Jon Kapla on the role of AI in the pharmaceutical industry
AI is changing the future of the pharmaceutical industry
When the Nobel Prize in chemistry 2024 was awarded to an AI model, it became a clear recognition of AI's influence and potential in scientific and industrial processes. The development marks that AI is not just a tool, but a catalyst for innovation in drug development.
Jon Kapla, a computational biologist at AFRY, has a strong background in pharmaceutical computational methods and has used AI models like AlphaFold2 to predict structures of preclinical drug candidates. He is now exploring the potential of new AI-based tools for protein design that offer unique opportunities in both drug research and the biotech industry.
“AI and machine learning have proven invaluable for solving previously unsolved structures,” Jon says.
He emphasises AI models’ ability to predict protein structures and their function, which can greatly accelerate the drug development process. The Nobel Prize in chemistry highlights these advancements, where Demis Hassabis and John Jumper with AlphaFold2 have solved the 50-year-old mystery of protein structures.
Potential to radically change how we develop drugs – but do we have the resources?
One of the biggest challenges for pharmaceutical companies is the high cost of bringing a drug to clinical trials, where most fail to reach the market due to lack of efficacy or unforeseen side effects. AI can help predict which molecules have the best chance of passing all trials, which is a great win as more drugs could reach the market.
“We can also see environmental gains, for example by trying to minimise the lab work and thus the use of harmful chemicals,” Jon says.
He also adds that these lab benefits must be weighed against the energy consumption required to use AI-tools, which often demands large computational resources such as storage, graphics cards, and processors. This is not apparent to end users of tools like OpenAI's generative AI model, ChatGPT, but is very clear when applying models to molecular problems.
“A discussion that has recently flared up is about the extensive resource usage of these tools. Last year, American scientists highlighted the large data centers needed to train and operate large models like ChatGPT, which require huge amounts of electricity and cooling water. Efforts will be needed in the future from both hardware and software developers as well as the energy sector to make future AI tools more sustainable,” Jon explains.
Furthermore, he highlights that ethical considerations are central in the discussion about AI in drugs. Jon emphasises the importance of understanding the limitations of AI models and always complementing them with experimental tests.
“It's important to know the weaknesses of the models when interpreting the answers,” he concludes.
This awareness is crucial to ensure a safe and responsible use of AI in drug development.
The power of technology to change and create sustainability
AI represents a revolutionary force in the pharmaceutical industry, where the technology's potential to profoundly change drug development has just begun to be explored. Jon Kapla's insights underscore the significant role AI plays in increasing precision, efficiency, and sustainability in this process. With the help of AI, we can look forward to a future where new and improved drugs are developed faster and more cost-effectively, while carefully navigating the ethical considerations that accompany this development. By continuing to integrate artificial intelligence in a responsible way, we can accelerate the transition to a sustainable society and create lasting value for future generations.
