The collaboration will combine Absci’s Integrated Drug Creation platform with Astrazeneca’s know how in oncology to discover an AI-designed antibody against cancer.
The deal sees AstraZeneca agree to pay artificial intelligence (AI) antibody discovery firm Absci Corporation up to $247 million to co-design an anti-cancer antibody. The sum of money includes an upfront payment, R&D funding and milestone payments, as well as royalties, dependent on product sales.
According to the Absci’s website, its AI platform takes a different approach to discover existing antibodies compared to traditional discovery methods “most drug companies” use. A spokesperson for Absci told BioProcess Insider it can design new therapeutics using the same type of AI that is known for generating images and texts derived from language prompts. When working with large biology datasets, the platform works by applying generative AI to design drug candidates based on target efficacy, manufacturability, as well as other traits.
“AstraZeneca is a leader in developing novel treatments in oncology, and we are excited to collaborate with them to design a therapeutic candidate antibody with the potential to improve the lives of cancer patients,” said Sean McClain, Absci CEO. “This agreement advances Absci’s goal of creating a new generation of life-changing and transformative therapeutics using its AI platform.”
The Integrated Drug Creation platform creates data by measuring millions of protein-protein connections. This data is then used to train Absci’s proprietary AI models and at a later stage, validate antibodies designed using the de novo AI models. The firm said it can advance drug discovery by completing the cycle of data collection, wet-lab validation, and AI-driven design within around six weeks. Its aim is to increase the possibility of successful development outcomes for biologic candidates by expanding drug targets to include those deemed “undruggable” in the past (ion channels and GPCRs).
Together, AstraZeneca and Absci aim to design an antibody therapy for use in oncology.
The application of AI and digitization in all aspects of drug development in the life sciences space has been hailed by many as the solution to some of the challenges faced by the biopharmaceutical industry.
In October, a CPHI’s annual report said, “Over the next five years, AI will become a significant component of our industry “applied across the value chain, from drug discovery to logistics and finance, to become the basis for continued business performance and a catalyst that reduces the cost and time of bringing effective drug therapies to the patients who need them.”
There has also been recent acknowledgement from the US Food and Drug Administration (FDA) that AI and machine learning (ML) are being used more frequently in a variety of therapeutic domains and across the drug development life cycle.
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