Alexander A. Morgan, MD PhD

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Alexander A. Morgan, MD PhD

Alexander A. Morgan, MD PhD

@genomicsdoc

25 years working at the intersection of AI, biotech, and healthcare. Partner at Khosla Ventures, investing in the future.

San Francisco Katılım Mayıs 2013
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Alexander A. Morgan, MD PhD
Alexander A. Morgan, MD PhD@genomicsdoc·
This is a real step function level improvement in the capability of AI driven drug design. @nablabio is able to fully design a multifunctional/multispecific biologic de novo. This is the way to get to N of 1 personalized biologics.
Nabla Bio@nablabio

Today, we expand zero-shot drug design beyond binding to the design of multifunctional medicines, the intracellular proteome, and state-of-the-art atomic precision with our model, JAM-2. In a new report (below), we show: 1. The first drug-grade, fully computationally designed multispecific antibodies against five peptide-MHCs: Routine picomolar T-cell activation/cell-killing EC50s, >100-fold selectivity, and drug-like developability 2. The first fully generatively designed, drug-grade dual-variant KRAS G12 multispecifics: They recruit primary T-cells from human donors to kill G12V and G12C presenting cells at pM to single-digit-nM potency, completely sparing wild-type. 3. Atomic accuracy, from sequence alone: Angstrom-level agreement between Cryo-EM and JAM-2 de novo designs, requiring only target sequences (not structure) as input. 4. Unrivaled speed with an AI-native in-house wet lab: Designed, built, and tested five programs in one parallelized campaign, end-to-end in-house in ~6 weeks. 5. A higher validation bar for AI-generated drug candidates: In a field increasingly rife with hype and uneven standards of proof, we provide the highest quality public wet-lab validation of AI-designed antibodies to date. We share experimental methods in full, and invite folks to adopt and build on these standards. Truly individualized therapies will be the most important contribution of AI in drug design. These advances help accelerate this future.

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Alexander A. Morgan, MD PhD
Alexander A. Morgan, MD PhD@genomicsdoc·
"Consistently frequent tea drinkers had a 12% (HR:0.88, 95% CI: 0.77, 0.99) reduced risk of cognitive decline." @ITO_EN
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Alexander A. Morgan, MD PhD
Alexander A. Morgan, MD PhD@genomicsdoc·
"subjects with two or three offspring had significantly reduced brain age compared to those without offspring...findings suggest that lifestyle factors accompanying having offspring, rather than the physical process of pregnancy"
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Khosla Ventures
Khosla Ventures@khoslaventures·
A landmark day for KV: @vkhosla named #1 on the @Forbes Midas List, 25 years after topping the inaugural edition. First at the birth of the internet. Now at AI’s defining moment. This year, he’s recognized for the first institutional check into @OpenAI – when others saw a not-for-profit research lab with no product and no revenue, Vinod saw the start of the most transformative technology shift in history. Congrats to managing partners @rabois and @SStrohband, recognized for their early bets on @tryramp and @DoorDash, and @RocketLab and @gitlab 🎉 At KV, we back founders bold enough to make the impossible possible. This recognition belongs to the entrepreneurs who see the future before it exists. forbes.com/lists/midas/
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Bryan Johnson
Bryan Johnson@bryan_johnson·
These numbers are shocking. It's like we got a new frontier AI model but for the body. Lilly's phase 3 results for retatrutide: > highest dose lost 28.3% of body weight in 80 wks > 70 lbs ave > 45% lost 30% or more of their body weight > 65% on the top dose no longer clinically obese Retatrutide is more dynamic than semaglutide and tirzepatide because it targets three receptors (GIP, GLP-1, and glucagon), versus one and two, respectively. Side effects, on the highest dose (12mg), were higher for retatrutide than tirzepatide (nausea and GI), with an 11.3% drop out rate. The lowest 4mg dose still delivered 19% loss with fewer dropouts than placebo.
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Brian Halligan
Brian Halligan@bhalligan·
I don't remember where I found this, but its spot on.
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John Cumbers
John Cumbers@johncumbers·
Anthropic Says Life Sciences Is Its Biggest Bet After Code. Eric Kauderer-Abrams started @AnthropicAI 's life sciences division ten months ago. He took on the stage at @SynBioBeta with Marc Tessier-Lavigne from @Xaira_Thera , and what caught my attention was how plainly Eric stated the following: "The greatest opportunity to have a beneficial, scaled impact with everything that's happening in frontier AI is in the life sciences." After coding, it's their biggest investment area. They've been training Claude on bioinformatics, chemistry, molecule design, structural biology, clinical regulatory. Their models went from mediocre in life sciences to roughly PhD level across most domains in under a year. That's a steep curve. But what I found more telling than the benchmarks was the infrastructure they're building around it. Wet labs for basic research so their own scientists hit the walls firsthand. An acquisition of Coefficient Bio (acquired by Anthropic) to teach @claudeai how to think like a biotech program manager, not just a bench scientist. The gap between "Claude can answer a biology question" and "Claude can help you run a drug program" is enormous, and they're clearly aware of it. Marc mentioned that 90% of drugs fail in the clinic. Two-thirds of those failures aren't bad science, but patient matching. You have a good target, a good drug, and you can't find who will respond. That's the problem both of them kept circling back to, and it's where causal AI models trained on real perturbation data might actually move the needle. Marc said nobody's pushing a button for a development candidate anytime soon. But Anthropic went from $1B to $30B in revenue in sixteen months. That kind of resource behind this kind of focus is new. It's fun to think of what R&D can look like in the next few months! #SynBioBeta2026 #SyntheticBiology #Biotech #AIxBio
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