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/

What if we could understand and talk to minimally verbal individuals thanks to machine learning?

Today I have the luck to meet the pure energy of Kristy Johnson. After a PhD at the MIT Media Lab, Kristy is now working at Boston Children’s Hospital, but she’s also a mother, and her first child has a terrible ultrarare disease called MEF2C haploinsufficiency. Kristy is a versatile scientist and she has devoted her research to minimally verbal and non-verbal children to help them communicate.

Kristy and I discuss her personal story, the several research fields she has touched, and her current research in population genetics to help patients with rare diseases, which, taken together, are not that rare. We are lucky to have her very personal understanding to guide us through the difficulties of a child who does not reach conventional milestones: “now what?”. Kristy and I discuss the need of high personalization: for example, even if much later than other children, learning a first word for a child with a rare disease, strongly delayed, is an outstanding success. But how can we motivate individuals with rare and widely diverse neurological disorders to pursue learning? How can we make sure we understand them and they understand us? Kristy explains several directions she has taken during the years, and we discuss how hard it is to understand if an individual is improving following some intervention, given the lack of a “control”, untreated population. Kristy has devoted herself to collecting vocalizations from minimally verbal MV* individuals through an app, having parents to label the emotion of their child associated with those vocalizations. She and her colleagues have then remarkably put together a machine learning model that can label such vocalization (Commalla Project). I’ll stop here, you’ll have to listen to the episode to know more! Looking forward to seeing what Kristy will invent in the next few years, but I am sure that the neurological disease community will greatly benefit from her work!

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:

Kristy’s MIT Page: https://www.media.mit.edu/people/ktj/overview/

MIT Media Lab: https://www.media.mit.edu/

Commalla: https://commallamit.wixsite.com/commalla

About MEF2C haploinsufficiency: https://rarediseases.org/rare-diseases/mef2c-deficiency/?filter=ovr-ds-resources

The Biotech Futurist podcast aims to build fundamental knowledge and trust in emerging research in the biomedical disciplines. I interview a guest every week, exploring topics such as CRISPR therapeutics, neuroscience, rare diseases, machine learning in biology, omics, oncology, longevity. You can imagine to be out with me and my expert guests for a friendly conversation, having fun as much as I've had recording this podcast. Thanks for listening to The Biotech Futurist!