High-Throughput and Format-Agnostic Mispairing Assay for Multispecific Antibodies Using Intact Mass Spectrometry.

Multispecific antibodies have gained significant importance in a broad indication space due to their ability to engage multiple epitopes simultaneously and to thereby overcome therapeutic barriers. With growing therapeutic potential, however, the molecular complexity increases, thus intensifying the demand for innovative protein engineering and analytical strategies. A major challenge for multispecific antibodies is the correct assembly of light and heavy chains. Engineering strategies exist to stabilize the correct pairing, but typically individual engineering campaigns are required to arrive at the anticipated format. Mass spectrometry has proven to be a versatile tool to identify mispaired species. However, due to manual data analysis procedures, mass spectrometry is limited to lower throughputs. To keep pace with increasing sample numbers, we developed a high-throughput-capable mispairing workflow based on intact mass spectrometry with automated data analysis, peak detection, and relative quantification using Genedata Expressionist. This workflow is capable of detecting mispaired species of ∼1000 multispecific antibodies in three weeks and thus is applicable to complex screening campaigns. As a proof of concept, the assay was applied to engineering a trispecific antibody. Strikingly, the new setup has not only proved successful in mispairing analysis but has also revealed its potential to automatically annotate other product-related impurities. Furthermore, we could confirm the assay to be format-agnostic, as shown by analyzing several different multispecific formats in one run. With these comprehensive capabilities, the new automated intact mass workflow can be applied as a universal tool to detect and annotate peaks in a format-agnostic approach and in high-throughput, thus enabling complex discovery campaigns.

Attribute Analytics Performance Metrics from the MAM Consortium Interlaboratory Study.

The multi-attribute method (MAM) was conceived as a single assay to potentially replace multiple single-attribute assays that have long been used in process development and quality control (QC) for protein therapeutics. MAM is rooted in traditional peptide mapping methods; it leverages mass spectrometry (MS) detection for confident identification and quantitation of many types of protein attributes that may be targeted for monitoring. While MAM has been widely explored across the industry, it has yet to gain a strong foothold within QC laboratories as a replacement method for established orthogonal platforms. Members of the MAM consortium recently undertook an interlaboratory study to evaluate the industry-wide status of MAM. Here we present the results of this study as they pertain to the targeted attribute analytics component of MAM, including investigation into the sources of variability between laboratories and comparison of MAM data to orthogonal methods. These results are made available with an eye toward aiding the community in further optimizing the method to enable its more frequent use in the QC environment.

New Peak Detection Performance Metrics from the MAM Consortium Interlaboratory Study.

The Multi-Attribute Method (MAM) Consortium was initially formed as a venue to harmonize best practices, share experiences, and generate innovative methodologies to facilitate widespread integration of the MAM platform, which is an emerging ultra-high-performance liquid chromatography-mass spectrometry application. Successful implementation of MAM as a purity-indicating assay requires new peak detection (NPD) of potential process- and/or product-related impurities. The NPD interlaboratory study described herein was carried out by the MAM Consortium to report on the industry-wide performance of NPD using predigested samples of the NISTmAb Reference Material 8671. Results from 28 participating laboratories show that the NPD parameters being utilized across the industry are representative of high-resolution MS performance capabilities. Certain elements of NPD, including common sources of variability in the number of new peaks detected, that are critical to the performance of the purity function of MAM were identified in this study and are reported here as a means to further refine the methodology and accelerate adoption into manufacturer-specific protein therapeutic product life cycles.

Integrated transcriptomic and proteomic evaluation of gentamicin nephrotoxicity in rats.

Gentamicin is an aminoglycoside antibiotic, which induces renal tubular necrosis in rats. In the context of the European InnoMed PredTox project, transcriptomic and proteomic studies were performed to provide new insights into the molecular mechanisms of gentamicin-induced nephrotoxicity. Male Wistar rats were treated with 25 and 75 mg/kg/day subcutaneously for 1, 3 and 14 days. Histopathology observations showed mild tubular degeneration/necrosis and regeneration and moderate mononuclear cell infiltrate after long-term treatment. Transcriptomic data indicated a strong treatment-related gene expression modulation in kidney and blood cells at the high dose after 14 days of treatment, with the regulation of 463 and 3241 genes, respectively. Of note, the induction of NF-kappa B pathway via the p38 MAPK cascade in the kidney, together with the activation of T-cell receptor signaling in blood cells were suggestive of inflammatory processes in relation with the recruitment of mononuclear cells in the kidney. Proteomic results showed a regulation of 163 proteins in kidney at the high dose after 14 days of treatment. These protein modulations were suggestive of a mitochondrial dysfunction with impairment of cellular energy production, induction of oxidative stress, an effect on protein biosynthesis and on cellular assembly and organization. Proteomic results also provided clues for potential nephrotoxicity biomarkers such as AGAT and PRBP4 which were strongly modulated in the kidney. Transcriptomic and proteomic data turned out to be complementary and their integration gave a more comprehensive insight into the putative mode of nephrotoxicity of gentamicin which was in accordance with histopathological findings.

A comparative integrated transcript analysis and functional characterization of differential mechanisms for induction of liver hypertrophy in the rat.

The main goal of the present work was to better understand the molecular mechanisms underlying liver hypertrophy (LH), a recurrent finding observed following acute or repeated drug administration to animals, using transcriptomic technologies together with the results from conventional toxicology methods. Administration of 5 terminated proprietary drug candidates from participating companies involved in the EU Innomed PredTox Project or the reference hepatotoxicant troglitazone to rats for up to a 14-day duration induced LH as the main liver phenotypic toxicity outcome. The integrated analysis of transcriptomic liver expression data across studies turned out to be the most informative approach for the generation of mechanistic models of LH. In response to a xenobiotic stimulus, a marked increase in the expression of xenobiotic metabolizing enzymes (XME) was observed in a subset of 4 studies. Accumulation of these newly-synthesized proteins within the smooth endoplasmic reticulum (SER) would suggest proliferation of this organelle, which most likely is the main molecular process underlying the LH observed in XME studies. In another subset of 2 studies (including troglitazone), a marked up-regulation of genes involved in peroxisomal fatty acid ß-oxidation was noted, associated with induction of genes involved in peroxisome proliferation. Therefore, an increase in peroxisome abundance would be the main mechanism underlying LH noted in this second study subset. Together, the use of transcript profiling provides a means to generate putative mechanistic models underlying the pathogenesis of liver hypertrophy, to distinguish between subtle variations in subcellular organelle proliferation and creates opportunities for improved mechanism-based risk assessment.

Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers.

The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with "omics" data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinical chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.

The enhanced value of combining conventional and "omics" analyses in early assessment of drug-induced hepatobiliary injury.

The InnoMed PredTox consortium was formed to evaluate whether conventional preclinical safety assessment can be significantly enhanced by incorporation of molecular profiling ("omics") technologies. In short-term toxicological studies in rats, transcriptomics, proteomics and metabolomics data were collected and analyzed in relation to routine clinical chemistry and histopathology. Four of the sixteen hepato- and/or nephrotoxicants given to rats for 1, 3, or 14days at two dose levels induced similar histopathological effects. These were characterized by bile duct necrosis and hyperplasia and/or increased bilirubin and cholestasis, in addition to hepatocyte necrosis and regeneration, hepatocyte hypertrophy, and hepatic inflammation. Combined analysis of liver transcriptomics data from these studies revealed common gene expression changes which allowed the development of a potential sequence of events on a mechanistic level in accordance with classical endpoint observations. This included genes implicated in early stress responses, regenerative processes, inflammation with inflammatory cell immigration, fibrotic processes, and cholestasis encompassing deregulation of certain membrane transporters. Furthermore, a preliminary classification analysis using transcriptomics data suggested that prediction of cholestasis may be possible based on gene expression changes seen at earlier time-points. Targeted bile acid analysis, based on LC-MS metabonomics data demonstrating increased levels of conjugated or unconjugated bile acids in response to individual compounds, did not provide earlier detection of toxicity as compared to conventional parameters, but may allow distinction of different types of hepatobiliary toxicity. Overall, liver transcriptomics data delivered mechanistic and molecular details in addition to the classical endpoint observations which were further enhanced by targeted bile acid analysis using LC/MS metabonomics.

Performance of novel kidney biomarkers in preclinical toxicity studies.

The kidney is one of the main targets of drug toxicity, but early detection of renal damage is often difficult. As part of the InnoMed PredTox project, a collaborative effort aimed at assessing the value of combining omics technologies with conventional toxicology methods for improved preclinical safety assessment, we evaluated the performance of a panel of novel kidney biomarkers in preclinical toxicity studies. Rats were treated with a reference nephrotoxin or one of several proprietary compounds that were dropped from drug development in part due to renal toxicity. Animals were dosed at two dose levels for 1, 3, and 14 days. Putative kidney markers, including kidney injury molecule-1 (Kim-1), lipocalin-2 (Lcn2), clusterin, and tissue inhibitor of metalloproteinases-1, were analyzed in kidney and urine using quantitative real-time PCR, ELISA, and immunohistochemistry. Changes in gene/protein expression generally correlated well with renal histopathological alterations and were frequently detected at earlier time points or at lower doses than the traditional clinical parameters blood urea nitrogen and serum creatinine. Urinary Kim-1 and clusterin reflected changes in gene/protein expression and histopathological alterations in the target organ in the absence of functional changes. This confirms clusterin and Kim-1 as early and sensitive, noninvasive markers of renal injury. Although Lcn2 did not appear to be specific for kidney toxicity, its rapid response to inflammation and tissue damage in general may suggest its utility in routine toxicity testing.

Use of SELDI MS to discover and identify potential biomarkers of toxicity in InnoMed PredTox: a multi-site, multi-compound study.

A serious bottleneck in the drug development pipeline is the inability of current pre-clinical toxicology evaluation methods to predict early on, and with good accuracy, that a drug candidate will have to be removed from development due to toxicology/safety issues. The InnoMed PredTox consortium attempted to address this issue by assessing the value of using molecular profiling techniques (proteomics, transcriptomics, and metabonomics), in combination with conventional toxicology measurements, on decision making earlier in pre-clinical safety evaluation. In this study, we report on the SELDI-TOF-MS proteomics component of the InnoMed PredTox project. In this large scale, multi-site, multi-compound study, tissue and plasma samples from 14-day in vivo rat experiments conducted for 16 hepato- and nephro-toxicants with known toxicology endpoints (including 14 proprietary compounds and 2 reference compounds) were analyzed by SELDI-TOF-MS. We have identified seven plasma proteins and four liver proteins which were shown to be modulated by treatment, and correlated with histopathological evaluations and can be considered potential biomarker candidates for the given toxicology endpoints. In addition, we report on the intra- and inter-site variations observed based on measurements from a reference sample, and steps that can be taken to minimize this variation.