While the design and discovery of antibody drugs remains challenging, Artificial Intelligence offers great promise for accelerating and improving the development of therapeutic antibodies
Words by Karan Karayi
In the heart of South London, where an old biscuit factory once stood, a remarkable transformation is taking place. Gone are the days of mixers and ovens; instead, robotic arms, incubators, and DNA sequencing machines have taken their place. This is the home of LabGenius, a groundbreaking company, a company on a mission to revolutionize antibody engineering using the power of Artificial Intelligence (AI) and automation.
The power of antibodies in disease treatment
Antibodies, the body’s natural defence against disease, play a crucial role in our immune system. These specialised proteins are designed to recognise and attach themselves to foreign invaders, effectively neutralizing them and clearing them from our system. Recognizing the potential of antibodies, pharmaceutical companies have been developing synthetic versions to treat various diseases, including cancer and organ rejection.
Creating synthetic antibodies, however, is a complex and time-consuming process. Traditional methods rely on human protein designers to sift through an overwhelming number of potential combinations of amino acids, hoping to find the right structure that will effectively target the disease. This trial-and-error approach involves painstakingly testing each potential antibody experimentally, making it a slow and inefficient process.
James Field’s work at LabGenius is helping discover new protein therapeutics using AI
Photo by Tom Trevatt
James Field, Founder of LabGenius, recognised this challenge and saw an opportunity to leverage advancements in DNA sequencing, computation, and robotics to automate and expedite the antibody discovery process. LabGenius was born with the vision of harnessing the power of AI to transform the field of antibody engineering.
AI meets antibodies
LabGenius combines the expertise of human scientists with the precision and efficiency of AI and automation. At their state-of-the-art lab in Bermondsey, London, machine learning algorithms are employed to design antibodies that target specific diseases. These algorithms are trained on vast datasets and continuously learn and improve their designs through iterative processes.
In the search for the ideal antibody, human scientists start by identifying a vast search space of potential options. LabGenius has developed a machine learning model that can rapidly and effectively explore this space. By providing the system with examples of healthy and diseased cells, the model can generate over 700 initial options from a search space of 100,000 potential antibodies. It then automatically designs, builds, and tests these antibodies, seeking areas of promise for further investigation.
Field likens the process to choosing the perfect car from a field of thousands. Just as one might start by selecting a broad colour and then narrowing down to specific shades, LabGenius’ model filters through the vast array of potential antibodies to identify the most promising candidates.
Automation and robotics at work
LabGenius’ lab is a symphony of automation and robotics. Automated robotic systems handle the building and growth of antibodies, running tests, and feeding data back into the machine learning algorithm. Technicians, donning lab coats, diligently prepare samples, and analyse the results while machines hum in the background.
This integration of automation and robotics not only expedites the antibody discovery process, but also reduces the margin for error. With limited human supervision, this ensures consistent and reliable results, paving the way for faster, more efficient antibody engineering.
The impact of this AI-powered approach to antibody engineering is far-reaching. By automating the discovery process, LabGenius aims to accelerate the development of new therapeutic antibodies, potentially revolutionizing disease treatment. Diseases that once seemed insurmountable may now have a greater chance of being conquered, unlocking new possibilities for patients around the world and potentially hugely advancing the field of healthcare in the process.
Advantages of AI in antibody engineering
The use of AI in antibody engineering offers several significant advantages. Firstly, it significantly reduces the time required to design and test antibodies. What would take years using traditional methods can now be accomplished in a fraction of the time. This accelerated pace opens up avenues for faster drug development and more timely treatment options.
Secondly, AI enables scientists to explore a much larger pool of potential antibodies. The vastness of the search space makes it nearly impossible for humans alone to thoroughly examine all possibilities. With AI, LabGenius can efficiently navigate this infinite space, uncovering hidden gems that may have otherwise been overlooked.
The future of antibody engineering
This innovative approach to antibody engineering is just the beginning. The intersection of AI, robotics, and biotechnology holds immense promise for the future of medical science. As AI algorithms continue to learn and improve, they will become even more adept at designing antibodies with enhanced therapeutic properties. This could lead to personalised treatments tailored to individual patients, maximising efficacy, and minimising side effects.
Collaborations between AI and biology are also likely to expand beyond antibody engineering. The same principles that drive LabGenius’s success could be applied to other areas of drug discovery, diagnostics, and even regenerative medicine. The possibilities are endless, and the future of medical science is bright with the advancements brought forth by AI.
This pioneering work in AI-powered antibody engineering is transforming the landscape of medical science. By leveraging the capabilities of AI, LabGenius is revolutionizing the discovery and development of therapeutic antibodies. Their automated processes and robotics enable faster and more efficient antibody design, significantly reducing the time required to bring potentially life-saving treatments to patients. With continued advancements in AI and the integration of biotechnology, the future of antibody engineering holds immense potential for personalized medicine and improved patient outcomes.
As we look ahead, it is clear that AI and automation will continue to play a pivotal role in the advancement of medical science. The synergy between human expertise and AI algorithms opens up new horizons for innovation, making the seemingly impossible a reality. LabGenius’ journey is just the beginning, and we eagerly anticipate the groundbreaking discoveries and breakthroughs that lie ahead in the realm of antibody engineering.
