Antibodies to watch in 2023

Kaplon, Hélène; Crescioli, Silvia; Chenoweth, Alicia; Visweswaraiah, Jyothsna; Reichert, Janice M.

doi:10.1080/19420862.2022.2153410

Cited by 121 publications

(36 citation statements)

References 62 publications

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“…Antibodies are a growing class of therapeutic molecules [12] due to their attractive drug-like properties, including high target selectivity and minimal immunogenic effects [13]. Antibody drug development commonly begins with initial lead molecule discovery.…”

Section: Introductionmentioning

confidence: 99%

Unlockingde novoantibody design with generative artificial intelligence

Shanehsazzadeh¹,

Bachas²,

Kasun³

et al. 2023

Preprint

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Generative artificial intelligence (AI) has the potential to greatly increase the speed, quality and controllability of antibody design. Traditional de novo antibody discovery requires time and resource intensive screening of large immune or synthetic libraries. These methods also offer little control over the output sequences, which can result in lead candidates with sub-optimal binding and poor developability attributes. Several groups have introduced models for generative antibody design with promising in silico evidence, however, no such method has demonstrated de novo antibody design with experimental validation. Here we use generative deep learning models to de novo design antibodies against three distinct targets, in a zero-shot fashion, where all designs are the result of a single round of model generations with no follow-up optimization. In particular, we screen over 400,000 antibody variants designed for binding to human epidermal growth factor receptor 2 (HER2) using our high-throughput wet lab capabilities. From these screens, we further characterize 421 binders using surface plasmon resonance (SPR), finding three that bind tighter than the therapeutic antibody trastuzumab. The binders are highly diverse, have low sequence identity to known antibodies, and adopt variable structural conformations. Additionally, these binders score highly on our previously introduced Naturalness metric, indicating they are likely to possess desirable developability profiles and low immunogenicity. We open source the HER2 binders and report the measured binding affinities. These results unlock a path to accelerated drug creation for novel therapeutic targets using generative AI combined with high-throughput experimentation.

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Section: Introductionmentioning

confidence: 99%

Unlockingde novoantibody design with generative artificial intelligence

Shanehsazzadeh¹,

Bachas²,

Kasun³

et al. 2023

Preprint

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“…Tebentafusp, a novel form of immunotherapy, has shown promising results but is only indicated in patients who are positive for HLA-A*02:01 [6][7][8] . It is not widely used currently and is not available outside the United States, Europe, and a few countries [9] . Thus, chemotherapy remains an important approach for the treatment of liver metastases from UM.…”

Section: Introductionmentioning

confidence: 99%

Regional chemotherapy for uveal melanoma liver metastases

Tao¹,

Luo²,

Li³

et al. 2023

Int J Ophthalmol

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Chemotherapy remains an important approach for the treatment of liver metastases from uveal melanoma (UM). Compared with systemic chemotherapy, regional chemotherapy has similar efficacy and fewer systemic adverse effects. Regional chemotherapy for UM liver metastases includes hepatic artery infusion (HAI), transarterial chemoembolization (TACE), and isolated hepatic perfusion (IHP). In this review, we aim to examine the efficacy of regional chemotherapy and compare HAI, TACE, and IHP in terms of overall survival (OS). The three approaches showed no obvious difference in OS results.

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“… 8 In 2022, three additional bispecific TCEs were approved in both the EU and the US, teclistimab targeting BCMA and CD3 for the treatment of multiple myeloma, mosunetuzumab directed against CD20 and CD3 for the treatment of follicular lymphoma, and tebentafusp, an HLAA*02:01-gp100×CD3 ImmTAC for the treatment of uveal melanoma. 9 , 10 …”

Section: Introductionmentioning

confidence: 99%

eIg-based bispecific T-cell engagers targeting EGFR: Format matters

Kühl

Schäfer

Kraft

et al. 2023

mAbs

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Bispecific antibodies are molecules with versatile modes of action and applications for therapy. They are commonly developed as T-cell engagers (TCE), which simultaneously target an antigen expressed by tumor cells and CD3 expressed by T-cells, thereby inducing T-cell-mediated target cell killing. There is growing evidence that the molecular composition and valency for the target antigen influence the activity of TCEs. Here, the eIg platform technology was used to generate a set of bispecific TCEs targeting epidermal growth factor receptors (EGFR) and CD3. These molecules either included or lacked an Fc region and exhibited one binding site for CD3 and either one or two binding sites for EGFR (1 + 1 or 2 + 1 formats) utilizing different molecular arrangements of the binding sites. In total, 11 different TCE formats were analyzed for binding to target cells and T cells, T cell-mediated killing of tumor cells, and for the activation of T cells (release of cytokines and proliferation of T-cells). Bivalent binding to EGFR strongly increased binding and T cell-mediated killing. However, the molecular composition and position of the CD3-binding arm also affected target cell killing, cytokine release, and T-cell proliferation. Our findings support that screening of a panel of formats is beneficial to identify the most potent bispecific TCE, and that format matters.

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Antibodies to watch in 2023

Cited by 121 publications

References 62 publications

Unlockingde novoantibody design with generative artificial intelligence

Unlockingde novoantibody design with generative artificial intelligence

Regional chemotherapy for uveal melanoma liver metastases

eIg-based bispecific T-cell engagers targeting EGFR: Format matters

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