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EP 111: Combining human and machine intelligence in protein engineering with Dr. James Field, CEO of LabGenius
Manage episode 382876612 series 2631947
内容由Sano Genetics提供。所有播客内容(包括剧集、图形和播客描述)均由 Sano Genetics 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
In this episode of The Genetics Podcast, we welcome Dr. James Field, founder and CEO of LabGenius. Join us as we delve into LabGenius' cutting-edge approach that utilises machine learning, artificial intelligence, and sophisticated robotics to advance antibody discovery and drug development. As a bonus, learn about James’ path from scientist to CEO, and how he created LabGenius.
Timestamps:
00:00 Introduction
01:04 The genesis of LabGenius: protein engineering
04:06 Progressing from human intuition and rules-of-thumb to a mathematically-driven approach to protein synthesis
05:24 Redefining the relationship between human and machine
08:38 Multi-dimensional optimisation: an iterative machine learning approach to design and test various molecules
11:20 The LabGenius Process to developing antibodies: sequencing, testing mammalian expression, and functional cell-based assays
12:50 The relative scalability of functional cell-based assays
14:30 How LabGenius is tackling the bottlenecks in finding antibodies to cure cancer
15:52 Applying protein engineering beyond antibodies to enzymes and other biological molecules
18:12 The challenges in scaling clinical trials and the choice to engage with partners
19:24 James’ shift from scientist to CEO: Overcoming the challenges of fundraising and finding smart investors who share your vision
24:40 James’ entrepreneurial spirit: wanting to build something that is worth the tough journey
26:10 The biggest challenges to creating LabGenius and lessons learned from starting a company
29:00 Navigating the complexities of partnering with large pharma and biotech companies
30:42 Novel technologies on the horizon that redefine what it means to be healthy
32:48 Future Frontiers: The potential for in-silico models in advancing drug discovery
34:58 Closing Remarks
179集单集
Manage episode 382876612 series 2631947
内容由Sano Genetics提供。所有播客内容(包括剧集、图形和播客描述)均由 Sano Genetics 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
In this episode of The Genetics Podcast, we welcome Dr. James Field, founder and CEO of LabGenius. Join us as we delve into LabGenius' cutting-edge approach that utilises machine learning, artificial intelligence, and sophisticated robotics to advance antibody discovery and drug development. As a bonus, learn about James’ path from scientist to CEO, and how he created LabGenius.
Timestamps:
00:00 Introduction
01:04 The genesis of LabGenius: protein engineering
04:06 Progressing from human intuition and rules-of-thumb to a mathematically-driven approach to protein synthesis
05:24 Redefining the relationship between human and machine
08:38 Multi-dimensional optimisation: an iterative machine learning approach to design and test various molecules
11:20 The LabGenius Process to developing antibodies: sequencing, testing mammalian expression, and functional cell-based assays
12:50 The relative scalability of functional cell-based assays
14:30 How LabGenius is tackling the bottlenecks in finding antibodies to cure cancer
15:52 Applying protein engineering beyond antibodies to enzymes and other biological molecules
18:12 The challenges in scaling clinical trials and the choice to engage with partners
19:24 James’ shift from scientist to CEO: Overcoming the challenges of fundraising and finding smart investors who share your vision
24:40 James’ entrepreneurial spirit: wanting to build something that is worth the tough journey
26:10 The biggest challenges to creating LabGenius and lessons learned from starting a company
29:00 Navigating the complexities of partnering with large pharma and biotech companies
30:42 Novel technologies on the horizon that redefine what it means to be healthy
32:48 Future Frontiers: The potential for in-silico models in advancing drug discovery
34:58 Closing Remarks
179集单集
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