Novartis CEO discusses how AI will impact drug development
Summary
TLDRThe discussion at Davos highlights the growing role of AI in healthcare, particularly in drug discovery. Vos Nara Simon, CEO of Noard, shares insights into their use of generative AI, including collaborations with Microsoft and DeepMind’s Isomorphic Labs to accelerate drug development. While acknowledging AI’s power, Simon notes that significant breakthroughs may take longer. The conversation also touches on the impact of GLP-1 drugs, the discipline of staying focused on core therapeutic areas, and concerns about future challenges, including potential political impacts on medical science and drug discovery.
Takeaways
- 😀 AI is playing a significant role in healthcare, particularly in drug discovery, and is seen as a key theme at the Davos conference.
- 😀 Generative AI has been integrated into the drug development process by companies like Noard, who started using it in collaboration with Microsoft and Isomorphic Labs for generative chemistry and target identification.
- 😀 AI’s impact on drug development is still in early stages, with great potential, but the human proof of its benefits in speeding up drug discovery is yet to be fully seen.
- 😀 In the next five years, AI is expected to enhance productivity in drug development, especially in areas like trial protocols, regulatory work, and patient data analysis, but major breakthroughs may take longer.
- 😀 Focus and discipline in research and drug development are crucial for Noard, which prefers to stay focused on its core therapeutic areas rather than chasing trending markets like obesity treatment with GLP-1 drugs.
- 😀 While GLP-1 drugs for weight loss are gaining attention, there are long-term questions about patient adherence and sustainability, particularly in terms of health outcomes and muscle mass loss.
- 😀 Long-term patient adherence to weight loss drugs is uncertain, and the effects of discontinuation on muscle mass and overall health remain open questions.
- 😀 In terms of cancer and cardiovascular diseases, Noard remains focused on its core therapeutic areas, but the potential ripple effects of weight loss treatments on these areas are still being explored.
- 😀 The company remains cautious about larger M&A deals, focusing on smaller companies and maintaining a strategy of sub-$5 billion acquisitions, complementing its existing portfolio.
- 😀 There are concerns about political developments, particularly regarding the potential impact of a Trump presidency on science and drug discovery. There is also concern about the erosion of trust in medical science and the potential consequences on the pharmaceutical industry.
- 😀 The pharmaceutical industry faces challenges with policies around drug pricing, particularly with disparities in pricing for oral cancer and cardiovascular drugs, which could lead to a reduction in pipeline development if not addressed.
Q & A
How is AI currently being used in drug discovery?
-Generative AI is being used in drug discovery through partnerships, such as one with Microsoft Research Labs. The company has developed 'generative chemistry' to accelerate the process of bringing new medicines into clinical trials. Additionally, collaborations like the one with Isomorphic Labs, a spin-out of DeepMind, are aimed at speeding up drug development by targeting new potential medicines.
What is the significance of DeepMind's AlphaFold in drug discovery?
-DeepMind's AlphaFold has made significant contributions to understanding how proteins fold, a crucial aspect of drug discovery. This breakthrough has opened up new avenues for research, making it a widely used tool in the scientific community for advancing drug development.
What challenges remain in AI-driven drug discovery?
-While AI is promising, there is still uncertainty about its real-world impact on drug development. The focus is currently on increasing productivity and efficiency in areas such as trial protocol generation and patient data analysis, but achieving significant breakthroughs in human drug development will take longer.
How does AI influence the drug pipeline over the next five years?
-AI is expected to impact drug development productivity, improving efficiencies in areas like generating trial protocols, working with regulators, and analyzing patient data. However, major breakthroughs in drug discovery may take longer than five years to materialize.
Why is the company not focusing on the GLP-1 drug market?
-The company prefers to stay focused on its strengths in specific therapeutic areas, such as cancer, immunology, and kidney diseases. Although GLP-1 weight-loss drugs are enticing, they do not align with the company’s core therapeutic focus, which is yielding positive results in their primary areas.
Is the GLP-1 weight loss trend sustainable in the long term?
-It’s still early to determine if the GLP-1 weight loss trend will be sustainable. While the drugs are effective in the short term, questions remain about long-term patient compliance, potential health risks if patients stop using the drugs, and whether this will continue to be a viable treatment.
What potential ripple effects could GLP-1 drugs have on other therapeutic areas?
-Although the GLP-1 drugs show promise in weight loss, their long-term effects on other areas like cancer and cardiovascular health remain uncertain. The company is focusing on other genetic risk factors, such as LP(a), and believes that weight loss alone is not enough to mitigate risks in these areas.
What is the company’s current M&A strategy?
-The company's M&A strategy focuses on smaller deals, typically under $5 billion, to complement their existing portfolio. They made 15 deals in the past year, and their focus remains on adding companies that enhance their existing pipeline rather than pursuing large, independent acquisitions.
How might a potential second Trump presidency impact science and the pharmaceutical industry?
-Concerns exist regarding the potential erosion of trust in medical science if science continues to be under attack, as it was during the first Trump presidency. Specifically, policies impacting drug discovery and development, such as cancer and cardiovascular drugs, could make it harder to develop new treatments, especially oral drugs.
What are the risks for the pharmaceutical industry if current policies aren't addressed?
-If policy issues, such as disparities in drug pricing and access, aren't addressed, certain types of drugs, especially cancer and cardiovascular treatments, may disappear from pipelines. This could result in a lack of new medicines for patients by the end of the decade.
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