AI's Impact on Healthcare: Insights from Young & Partners 2024 Summit
Published Date : 25/10/2024
At the 20th Annual Young & Partners Pharmaceutical Executive Summit, industry leaders Najat Khan from Recursion and Fred Hassan from Warburg Pincus delve into the transformative potential of artificial intelligence in reducing healthcare costs and improving drug development processes.
At the 20th Annual Young & Partners Pharmaceutical Executive Summit held at the Yale Club of New York, Fred Hassan, director at Warburg Pincus, and Najat Khan, chief R&D and chief commercial officer at Recursion, discussed the profound impact of artificial intelligence (AI) on the pharmaceutical industry. The summit brought together leading experts to explore innovative solutions that can help reduce healthcare costs and improve patient outcomes.
Hassan kicked off the discussion by drawing a parallel between AI and electricity, highlighting Google CEO Sundar Pichai's prediction that AI would become mainstream within five years. He asked Khan whether she shared this optimism. Khan responded, 'I think so, but let’s unpack that a little bit. A lot of people talk about writing a prompt and keeping it summarized, and that’s the easy part. The next thing is, can it generate new ideas? That’s much harder. AI sometimes hallucinates, and sometimes it doesn’t, but it's getting much better at a pace that's quite astonishing. Just last year, I thought AI was like an analyst in its first year, and now it's already a senior analyst, learning quite fast. In the healthcare space, there are countless questions we need to address, from getting data in digital format to predicting and designing better molecules, given our 90% failure rate in getting drugs to market. The applications of AI are vast, and that’s why I believe it is like electricity.'
Switching gears, Hassan addressed the biopharma industry’s potential for AI adoption, noting the rapid uptake in other sectors like financial services. He asked Khan about the mindset challenges and barriers to AI adoption in biopharma. Khan acknowledged that a significant part of the issue is the high margins in the pharmaceutical industry, which reduces the urgency for change. She also pointed out the lack of understanding and the fear of job displacement. 'Pharma companies have high margins, so why change? That's the reality. Additionally, there’s a lack of understanding when it comes to using AI. Everyone knows the pain points, but how do you deploy it? Sometimes, it means your job changes, which can be threatening. I've seen this firsthand. The key is to evolve or risk being left behind. You don’t need to be a coder to understand AI; it’s just another technical topic. The focus should be on how to use it effectively, given the complexity of the pharmaceutical industry and the stringent regulations.'
Hassan concluded the discussion by emphasizing the unsustainable cost of healthcare in the United States and the need for innovation. He asked Khan how AI could help reduce these costs. Khan explained, 'Let’s start with therapeutics. The high cost is often due to the massive failure rate. In biotech companies, you often see a 50/50 split between computer scientists and scientists. At Recursion, we have 15 medicinal chemists working on 20 programs. By leveraging computational power, we fail faster using computers, but we don’t fail by running multiple experiments. We start with a better hypothesis of what’s driving the disease, rather than relying on mouse data that often fails to translate to humans. This approach not only speeds up the process—18 months instead of three to four years—but also saves a significant amount of money.'
Recursion, a leading biotechnology company, is at the forefront of using AI to streamline drug development. Founded in 2013, Recursion leverages artificial intelligence and machine learning to accelerate the discovery and development of new treatments, aiming to transform the way medicines are created and reduce the time and cost associated with bringing new drugs to market.
The insights shared at the Young & Partners Pharmaceutical Executive Summit underscore the transformative potential of AI in the healthcare industry. By addressing the mindset challenges and harnessing the power of AI, the pharmaceutical industry can drive innovation, reduce costs, and ultimately improve patient outcomes.
Frequently Asked Questions (FAQS):
Q: How does artificial intelligence (AI) compare to electricity in the pharmaceutical industry?
A: AI is often compared to electricity because of its potential to revolutionize various industries. In the pharmaceutical sector, AI is seen as a transformative tool that can significantly enhance drug development processes and reduce healthcare costs.
Q: What are some of the main challenges to AI adoption in the biopharma industry?
A: The main challenges include a lack of understanding about AI, the high margins in the pharmaceutical industry which reduce the urgency for change, and the fear of job displacement. Overcoming these challenges requires a mindset shift and a focus on effective AI deployment.
Q: How can AI help reduce the high failure rate in drug development?
A: AI can help reduce the high failure rate by enabling faster and more accurate hypothesis generation and testing. By leveraging computational power, researchers can fail faster using simulations rather than running multiple experiments, saving time and resources.
Q: What is the role of Recursion in the AI-driven drug development process?
A: Recursion is a leading biotechnology company that uses artificial intelligence and machine learning to accelerate the discovery and development of new treatments. By integrating AI into their processes, Recursion aims to reduce the time and cost associated with bringing new drugs to market.
Q: Why is the cost of healthcare in the United States becoming unsustainable, and how can AI help address this issue?
A: The cost of healthcare in the United States is becoming unsustainable due to the high costs of drug development and the inefficiencies in the system. AI can help by optimizing drug development processes, reducing failure rates, and speeding up the time to market for new treatments, ultimately lowering healthcare costs.