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#50 - Scaling drug discovery with quantum physics and AI - Maximilien Levesque - Aqemia

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Manage episode 515849317 series 3525366
Content provided by Mathieu Chaffard. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Mathieu Chaffard or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What's the link between quantum physics, AI, and drug discovery?

Maximilien Levesque might be the perfect person to answer.

A former theoretical physicist, he realised his research could transform drug development by fundamentally understanding how molecules interact at the atomic level.

In 2019, he co-founded Aqemia with Emmanuelle Martiano Rolland to turn that vision into reality.

Their mission is bold: to design new molecules, atom by atom, capable of binding "undruggable" therapeutic targets.

Unlike AI models that base themselves on existing compounds, Aqemia's generative engine creates novel structures, opening up a new universe of possibilities.

In this episode, Maximilien pulls back the curtain on one of TechBio's most promising startups.

With passion and clarity, he breaks down their approach to drug design, explaining how these "digitally-native" compounds go from the numeric world to real-world testing.

A conversation to understand the ins and outs of an ongoing revolution in the pharmaceutical industry!

Timeline:

  • 00:00:00 - Maximilien’s background as a researcher in mathematics and quantum physics
  • 00:03:46 - What drew Maximilien to drug discovery
  • 00:05:43 - The link between quantum physics and drug discovery
  • 00:10:27 - Aqemia’s technology to design new molecules atom-by-atom
  • 00:18:36 - Aqemia’s pipeline and ongoing preclinical programs
  • 00:20:27 - The difference between AI-based drug discovery and physics-based drug discovery
  • 00:27:55 - Striking a balance between internal development programs and external collaborations
  • 00:32:35 - Aqemia’s approach to talent recruitment at the interface of biology, mathematics, and computer science
  • 00:34:23 - Maximilien’s wish to enter clinical trials in 2026

What we also talked about with Maximilien:

We cited with Maximilien some of the past episodes of the series:

You can learn more about Maximilien’s publications here and prompt ChatGPT, as he suggested, to find out more about quantum physics, AI, and their applications in the field of drug discovery!

You can reach out to Maximilien via LinkedIn and follow Aqemia’s activities on their website and LinkedIn page!

✉️ If you want to give me feedback on the episode or suggest potential guests, contact me over LinkedIn or via email!

⭐️ And if you liked the episode, please share it, subscribe to the podcast, and leave a 5-star review on streaming platforms!

🙏 You can also support my work by doing a PayPal donation @ImpulsePodcast!

👍 Lastly, don’t forget to follow our activities on LinkedIn and our website!

  continue reading

101 episodes

Artwork
iconShare
 
Manage episode 515849317 series 3525366
Content provided by Mathieu Chaffard. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Mathieu Chaffard or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What's the link between quantum physics, AI, and drug discovery?

Maximilien Levesque might be the perfect person to answer.

A former theoretical physicist, he realised his research could transform drug development by fundamentally understanding how molecules interact at the atomic level.

In 2019, he co-founded Aqemia with Emmanuelle Martiano Rolland to turn that vision into reality.

Their mission is bold: to design new molecules, atom by atom, capable of binding "undruggable" therapeutic targets.

Unlike AI models that base themselves on existing compounds, Aqemia's generative engine creates novel structures, opening up a new universe of possibilities.

In this episode, Maximilien pulls back the curtain on one of TechBio's most promising startups.

With passion and clarity, he breaks down their approach to drug design, explaining how these "digitally-native" compounds go from the numeric world to real-world testing.

A conversation to understand the ins and outs of an ongoing revolution in the pharmaceutical industry!

Timeline:

  • 00:00:00 - Maximilien’s background as a researcher in mathematics and quantum physics
  • 00:03:46 - What drew Maximilien to drug discovery
  • 00:05:43 - The link between quantum physics and drug discovery
  • 00:10:27 - Aqemia’s technology to design new molecules atom-by-atom
  • 00:18:36 - Aqemia’s pipeline and ongoing preclinical programs
  • 00:20:27 - The difference between AI-based drug discovery and physics-based drug discovery
  • 00:27:55 - Striking a balance between internal development programs and external collaborations
  • 00:32:35 - Aqemia’s approach to talent recruitment at the interface of biology, mathematics, and computer science
  • 00:34:23 - Maximilien’s wish to enter clinical trials in 2026

What we also talked about with Maximilien:

We cited with Maximilien some of the past episodes of the series:

You can learn more about Maximilien’s publications here and prompt ChatGPT, as he suggested, to find out more about quantum physics, AI, and their applications in the field of drug discovery!

You can reach out to Maximilien via LinkedIn and follow Aqemia’s activities on their website and LinkedIn page!

✉️ If you want to give me feedback on the episode or suggest potential guests, contact me over LinkedIn or via email!

⭐️ And if you liked the episode, please share it, subscribe to the podcast, and leave a 5-star review on streaming platforms!

🙏 You can also support my work by doing a PayPal donation @ImpulsePodcast!

👍 Lastly, don’t forget to follow our activities on LinkedIn and our website!

  continue reading

101 episodes

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