Written by:
Chief Data Scientist, Biopharmaceuticals R&D, AstraZeneca
Vice president, Biologics Engineering, AstraZeneca
Vice president, R&D IT, AstraZeneca
Antibodies, protein-based therapeutics, and other biologic modalities are a core part of our pipeline due to their ability to target disease at the molecular level and their versatile applications across therapy areas. By harnessing the power of artificial intelligence (AI) we’re accelerating the discovery and design of these promising molecules.
How can AI help design better molecules?
Imagine a world where we can design never-before-seen molecules with just a few clicks. This is the potential AI holds for biologics discovery and design. By leveraging in silico tools, we are expediting the design, build, and testing processes, creating novel, potentially more effective biologics, and substantially reducing timelines. We’re already seeing the positive impact in discovery, identifying early biologic drug hits in weeks instead of months, and gaining invaluable insights in identifying novel targets, testing the developability of drug candidates, and more recently, exploring de novo design of new molecules.
What is de novo design of biologics?
De novo design refers to the process of creating entirely new biological molecules, such as antibodies or proteins, from scratch, rather than relying on existing molecules as a starting point. By exploring an AI-assisted approach to custom-designing biologics with desirable therapeutic properties, we have the potential to develop innovative treatments for diseases that were previously difficult to treat.
Our goal is to use AI and Machine Learning (ML) tools to enhance our biologics discovery, working towards de novo design of new biological drugs. Initially, we are applying our in silico tools to library design, hit identification and lead optimisation, with the aim to speed up the discovery process and enhance our success in drug development.
While it’s still early days, the approach has the benefit of engineering molecules based on specific therapeutic targets or functions, with the goal of developing novel and potentially more effective treatments, faster.
AI and the future of biologics development
We are at the beginning of a revolution in the biologics landscape, which holds promise for highly specific, efficacious, and even curative biologic therapies. AI may not only accelerate timelines; it has the potential to transform the future of drug development.
We continue to invest in augmenting our biologics capabilities with AI and ML approaches. The world of digital biologics is beginning to open up, and AstraZeneca will be at the forefront with AI designed molecules a key feature of its future pipeline.
Critical to our progress is our extensive experience and robust data infrastructure which enables AI to harness our vast data resources and expertise, transforming them into actionable insights. We have the potential to unlock novel target classes and predict the behaviour of biological molecules, helping accelerate our emerging biologics pipeline.
Advances in science and technology have paved the way for the development of next-generation therapeutics, and AstraZeneca is now at the forefront of leveraging AI and ML to transform R&D across therapy areas.
Beyond biologics design, we're embedding data science and AI across every aspect of R&D, from target identification to clinical trials, to automate processes and push the boundaries of science to accelerate the delivery of life-changing medicines for patients.
