The rise of antibody-drug conjugates (ADCs)

Multiple high-profile ADC deals were signed recently.

• Merck and Daiichi Sankyo will codevelop and market three ADCs in a deal that could be worth up to $22 billion (press release).

• Eli Lilly will acquire Mablink Bioscience, a pre-clinical biotechnology company pioneering the development of next-generation ADCs via its PSARLink™ proprietary platform (press release).

• GSK entered an exclusive license agreement with China’s Hansoh Pharma for a B7-H4 targeted ADC with a $85 million upfront payment and a total of $1.485 billion in potential payments (press release).

• BioNTech will license a Her3 targeted ADC from Suzhou-based MediLink Therapeutics with potential $1 billion milestone payments. (press release).

ADC consists of three main parts: the antibody responsible for the selective recognition of the cancer cell surface antigen, the drug payload responsible for killing the cancer cell once released inside it, and the linker connecting the antibody and payload parts. It combines both the advantages of highly specific targeting ability (antibody) and highly potent killing effect (cytotoxic payload) to achieve accurate and efficient elimination of cancer cells.

How AI and data science can help ADC drug design?

• Analyzing omics data to identify and prioritize tumor cell-specific antigens as the drug targets, predict treatment response and off-target effect, and select combination therapies.

• Using protein structure prediction and generative AI to design antibodies with higher binding affinity to the targeted antigens.

• Utilizing chemical-based AI to design payload agents with improved cytotoxicity and linkers with higher stability during systemic circulation and more efficient release of the payload in the targeted cells.

Other news to highlight

• Two weeks ago, we shared the FDA’s list of approved AI/ML devices up to October 05, 2022. The list was renewed on October 19, 2023, with 171 devices were added.

• The largest brain single-cell data and related studies were published in Science, Science Advances, and Science Translational Medicine, enabling more precise data- and AI-driven study of the brain.

• Two AI reports were released by Nathan Benaich and Kaggle, respectively, highlighting the recent advances in AI, especially generative AI and LLM.

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