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The Biotech Capital Compass's avatar

Very cool. And thorough…thank you!

David Kingsley, PhD's avatar

I'm glad you enjoyed it! I'd be curious if there was anything you felt missed the list? My next article after JPM debrief will be a 2026 forecast.

Peter W Shuster's avatar

Thank you! From @Neuromics.

David Kingsley, PhD's avatar

You're welcome! Let me know if we missed anything you're interested in or believe should make the list.

Max Votek's avatar

Solid list. One underrated thread connecting all five. The bottleneck is no longer discovery, it's manufacturing and delivery. GLP-1s work, but tolerability and weight regain remain. Cell therapies work, but scalability is the wall. AI designs enzymes, but validation is still slow. 2026's breakthroughs will be about closing the last mile.

David Kingsley, PhD's avatar

Thanks, Max. It seems like there were a few decades where very little happened on major diseases, but we are making tons of break throughs simultaneously now. Another big topic for the future will be the peptide drug class.

Alexander Ipfelkofer's avatar

"The core idea is not “a chatbot that writes protocols.” It is closing the loop between hypothesis, execution, measurement, and iteration, with software that can reason over experiments the way a strong scientist does, while operating at machine cadence."

R&D of the future.

Great roundup, David!

YOUR DOCTOR KLOVER's avatar

Loved this roundup! What stands out to me (as a clinician-scientist) is that all five “breakthroughs” are really the same story told in different languages: we’re learning how to control complex biological systems at scale; metabolism, proteins, labs, neurodegeneration, and immune cells.

A few reflections that feel especially important for 2026:

1. GLP-1 era → “body composition medicine” is the real next frontier. The clinical win isn’t just weight loss, but it’s risk remodeling (hepatic fat, BP, sleep apnea, cardiometabolic inflammation). But the next hard problem is preserving/adding lean mass, bone density, and functional capacity while reducing fat mass—especially in midlife and older adults. “Successful” outcomes will increasingly be measured in strength, VO₂max, gait speed, and frailty metrics, not just the scale.

2. Protein design and multi-step enzymes are a quiet revolution. When we can reliably design catalytic cycles (not just binders), we’re talking about new therapeutic modalities, manufacturing routes, and even environmental/diagnostic applications. The scientific bar that matters will be: does the designed function persist in messy biology, crowding, redox, proteases, immune surveillance?

3. Autonomous labs are a step-change, but only if we keep them honest. Closing the loop between hypothesis → experiment → measurement → iteration is transformative, yet biomedical reality punishes weak ground truth. The most valuable early wins may be in areas with tight readouts and reproducibility (QC, assay optimization, protein expression), while the harder frontier is causal biology where confounding and batch effects masquerade as “discoveries.”

4. Alzheimer’s progress deserves both hope and precision. The public narrative swings between “cure” and “failure.” The more accurate frame is: we’re finally learning which biology to target in which patient at which stage, and how to pair biomarkers with treatment. That’s progress, even if it’s incremental and heterogeneous.

5. Cell therapy’s next act is logistics + safety + solid tumors/autoimmunity. The science is stunning; the bottleneck is often manufacturing speed, access, durability, and managing on-target/off-tumor and inflammatory toxicity. If automation shortens vein-to-vein time and standardizes product quality, that’s not “boring ops”, it’s clinical impact.

Mackenzie Sharp's avatar

The AI lab is so cool, thanks for sharing! :')

David Kingsley, PhD's avatar

Hi Mackenzie, glad you liked it! I’m hoping we start seeing the effects scale to solve healthcare challenges and enhance human potential!

Big Pharma Sharma's avatar

Nice list! I would nominate some of the advancements in multiple myeloma that came out of ASH in december. BCMAxCD3 alone and in combo with anti-CD38 reduced risk of death by 40 (Majestec-9) and 54% (Majestec-3).

There was also really impressive in vivo CAR-T data with a BCMA CAR-T from Kelonia Therapeutics. Still super early, but a very encouraging 100% ORR and multiple MRD- responses.

Wrote about both in detail in my NL in case you want to learn more: https://www.bigpharmasharma.com/p/ash-2025-is-this-the-beginning-of

David Kingsley, PhD's avatar

Great post! You've earned at least one new subscriber.

Big Pharma Sharma's avatar

Thanks! You too!

Owen Lewis's avatar

Read that article, very interesting stuff! I actually happen to have multiples myeloma (young, but it happens), so this is of particular interest to me.

Are you familiar with any trials doing in vivo CAR-T cell engineering? Seemed to me a promising option with less risk and potentially greater efficacy (and the generation of memory T-cells).

Big Pharma Sharma's avatar

Thanks for reading and so sorry that you going through the MM journey. I have an uncle who is also battling. Luckily MM is quite a hot area for development of new therapies and every year I am impressed with how much higher the efficacy bar gets it in that space.

Re: In vivo CAR-T, the BCMA CAR-T program from Kelonia is in the clinic now: https://clinicaltrials.gov/study/NCT07075185 and I would imagine they expand to more sites over the course of this year.

I am optimistic about in vivo in general, however I would caution you in characterizing it as 'less risk', since it is a much newer modality compared to auto' or allo' CAR-T, and for MM specifically has only been used in a handful of patients (at least in the US). Creating CAR-T cells directly within the patient's body with a viral vector carries some risks (e.g. accidentally engineering malignant cells, off-target vector tropism, vector-specific immunogenicity, etc.) that going the ex vivo route does not. It's still early days with this technology and more patients + longer-term follow up are needed before we know how the full profile stacks up vs. auto'.

Certainly DM me if there is any additional information I can provide that will help you have a more informed conversation with your doctor about treatment options.

Victor Perton's avatar

Excellent food for thought! Thanks!

David Kingsley, PhD's avatar

It was a fun thought exercise! I'm glad you found value.

Juli's avatar

Que buen contenido! 💕

Michael's avatar

I wonder if 'peptides' as a drug class could be its own category.

Owen Lewis's avatar

Maybe? Could easily be. Peptides and peptide derivatives.