Pages: 189 - 198 Abstract: AbstractThe manufacturability assessment and optimization of bispecific antibodies (bsAbs) during the discovery stage are crucial for the success of the drug development process, impacting the speed and cost of advancing such therapeutics to the Investigational New Drug (IND) stage and ultimately to the market. The complexity of bsAbs creates challenges in employing effective evaluation methods to detect developability risks in early discovery stage, and poses difficulties in identifying the root causes and implementing subsequent engineering solutions. This study presents a case of engineering a bsAb that displayed a normal solution appearance during the discovery phase but underwent significant precipitation when subjected to agitation stress during 15 L Chemistry, Manufacturing, and Control (CMC) production Leveraging analytical tools, structural analysis, in silico prediction, and wet-lab validations, the key molecular origins responsible for the observed precipitation were identified and addressed. Sequence engineering to reduce protein surface hydrophobicity and enhance conformational stability proved effective in resolving agitation-induced aggregation. The refined bsAb sequences enabled successful mass production in CMC department. The findings of this case study contribute to the understanding of the fundamental mechanism of agitation-induced aggregation and offer a potential protein engineering procedure for addressing similar issues in bsAb. Furthermore, this case study emphasizes the significance of a close partnership between Discovery and CMC teams. Integrating CMC’s rigorous evaluation methods with Discovery’s engineering capability can facilitate a streamlined development process for bsAb molecules. PubDate: Wed, 29 May 2024 00:00:00 GMT DOI: 10.1093/abt/tbae013 Issue No:Vol. 7, No. 3 (2024)
Pages: 199 - 208 Abstract: AbstractBackgroundEarly assessment of antibody off-target binding is essential for mitigating developability risks such as fast clearance, reduced efficacy, toxicity, and immunogenicity. The baculovirus particle (BVP) binding assay has been widely utilized to evaluate polyreactivity of antibodies. As a complementary approach, computational prediction of polyreactivity is desirable for counter-screening antibodies from in silico discovery campaigns. However, there is a lack of such models.MethodsHerein, we present the development of an ensemble of three deep learning models based on two pan-protein foundational protein language models (ESM2 and ProtT5) and an antibody-specific protein language model (PLM) (Antiberty). These models were trained in a transfer learning network to predict the outcomes in the BVP assay and the bovine serum albumin binding assay, which was developed as a complement to the BVP assay. The training was conducted on a large dataset of antibody sequences augmented with experimental conditions, which were collected through a highly efficient application system.ResultsThe resulting models demonstrated robust performance on canonical mAbs (monospecific with heavy and light chain), bispecific Abs, and single-domain Fc (VHH-Fc). PLMs outperformed a model built using molecular descriptors calculated from AlphaFold 2 predicted structures. Embeddings from the antibody-specific and foundational PLMs resulted in similar performance.ConclusionTo our knowledge, this represents the first application of PLMs to predict assay data on bispecifics and VHH-Fcs. PubDate: Thu, 30 May 2024 00:00:00 GMT DOI: 10.1093/abt/tbae012 Issue No:Vol. 7, No. 3 (2024)
Pages: 209 - 220 Abstract: AbstractFc optimization can significantly enhance therapeutic efficacy of monoclonal antibodies. However, existing Fc engineering approaches are sub-optimal with noted limitations, such as inappropriate glycosylation, polyclonal libraries, and utilizing fragment but not full-length IgG display. Applying cell cycle arrested recombinase-mediated cassette exchange, this study constructed high-quality monoclonal Fc libraries in CHO cells, displayed full-length IgG on cell surface, and preformed ratiometric fluorescence activated cell sorting (FACS) with the antigen and individual FcγRs. Identified Fc variants were quantitatively evaluated by flow cytometry, ELISA, kinetic and steady-state binding affinity measurements, and cytotoxicity assays. An error-prone Fc library focusing on the hinge-CH2 region was constructed in CHO cells with a functional diversity of 7.5 × 106. Panels of novel Fc variants with enhanced affinity and selectivity for FcγRs were isolated. Particularly, clone 2a-10 (G236E/K288R/K290W/K320M) showed increased binding strength towards FcγRIIa-131R and 131H allotypes with kinetic dissociation constants (KD-K) of 140 nM and 220 nM, respectively, while reduced binding strength towards FcγRIIb compared to WT Fc; clone 2b-1 (K222I/V302E/L328F/K334E) had KD-K of 180 nM towards FcγRIIb; clone 3a-2 (P247L/K248E/K334I) exhibited KD-K of 190 nM and 100 nM towards FcγRIIIa-176F and 176 V allotypes, respectively, and improved potency of 2.0 ng/ml in ADCC assays. Key mutation hotspots were identified, including P247 for FcγRIIIa, K290 for FcγRIIa, and K334 for FcγRIIb bindings. Discovery of Fc variants with enhanced affinity and selectivity towards individual FcγR and the identification of novel mutation hotspots provide valuable insights for further Fc optimization and serve as a foundation for advancing antibody therapeutics development. PubDate: Fri, 21 Jun 2024 00:00:00 GMT DOI: 10.1093/abt/tbae017 Issue No:Vol. 7, No. 3 (2024)
Pages: 221 - 232 Abstract: AbstractBackground: Several HER2-targeting antibody–drug conjugates (ADC) have gained market approval for the treatment of HER2-expressing metastasis. Promising responses have been reported with the new generation of ADCs in patients who do not respond well to other HER2-targeting therapeutics. However, these ADCs still face challenges of resistance and/or severe adverse effects associated with their particular payload toxins. Eribulin, a therapeutic agent for the treatment of metastatic breast cancer and liposarcoma, is a new choice of ADC payload with a distinct mechanism of action and safety profile. Methods: We’ve generated a novel HER2-tageting eribulin-containing ADC, BB-1701. The potency of BB-1701 was tested in vitro and in vivo against cancer cells where HER2-expressing levels vary in a large range. Bystander killing effect and toxin-induced immunogenic cell death (ICD) of BB-1701 were also tested. Results: In comparison with HER2-targeting ADCs with DM1 and Dxd payload, eribulin-containing ADC demonstrated higher in vitro cytotoxicity in HER2-low cancer cell lines. BB-1701 also effectively suppressed tumors in models resistant to DM1 or Dxd containing ADCs. Mode of action studies showed that BB-1701 had a significant bystander effect on HER2-null cells adjacent to HER2-high cells. In addition, BB-1701 treatment induced ICD. Repeated doses of BB-1701 in nonhuman primates showed favorable pharmacokinetics and safety profiles at the intended clinical dosage, route of administration, and schedule. Conclusions: The preclinical data support the test of BB-1701 in patients with various HER2-expressing cancers, including those resistant to other HER2-targeting ADCs. A phase I clinical trial of BB-1701 (NCT04257110) in patients is currently underway. PubDate: Tue, 25 Jun 2024 00:00:00 GMT DOI: 10.1093/abt/tbae019 Issue No:Vol. 7, No. 3 (2024)
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