CAR T therapy is a groundbreaking medicine that uses engineered T cells to attack cancer. But CAR T cells (that is, chimeric antigen receptor T cells) can be programmed to recognize a huge range of target proteins and cell types. So what other types of cells should we train CAR Ts to recognize and destroy to improve human health? On this episode of the a16z Journal Club, a16z General Partner Jorge Conde, bio deal team partner Andy Tran, and Lauren Richardson discuss new research published in Nature in which the authors engineer CAR T cells to recognize and kill senescent cells. Cellular senescence is a process where cells stop dividing (sort of go to sleep), and in many cases this can be protective, like its role in tumor suppression, but if too many cells become senescent of if they are not removed, they can trigger inflammation and cause disease, like in atherosclerosis and type 2 diabetes. Critically, senescent cells build up as we age and contribute to a whole host of age-related conditions. In this episode we cover how the authors created these senescence killing (aka senolytic) CAR T cells, the diseases that could be treated with senolytic CAR Ts, the hurdles to getting them into the clinic, and how they could potentially be used to treat aging and possibly improve longevity. “Senolytic CAR T cells reverse senescence-associated pathologies” in Nature (June 2020) by Corina Amor, Judith Feucht, Josef Leibold, Yu-Jui Ho, Changyu Zhu, Direna Alonso-Curbelo, Jorge Mansilla-Soto, Jacob A. Boyer, Xiang Li, Theodoros Giavridis, Amanda Kulick, Shauna Houlihan, Ellinor Peerschke, Scott L. Friedman, Vladimir Ponomarev, Alessandra Piersigilli, Michel Sadelain & Scott W. Lowe a16z bio Journal Club (part of the a16z Podcast), curates and covers recent advances from the scientific literature -- what papers we’re reading, and why they matter from our perspective at the intersection of biology & technology. You can find all these episodes at a16z.com/journalclub.

In this episode -- cross posted from our 16 Minutes show feed -- we cover all the buzz around GPT-3, the pre-trained machine learning model from OpenAI that’s optimized to do a variety of natural-language processing tasks.  It’s a commercial product, built on research; so what does this mean for both startups AND incumbents… and the future of “AI as a service”? And given that we’re seeing all kinds of (cherrypicked!) examples of output from OpenAI’s beta API being shared — how do we know how good it really is or isn’t? How do we know the difference between “looks like” a toy and “is” a toy when it comes to new innovations?  And where are we, really, in terms of natural language processing and progress towards artificial general intelligence? Is it intelligent, does that matter, and how do we know (if not with a Turing Test)? Finally, what are the broader questions, considerations, and implications for jobs and more? Frank Chen explains what “it” actually is and isn’t and more in conversation with host Sonal Chokshi. The two help tease apart what’s hype/ what’s real here… as is the theme of 16 Minutes.