Recent Trends of ADCs

Antibody-drug conjugates (ADCs) are rapidly emerging as a transformative approach in cancer therapeutics, offering significant advancements over traditional treatments. The global ADC market is projected to reach $11.29 billion in 2023, with an estimated compound annual growth rate (CAGR) of 9.2% between 2024 and 2030, reflecting substantial economic and scientific interest in this field [1].

ADCs are recognized as one of the fastest-growing drug classes in oncology, driven by their potential to deliver targeted therapies with fewer side effects, broader applications, and a higher therapeutic index compared to conventional chemotherapy.

While ADCs initially focused on hematological malignancies, there is a marked shift toward targeting solid tumors. Approximately 90% of current ADC trials are aimed at solid tumor applications [2]. This shift highlights the urgent need for improved treatments for solid tumors, which often pose greater therapeutic challenges than blood cancers. These challenges include limited antibody penetration into tumor tissues, which hinders drug delivery and reduces efficacy. To overcome these obstacles, researchers are focusing on novel targets within the tumor microenvironment, enabling ADCs to address the complexities of solid tumor biology and expand their therapeutic potential.

Limitation
Despite their promise, ADCs face several challenges that limit their full potential. Drug resistance is a significant concern, as cancer cells can adapt to resist the effects of cytotoxic payloads. Off-target toxicity also poses a problem, with linkers sometimes causing the unintended release of payloads in non-tumorous tissues, leading to adverse effects. Limited tumor penetration further restricts drug delivery, resulting in suboptimal efficacy. The complex structure of ADCs, which combines an antibody, a payload, and a linker, adds to the challenges in both preclinical studies and clinical applications.

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It has been reported that only a small fraction of the administered dose—ranging from 0.0003% to 0.08% per gram of tumor is accumulated in the target site which significantly impacts efficacy [2]. Current payloads also exhibit clinical limitations, such as severe side effects and the development of resistance.

ADC development -linker
Linkers are vital components in antibody-drug conjugates (ADCs) as they connect the antibody and cytotoxic payload, playing a critical role in the stability, payload release, pharmacokinetics (PK), toxicity, and overall therapeutic efficacy of ADCs. An ideal linker should remain stable in the circulatory system to prevent premature drug release and minimize off-target toxicity while enabling specific payload release in the target tissue. Additionally, linkers should feature appropriate conjugation sites to facilitate efficient drug design.

Linkers are classified into two main types: cleavable and non-cleavable. Cleavable linkers are designed to release the payload in response to specific triggers found within the tumor environment. These triggers include low pH, protease activity, or high glutathione levels. Chemical cleavage linkers, such as those based on hydrazone or disulfide bonds, break down through processes like proton lysis or thiol reduction.

Enzyme-cleavable linkers, including glucuronide or peptide-based linkers, are degraded by proteolysis or carbohydrate hydrolysis. Examples of cleavable linkers include valine-citrulline (Val-Cit), phenylalanine-lysine, and glutathione-sensitive disulfide linkers [2].

On the other hand, non-cleavable linkers do not feature a chemical trigger. Instead, they remain attached to the payload even after internalization, with payload release occurring via lysosomal degradation of the antibody.

Recent advancements in linker technology have focused on optimizing chemical triggers and developing novel ones to create highly selective linkers that reduce off-target toxicity. Innovations include the incorporation of hydrophilic elements like phosphate or polyethylene glycol (PEG) to improve solubility and PK, particularly for ADCs with hydrophobic payloads [3].

Shorter linkers have been shown to enhance ADC stability by providing steric shielding for the payload. Additionally, the rise of dual-payload ADCs has necessitated the development of linkers capable of balancing plasma stability with precise cleavage. These dual-payload linkers often employ linear or branching designs with orthogonal reaction handles tailored to the conjugation strategy. [1]

ADC development – payload
Payloads, the cytotoxic agents responsible for killing cancer cells, are critical in determining the anti-tumor efficacy and potential adverse effects of ADCs. Ideal payloads should exhibit high cytotoxicity (with picomolar or nanomolar IC50 values), low immunogenicity, stability in circulation, modifiable functional groups, and suitable water solubility. Among the most common second-generation payloads are tubulin inhibitors, such as auristatins (MMAE, MMAF) and maytansine derivatives (DM1, DM4).

Auristatins target the β-subunit of tubulin to disrupt microtubule formation; MMAE is cell-permeable with bystander activity, whereas MMAF has limited cellular permeability. Maytansines block tubulin polymerization, further hindering cell division. DNA-damaging agents, another major class of payloads, include calicheamicin analogues, duocarmycin analogues, and topoisomerase 1 inhibitors, which cause double-strand breaks, alkylation, or intercalation of DNA. Pyrrolobenzodiazepines (PBD) are also DNA-damaging agents, known for their ability to form inter-strand crosslinks. [4]

In addition to these traditional payloads, novel agents are being explored, such as RNA inhibitors, Bcl-xL inhibitors, NAMPT inhibitors, carmaphycins, and immunomodulators. Emerging technologies like PROTACs (proteolysis-targeting chimeras) and photosensitizers are also finding roles as ADC payloads. Immune ADCs, which use immunomodulators to engage the immune system, are garnering attention for their potential to advance tumor immunotherapy. [4]

The interplay between linkers and payloads is essential for the function of ADCs, as the choice of linker often dictates the suitability of the payload and vice versa. For instance, non-cleavable linkers may not be effective for certain payloads. Specificity is also paramount, requiring antibodies with high affinity for tumor-specific antigens to minimize off-target effects. ADCs with payloads capable of promoting a bystander effect are particularly advantageous for tumors with low or heterogeneous antigen expression, though this must be carefully balanced to avoid toxicity in healthy tissues.

Dual payload
Not all dual-payload ADCs are bispecific; the dual-payload approach focuses on combining multiple mechanisms of action to enhance therapeutic outcomes. By integrating two distinct drugs, dual-payload ADCs aim to reduce the likelihood of drug resistance, mitigate toxic side effects, and improve anti-tumor efficacy. Utilizing multiple payloads can decrease the chances of resistance by targeting cancer cells through diverse pathways. When payloads with different mechanisms of action are combined, they can produce synergistic therapeutic effects, often resulting in superior survival benefits compared to administering individual drugs separately.

Developing dual-payload ADCs requires sophisticated linker designs to accommodate the attachment of two distinct payloads. These designs often rely on traditional linear or branching linkers equipped with orthogonal reaction handles to ensure precise conjugation. However, most dual-payload ADCs remain in the preclinical stage of development. [4] Despite their promise, these ADCs face challenges, including the risk of overlapping toxicities between the two payloads, which can complicate safety profiles. Additionally, their manufacturing process is complex, involving multiple purification steps, which can pose significant challenges in maintaining quality control during production.

Bispecific and multispecific antibodies
Bispecific antibodies (bsAbs) are engineered to recognize two or more epitopes, which can be located on the same or different target molecules. They are constructed using various formats, such as single-chain variable fragments (scFvs), single-domain antibodies (sdAbs), and full-length antibodies with engineered Fc regions. A specialized subset of bsAbs, known as biparatopic antibodies (bpAbs), bind to two distinct, non-overlapping epitopes on the same antigen. This design enhances the internalization and lysosomal trafficking of ADCs, thereby improving payload delivery. BpAbs also address challenges like antigen downregulation by targeting multiple epitopes on the same molecule, ensuring effective binding and therapeutic action. For example, ISB 1442 is a bispecific bpAb that targets two distinct CD38 epitopes while also binding CD47 with low affinity. Similarly, M1231 is a bispecific ADC that targets MUC-1 and EGFR, demonstrating enhanced cell internalization and lysosomal trafficking.[5]

Multispecific antibodies (MsAbs), on the other hand, are designed to bind to two or more epitopes on the same or different targets, offering expanded functionality beyond traditional monoclonal antibodies. MsAbs can crosslink cell surface proteins and recruit immune cells to eliminate tumor cells. These antibodies are constructed from diverse building blocks (BBs), including Fab, scFv, Fc regions, cytokines, and single-domain antibodies. The design and selection of BBs are critical to ensuring that the final MsAb meets the desired product profile and matches the target and mechanism of action. Each format must be carefully optimized for the specific targets or epitopes, as the same configuration may not work universally. MsAbs are being explored for a variety of applications, such as enhancing immune cell recruitment and facilitating crosslinking of distinct cell surface proteins. However, their development often involves more complex manufacturing processes, requiring additional considerations to address production challenges. [6]

De novo Design and AI for ADCs
Artificial intelligence (AI) and machine learning (ML) are increasingly being utilized to enhance the design and development of antibody-drug conjugates (ADCs). AI can identify novel ADC targets with improved tumor selectivity, such as the promising use of AI technologies for neoantigen identification. Additionally, AI plays a significant role in optimizing antibody affinity and biophysical characteristics, facilitating the design of novel linkers. AI can also predict synergistic effects in drug combinations for dual-payload ADCs, with recent advancements in in-silico methods allowing for personalized drug combination therapies. These methods utilize genetic data, drug targets, and molecular information from malignant cell lines to estimate the potential synergistic effects between two payloads.

Other developments include the use of multitasking deep neural networks, which efficiently predict toxicity in vitro, in vivo, and in clinical settings, improving the accuracy and interpretability of toxicity predictions. AI also assists in antibody design, including the creation of de novo antibodies and the optimization of existing antibody properties.

De novo protein design involves generating entirely new proteins from scratch using computational methods, rather than modifying existing ones. This approach allows for the creation of novel binding interfaces that natural proteins cannot access. Tools like Rosetta are used in this process. These newly designed proteins can be employed as building blocks for multispecific antibodies (MsAbs), offering the potential for developing unique binders targeting hard-to-reach molecules and enabling the creation of new pharmacokinetic and pharmacodynamic profiles.

In addition, AI and ML are streamlining the drug development process by creating smarter workflows for ADC design. Hybrid approaches combining AI and ML have shown promise in improving the efficiency and success rates of ADC development, ultimately leading to more effective and targeted therapies. [6]

Concluding remarks
Advancements in linker chemistry, payload design, and multispecific antibody engineering are transforming the ADC landscape, with AI playing a pivotal role in improving precision and efficacy. Innovations in stability, specificity, and chemical triggers ensure accurate payload delivery while reducing off-target toxicity. Bispecific and multispecific antibodies enhance targeting precision, enabling better outcomes in complex tumor environments.

AI streamlines drug development, accelerating target identification, toxicity prediction, and antibody optimization while facilitating personalized medicine. Novel payloads like immunomodulators and dual designs further boost efficacy and address resistance. These advancements position ADCs as key tools in oncology, offering new hope for more effective cancer treatments.

References:
[1] Dual-payload antibody-drug conjugates: Taking a dual shot. Junjie Tao, Yilin Gu, Wei Zhou, Yuxi Wang. 2024, European Journal of Medicinal Chemistry.
[2] Antibody-drug conjugates in the clinic. Edidiong Udofa, Disha Sankholkar, Samir Mitragotri, Zongmin Zhao. 2021, Bioengineering & Translational Medicine.
[3] Antibody-drug conjugates: Recent advances in linker chemistry. Zheng Su, Dian Xiao, Fei Xie, Lianqi Liu, Yanming Wang, Shiyong Fan, Xinbo Zhou, Song Li. 2021, Acta Pharmaceutica Sinica B, pp. 3889-3907.
[4] Antibody-drug conjugates: Recent advances in payloads. Zhijia Wang, Hanxuan Li, Lantu Gou, Wei Li, Yuxi Wang. 2023, Acta Pharmaceutica Sinica B, pp. 4025-4059.
[5] Biparatopic antibodies: therapeutic applications and prospects. David L. Niquille, Kyle M. Fitzgerald, Nimish Gera. 2024, mAbs.
[6] Next generation of multispecific antibody engineering. Daniel Keri, Matt Walker, Isha Singh, Kyle Nishikawa, Fernando Garces. 2024, Antibody Therapeutics, pp. 37-52.

Featured Image: Antibody. Photo courtesy:© 2016 – 2023 Fotolia / Adobe. Used with permission.

Author: William Lee, Ph.D¹

¹ Constructive.Bio The Recodery, LION WORKS, Station Rd E, Whittlesford, Cambridge CB22 4WL, United Kingdom