Biotechnology Innovations In Medicine

I woke up to this news that: Scientists Just Solved Organoids' Biggest Problem! I’m happy to share highlights from a new Science paper by Dr. Oscar Abilez, Dr. Huaxiao 'Adam' Yang, Dr. Joseph C. Wu, and colleagues, a leap forward for organoid technology and regenerative medicine! What Did They Do? Stanford researchers have created the first heart and liver organoids with integrated, functional blood vessels. This solves a critical bottleneck: until now, organoids could only grow a few millimeters before their centers died from lack of oxygen and nutrients. With built-in vasculature, these mini-organs can grow larger, mature further, and better mimic real human tissues. How Did They Do It? *The team meticulously optimized a “recipe” of growth factors and signaling molecules, guiding pluripotent stem cells to differentiate into not just heart or liver cells, but also endothelial and smooth muscle cells that self-organize into branching blood vessels. *Their protocol mirrors early embryonic development, allowing the organoids to achieve a cellular complexity similar to a 6.5-week-old human embryonic heart, including beating function! Why Is This Important? *Better Disease Models: Vascularized organoids allow researchers to study early human development and test how drugs impact organ growth and blood vessel formation. *Personalized Medicine: These models can be tailored from patient-derived stem cells, paving the way for individualized drug testing and disease modeling. *Regenerative Therapies: In the future, vascularized cardiac organoids could be implanted to repair damaged heart tissue, offering a more complete cellular environment than current cell therapies Clinical Context As Dr Joseph C. Wu notes, ongoing clinical studies are already injecting lab-grown cardiomyocytes into patients with heart dysfunction. But real heart tissue is much more complex, containing blood vessels, pericytes, fibroblasts, and more. Vascularized organoids could one day provide all these cell types in a single, implantable tissue patch, dramatically improving integration and function. What’s Next? The team aims to: *Grow organoids longer to assess their maturation and size limits *Further refine the recipes to include immune and blood cells *Adapt this vascularization approach to other organs, moving closer to true “mini-organs” for research and therapy A huge CONGRATULATIONS to the entire Stanford team! References: https://lnkd.in/gmYc-cX9 https://lnkd.in/gbntyWgN https://lnkd.in/g-YT5wdU

Eli Lilly and Company just dropped $1.3 billion to turn off a gene. Permanently. Not suppress. Not modulate. Not block. One edit. One time. And PCSK9 is gone. That may sound like science fiction. But it is not. This week, Eli Lilly announced its acquisition of Verve Therapeutics (a biotechnology company developing a new kind of medicine). It is not a pill. It is not an injection you take every week. It is a one-time treatment that edits your DNA. The therapy is called Verve 102. It targets a gene known as PCSK9, which plays a key role in regulating cholesterol. Specifically LDL, the so-called “bad” cholesterol that contributes to heart disease. Scientists found that by changing a single letter in that gene (literally one letter in your genetic code), they can shut it down. When that happens, LDL levels drop. In early human trials, a single dose lowered LDL by more than 50 percent. That is not just comparable to the best drugs we have today… it might actually outperform them. And again, it is one treatment. For life. This kind of gene editing is called base editing. It does not cut your DNA like older CRISPR tools. Instead, it rewrites a single base (an A to a G) with extraordinary precision. The edit happens in the liver, where cholesterol is processed, using a delivery system designed to find the right cells and make the change. Why does this matter? Because for the first time, we are not just managing high cholesterol. We are looking at the possibility of removing the root cause… with one carefully targeted edit. And Eli Lilly just staked $1.3 billion on it. If successful, this could mark the beginning of a new era in medicine. One where chronic conditions like high cholesterol are not treated with decades of pills but with a single genetic correction that rewrites the story from the start. It is early. The trials are still underway. But this is a moment worth watching. Because the question now is not just can we edit our genes…

⚕️ The era of curative, precision medicine has begun. For decades, the industry has been built on chronic care models... 🧬 Eli Lilly’s latest move signals more than market confidence — it marks a structural shift toward gene-editing therapies that aim not just to treat, but to end disease at its source. The announcement of Eli Lilly's acquisition of Verve Therapeutics is about more than strategy or scale. It signals a defining shift in biopharma: from managing chronic conditions to engineering curative interventions — and doing so through precise, in vivo gene editing. This isn’t incremental innovation. It’s a structural transformation in how we think about drug development, patient care, and the role of pharma itself. A future of single-dose therapies is no longer speculative — it's being actively built, tested, and embraced by industry leaders with the infrastructure to deliver it globally. 📈 What does this mean for the field? 👉 Gene editing is crossing the credibility threshold, from "promising" to "priority." 👉 Traditional pipelines will feel pressure to adapt to this new model of durable, front-loaded interventions. 👉 Companies that once tiptoed around CRISPR-based technologies are now sprinting to secure platform assets and talent. The message is clear: the rules are being rewritten. What was once a long-term vision is rapidly becoming an industry expectation. This isn’t just a biotech acquisition. It’s a referendum on the future of medicine. 💸 What’s the long-term value of a drug that works once — and works for life? This is the question reshaping how pipelines, partnerships, and portfolios are being built. High-risk, high-reward innovation used to be a biotech play. Now it’s pharma’s blueprint. The appetite for transformative, gene-based therapies is growing — and so is the urgency to act. #LifeSciences #PharmaInnovation #GeneEditing #PrecisionMedicine #HealthcareTransformation #CRISPR #FutureOfMedicine #TherapeuticStrategy #RAndDLeadership #BiotechEvolution https://lnkd.in/eCXBkNBM

How close is the Holy Grail of de novo antibody design? Feed an antigen structure/sequence, into a program. Define an epitope and out comes a series of mAbs to test. All human, developable, epitope specific and high affinity. I'm a big believer in AI but also a harsh critic. Where do we stand with this challenge? I was at NextGen Biomed last week - an opportunity to gauge the atmosphere. It was skeptical, at times pessimistic, especially at the panel discussion I attended. "What happens when the first AI antibody fails in the clinic?" was one question. It's hardly like we are successful without AI. As an industry we are so conservative. Is there any pharma not developing PD1/VEGF or GLP1 right now? We spend billions and have low clinical success so derisk to increase our odds. Favouring targets and technologies that have been clinically validated. But mAbs usually fail due to biology not their design. But are we fixated on an unnecessary problem with de novo mAb design? AI design of mini-proteins appears to be a solved problem, with hit rates often >50%. It is simpler to accurately predict binding through α-helices and β-sheets than for antibody CDR loops with high conformational flexibility. Yet the industry seems unwilling to take a risk on anything that doesn't look like what we've been doing for 40 years. Recently Nabla Bio and the Baker group have separately developed a number of AI-nanobodies to a range of targets. Hit rates of <1% but they are generating binders in the double digit nM affinity range from so called zero shot efforts. Highly impressive, and to me at least seems like a more tractable problem than classical mAbs. Half the number of CDRs and no VH/VL pairing! Yet still 95% of talks I went to focussed on the need for classical antibodies not nanobodies or mini-proteins. I couldn't get an answer on why. I was left a bit frustrated until someone I'd never met tapped me on the shoulder - "our paper comes out in 2 days, can I show you some data?". Galux have de novo designed scFvs to 6 distinct targets and got binders to all. This includes a target for which no structure is available and an epitope to which no antibody in the PDB binds. A real test of AIs potential! For PDL1 they went after the same epitope as atezolizumab. Their best AI mAb had higher affinity (9pM compared to 13pM), a 12°C improved Tm and good developability. Sadly they only did this level of analysis for this target but this seems to be the first de novo mAbs with pico molar affinity. More interesting will be achieving that to less well-known targets and unique epitopes. We seem to be approaching this Holy grail very rapidly though! Link to paper in comments. ----- I'm Ian, I post about antibody engineering and my journey to bootstrap Gamma Proteins into a leading supplier of Fc receptors. If you like my content please reshare with your network and follow me to see more.

🔬 Advancing ADME Profiling for PROTACs: New Insights Understanding the ADME behavior of PROTACs is critical as more molecules from this class advance into clinical development. This recent publication provides important insights into how conventional ADME assays perform when applied to PROTACs, a rapidly evolving therapeutic modality. Key findings include: 🔬 Conventional ADME assays (permeability, plasma protein binding) are limited for highly lipophilic PROTACs, with reliable results generally observed when ChromLogD is below 3.5–4. 🔬 Metabolic clearance (CLint) and blood-to-plasma (B:P) ratios are measurable across a wide range of lipophilicity, demonstrating robustness of these assays for PROTACs. 🔬 Implementation of an acetonitrile (ACN) wash step in Caco-2 permeability assays improved the detection of nonspecifically bound compounds. 🔬 Biorelevant solubility studies (using SGF, FaSSIF, FeSSIF) highlight the importance of gastrointestinal conditions in influencing solubility and absorption potential. These findings provide practical guidance for optimizing assay strategies and inform better decision-making during the discovery and development of PROTACs. This work is a significant step toward refining drug discovery processes for bRo5 molecules and addressing the unique challenges presented by PROTACs. Link: https://lnkd.in/gZZGvvgM #DrugDiscovery #DMPK #PROTACs #Pharmacokinetics #MedicinalChemistry #PharmaceuticalResearch

Excited to share our latest work, "#Engineering the #Hierarchical #Porosity of #Granular #Hydrogel #Scaffolds using Porous #Microgels to Improve #Cell Recruitment and #Tissue Integration," published in Advanced Functional Materials! In this study, we tackled a key limitation of granular hydrogel scaffolds (GHS) — limited porosity due to spherical nonporous microgels — by introducing porous microgels fabricated through thermally induced polymer phase separation. This approach resulted in: i) Approximately 170% increase in void fraction compared with nonporous microgel-based GHS; (ii) Preservation of structural stability despite increased porosity; (iii) Significantly higher and more uniform cell infiltration in vitro and in vivo; (iv) Up to ~ 78% increase in cell infiltration in vivo. This work sets the foundation for developing next-generation granular biomaterials with hierarchical porosity, improved cell recruitment, and enhanced tissue integration — paving the way for faster and more effective tissue repair. A big thank you to my incredible team for their outstanding effort! 👉 Read the full paper here: https://lnkd.in/euJPcnQs #weare #pennstate #chemicalengineering #biomedicalengineering #chemistry #neurosurgery #BSMaL #Biomaterials #TissueEngineering #Hydrogels #RegenerativeMedicine #PorousMaterials

Identifying cancer-related mutations accurately is a critical step in precision medicine. Today, we’ve published new research in Nature Biotechnology on 🧬DeepSomatic🧬, an AI-powered tool that uses machine learning to identify genetic variants, or mutations, in cancer cells more accurately than current methods. This work is aimed at helping researchers pinpoint what's driving a cancer and informing more effective treatment plans. Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies offer potential advantages to discover variants in the hardest to sequence parts of the genome. 🧬 About the model:  DeepSomatic was rigorously trained on high-confidence data, a feat made possible by working with our partners at UC Santa Cruz. The model is capable of accurately differentiating actual genetic cancer variants from the technical artifacts introduced during sample preservation, addressing a critical hurdle in early detection. 🧬 Superior Accuracy and Clinical Impact:  DeepSomatic consistently outperformed other tools across all major sequencing platforms. It shows major improvements in identifying complex insertions and deletions (Indels). Furthermore, in a new study with partners at Children's Mercy, DeepSomatic successfully found ten small variants in pediatric leukemia cells that were missed by other tools. 🧬 Flexible and Broad Use:  The model is flexible, working across all major sequencing platforms, and can be applied to both tumor-normal and challenging tumor-only samples, extending its utility for complex cancer types. 🧬 Open Access:  We are making DeepSomatic and the CASTLE dataset openly available to the research community. DeepSomatic is the most recent addition to our 10-year journey developing open source methods for geneticists to study the genomes of humans, plants, and animals. We are excited to see how researchers and drug manufacturers will use these resources to develop more effective, personalized treatments for cancer patients. The ability to accurately identify these subtle genetic drivers is key to unlocking new therapies. More in our blog authored by Kishwar Shafin and Andrew Carroll: https://goo.gle/4n23gIB   Read the full article in Nature Biotechnology: https://lnkd.in/drxii8fz