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AI-Powered Scalable Diagnostics For Any Virus | Ben Zhang

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Manage episode 357832897 series 3453925
Content provided by thebiotechfuturistpodcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by thebiotechfuturistpodcast 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://player.fm/legal.

What if we had rapid and reliable COVID tests since the very early days of the pandemics?

Today I have the pleasure to discuss state-of-the-art diagnostics for infectious diseases with my friend Ben Zhang. Ben is a medical student at Harvard Medical School. He has done prize-winning work in the Pardis Sabeti lab on CRISPR-based diagnostic for flu and COVID.

Ben and I discuss the importance of viral tests that are easy to use and do not require expensive technology and expertise, to foster widespread home testing immediately as a new pathogen begins circulating, also in developing countries. CRISPR-based diagnostics seems to provide the answer. The Sabeti lab has done outstanding work to make it a reality with its SHERLOCK assay. We discuss the main challenges and solutions to build CRISPR-based viral diagnostics: multiplexing enzyme activities for single-pot reactions given different constraints on reaction conditions, avoiding the use of a thermocycler, multiplexing different diagnostic reactions, evaluating sensitivity, adjusting the assay to keep into account viral variants. We discuss ADAPT, an incredible machine learning-backed tool developed by the Sabeti lab to design a SHERLOCK assay (and, in principle, other assays) in probably < 2 weeks after the first genomic sequence of a new pathogen is published. This exciting work may help us reduce the impact of pandemics with early, efficient, at home diagnostics. Looking forward to seeing what Ben and the Sabeti lab achieve in the next few years!

If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM or email me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini.

RESOURCES:

[ACADEMIC] Field-deployable viral diagnostics using CRISPR-Cas13: https://www.science.org/doi/10.1126/science.aas8836

[ACADEMIC] Simplified Cas13-based assays for the fast identification of SARS-CoV-2 and its variants: https://www.nature.com/articles/s41551-022-00889-z

[ACADEMIC] Designing sensitive viral diagnostics with machine learning: https://www.nature.com/articles/s41587-022-01213-5

ADAPT: https://adapt.run/

[ACADEMIC] Streamlined inactivation, amplification, and Cas13-based detection of SARS-CoV-2: https://www.nature.com/articles/s41467-020-19097-x

[OUTREACH] https://www.sciencedaily.com/releases/2018/04/180426141510.htm

The Sabeti Lab: https://www.sabetilab.org/

Pardis Sabeti on Instagram: https://www.instagram.com/pardis_sabeti/

  continue reading

14 episodes

Artwork
iconShare
 
Manage episode 357832897 series 3453925
Content provided by thebiotechfuturistpodcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by thebiotechfuturistpodcast 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://player.fm/legal.

What if we had rapid and reliable COVID tests since the very early days of the pandemics?

Today I have the pleasure to discuss state-of-the-art diagnostics for infectious diseases with my friend Ben Zhang. Ben is a medical student at Harvard Medical School. He has done prize-winning work in the Pardis Sabeti lab on CRISPR-based diagnostic for flu and COVID.

Ben and I discuss the importance of viral tests that are easy to use and do not require expensive technology and expertise, to foster widespread home testing immediately as a new pathogen begins circulating, also in developing countries. CRISPR-based diagnostics seems to provide the answer. The Sabeti lab has done outstanding work to make it a reality with its SHERLOCK assay. We discuss the main challenges and solutions to build CRISPR-based viral diagnostics: multiplexing enzyme activities for single-pot reactions given different constraints on reaction conditions, avoiding the use of a thermocycler, multiplexing different diagnostic reactions, evaluating sensitivity, adjusting the assay to keep into account viral variants. We discuss ADAPT, an incredible machine learning-backed tool developed by the Sabeti lab to design a SHERLOCK assay (and, in principle, other assays) in probably < 2 weeks after the first genomic sequence of a new pathogen is published. This exciting work may help us reduce the impact of pandemics with early, efficient, at home diagnostics. Looking forward to seeing what Ben and the Sabeti lab achieve in the next few years!

If you liked this episode, please consider subscribing to The Biotech Futurist on Spotify, Apple Podcast, Stitcher, Google Podcast, or your favorite platform, and leaving a positive review. The growth of this podcast depends critically on word-of-mouth. Thank you for your help. Follow The Biotech Futurist on Instagram and YouTube, and DM or email me if you have any curiosity. You can always download the transcript of this episode and find the links to the papers we mention on my website, lucafusarbassini.com. The jingle is by Gabriele Fusar Bassini.

RESOURCES:

[ACADEMIC] Field-deployable viral diagnostics using CRISPR-Cas13: https://www.science.org/doi/10.1126/science.aas8836

[ACADEMIC] Simplified Cas13-based assays for the fast identification of SARS-CoV-2 and its variants: https://www.nature.com/articles/s41551-022-00889-z

[ACADEMIC] Designing sensitive viral diagnostics with machine learning: https://www.nature.com/articles/s41587-022-01213-5

ADAPT: https://adapt.run/

[ACADEMIC] Streamlined inactivation, amplification, and Cas13-based detection of SARS-CoV-2: https://www.nature.com/articles/s41467-020-19097-x

[OUTREACH] https://www.sciencedaily.com/releases/2018/04/180426141510.htm

The Sabeti Lab: https://www.sabetilab.org/

Pardis Sabeti on Instagram: https://www.instagram.com/pardis_sabeti/

  continue reading

14 episodes

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