (c) The Tonset value measured by SLS (d) the Tm value(s) for each component of the Fab transition measured by DSC. 237x630mm (300 x 300 DPI)


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Screening Buffer

Molecule

mAb1 mAb2 mAb3 mAb4 mAb5 mAb6 mAb7 mAb8

Output

Optimized Formulations

Ton

Tm(1)

Tm(2)

Tm(3)

Tm(4)

Ton

Tm(1)

Tm(2)

Tm(3)

Tm(4)

DSC

63.1(±0.2)

70.2(±0.1)

74.3(±0.1)

82.9(±0.1)

−

65.1(±0.4)

71.2(±0.1)

75.0(±0.1)

83.1(±0.1)

−

F350/330 Sc266

63.6(±1.1) 68.9(±1.1)

69.0(±1.0) 71.4(±0.9)

− −

− −

− −

63.2(±0.3) 67.4(±0.2)

69.6(±0.7) 71.0(±0.6)

− −

− −

− −

DSC

52.8(±1.6)

66.5(±1.0)

73.5(±0.1)

82.3(±0.1)

−

50.1(±2.0)

56.5(±0.8)

73.5(±0.3)

82.7(±0.2)

−

F350/330 Sc266

55.7(±0.4) 68.3(±1.1)

64.0(±0.9) 71.9(±1.1)

− −

− −

− −

43.3(±1.8) 73.0(±3.2)

52.7(±0.5) 76.3(±2.9)

74.5(±0.5) 81.2

− −

− −

DSC

59.7(±0.2)

68.7(±0.2)

77.7(±0.1)

83.9(±0.1)

−

58.7(±0.7)

67.2(±0.1)

76.9(±0.1)

84.0(±0.1)

−

F350/330 Sc266

58.5(±1.2) 69.2(±0.5)

64.0(±1.4) 71.3(±0.1)

70.3(±2.2) 75.7(±0.8)

75.4(±1.5) −

− −

56.0(±0.8) 70.2(±0.7)

60.3(±1.3) 73.0(±1.1)

64.3(±1.1) 83.9(±0.7)

72.3(±1.1) −

− −

DSC

62.7(±0.7)

68.6(±0.8)

70.2(±0.2)

77.8(±0.3)

85.6(±0.1)

63.3(±0.3)

70.0(±1.4)

72.0(±0.1)

78.2(±0.2)

85.6(±0.1)

F350/330 Sc266

47.7 64.6(±0.6)

54.4 67.0(±1.0)

66.4(±0.8) 76.2(±1.3)

84.2 −

− −

51.7(±0.8) 76.1(±1.4)

55.6(±0.4) 89.8(±2.1)

69.7(±1.0) −

80.7(±0.5) −

− −

DSC

60.8(±0.1)

67.2(±0.3)

70.0(±0.1)

82.0(±0.1)

−

63.1(±0.5)

69.1(±0.4)

71.7(±0.3)

83.2(±0.1)

−

F350/330 Sc266

63.0(±1.2) 66.5(±0.8)

67.6(±1.1) 68.6(±1.0)

− −

− −

− −

65.5(±0.4) 68.6(±0.9)

69.8(±1.0) 71.1(±1.1)

− −

− −

− −

DSC

54.2(±0.1)

63.3(±0.1)

70.6(±0.5)

82.6(±0.1)

−

54.4(±0.5)

60.1(±0.2)

66.2(±0.1)

71.8(±0.1)

82.7(±0.1)

F350/330 Sc266

50.8(±0.3) 61.0(±0.3)

59.8(±0.2) 62.9(±0.0)

− −

− −

− −

52.5(±2.1) 63.1(±0.6)

61.1(±0.8) 65.2(±0.8)

− −

− −

− −

DSC

47.5(±1.6)

54.6(±0.1)

68.0(±0.2)

77.5(±0.2)

80.0(±0.1)

54.4

59.4(±0.5)

70.4(±0.1)

78.8(±0.5)

81.5(±0.1)

F350/330 Sc266

48.1(±1.5) 65.1(±1.1)

54.4(±0.3) 68.4(±0.2)

70.3(±0.7) 73.2(±1.5)

− −

− −

53.5(±0.3) 66.7(±0.5)

62.9(±1.3) 70.3(±0.7)

72.1(±1.0) 75.6(±0.9)

− 80.0(±0.8)

− −

DSC

59.4(±0.5)

66.1(±0.1)

77.4(±0.2)

80.3(±0.1)

−

60.6(±0.1)

67.0(±0.1)

78.6(±0.2)

81.0(±0.1)

−

F350/330 Sc266

58.7(±0.8) 72.9(±0.1)

64.9(±0.9) 74.7(±0.7)

76.5(±1.4) 77.8(±0.6)

− −

− −

58.6(±1.3) 68.0(±1.5)

65.1(±0.6) 71.2(±1.1)

76.9(±0.9) 77.5(±1.0)

− −

− −

Agg rate @40oC

Agg rate @25oC

1.01

0.27

2.77

0.14

1.47

0.25

1.12

0.12

1.9

0.21

2.3

0.04

3.62

0.084

1.09

0.038

Table 1. Thermal unfolding transition onsets (Tonset) and mid-points (Tm) measured in screening buffer (20 mM citrate, 150 mM NaCl, pH 6.0) and under individually optimized formulation conditions using: DSC, intrinsic fluorescence emission ratio at 350/330 nm (F350/330) and scattering at 266 nm (Sc266). Standard deviations from duplicate runs are shown. Values without standard deviations were taken from a single run. Green-shaded cells indicate DSC transitions assigned tentatively to the Fab domains. Aggregation rates (Agg rate) from linear fit to SE-HPLC measurements of aggregation upon storage at 40oC and 25oC are given in % aggregate per month.


Examination of Thermal Unfolding and ... - ACS Publications

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