MOL Therapy Nucleic Acids article on NK cells

I am passionate about developing tools that advance both basic and translational sciences. The Ting group has introduced an exciting innovation, published in #Nature: Programmable Antigen-Gated G-protein-coupled Engineered Receptors (PAGERs). These synthetic receptors leverage a modular GPCR scaffold to detect soluble and cell-surface antigens, offering precise control over cellular responses. This breakthrough can potentially revolutionize the programming of biological processes, including drug discovery. I'm eager to see its transformative impact on the field. The future holds endless possibilities—let's reimagine what's achievable! #Tooldevelopment #SyntheticBiology #GPCR #CellTherapy #Innovation https://lnkd.in/eBt6p6Ef

Using biological target structure in computer-aided drug design (CADD) By combining molecular modelling, bioinformatics, and cheminformatics, CADD approaches can predict how drugs will interact with their biological targets, allowing the visualisation and analysis of crucial molecular interactions that are key for a drug’s effectiveness and safety #CADD #molecularmodelling #bioinfomatics #chemoinfomatics #SBDD Read more: https://lnkd.in/equ7NeDH

Tackling Variability and Scalability in mRNA and siRNA Lipid Nanoparticles (LNPs), here’s how: حلول مشاكل صناعة جزيئات النانو الدهنية من المختبر إلى الإنتاج المصنعي Variability and scalability are significant challenges when it comes to mRNA and siRNA LNPs. At the lab level, many researchers rely on the simple injection method for LNP production. While this approach is cost-effective and scientifically accepted, it falls short for industrial applications. Here’s why: 1. Size Variability (تباين في حجم الجزيائات): Inconsistencies in size can significantly impact overall in vivo performance. 2. Scaling Challenges (القدرة على انتاج كميات كبيرة): Transitioning from lab-scale to industrial-scale production poses significant difficulties. The Solution? In the industrial realm, microfluidics technology has emerged as a successful method for creating LNPs at scale. A recently published paper highlights a novel approach that achieves large-scale production with minimal variability. How did they do it? The study utilizes a Parallelized Microfluidic Device (PMD) featuring 128 mixing channels that operate simultaneously. Does it Matter in Vivo? Absolutely! In mouse models, the results were impressive: - The LNPs-siRNA demonstrated a **4-fold increase** in hepatic gene silencing compared to conventional methods. - The LNPs-luciferase-encoding mRNA exhibited a **5-fold increase** in luciferase expression compared to traditional techniques. Take-Home Message: If you canNOT scale up and produce uniformly stable LNP formulations, your lab work may NOT translate effectively to clinical applications.

𝐓𝐡𝐞 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧!🧬⚙️ A recent lecture on Model systems by one of our professors got me thinking about how much research tools have advanced. In the rapidly evolving world of biotechnology, 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗺𝗼𝗱𝗲𝗹𝗶𝗻𝗴 is transforming the way we conduct research and development. But what exactly does this mean, and why should you care? Imagine this: Instead of lengthy, costly lab experiments, scientists can now use advanced algorithms to simulate biological processes and predict outcomes before even setting foot in the lab. Welcome to the world of 𝐢𝐧 𝐬𝐢𝐥𝐢𝐜𝐨 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬!📈📊 Predictive modeling leverages complex statistical techniques and ML to analyze vast datasets. By utilizing existing data on biological systems, researchers can create models that forecast how different variables will interact. 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲: Predictive models can identify potential drug candidates by simulating their interactions with target proteins, significantly speeding up the process. For instance, a study published in Nature Biotechnology demonstrated that machine learning algorithms could predict the efficacy of drug compounds with remarkable accuracy (https://lnkd.in/dxEnnw9E) 𝐆𝐞𝐧𝐞𝐭𝐢𝐜 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡: In silico analysis allows scientists to predict the behavior of genes and their interactions within cellular environments. This has enormous implications for understanding diseases and developing gene therapies. A paper in Bioinformatics highlighted how predictive models successfully identified novel genetic variants associated with specific conditions. (Larrea-Sebal, Asier et al. “Predictive Modeling and Structure Analysis of Genetic Variants in Familial Hypercholesterolemia: Implications for Diagnosis and Protein Interaction Studies.” Current atherosclerosis reports vol. 25,11 (2023): 839-859. doi:10.1007/s11883-023-01154-7) 𝐄𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐚𝐥 𝐈𝐦𝐩𝐚𝐜𝐭 𝐀𝐬𝐬𝐞𝐬𝐬𝐦𝐞𝐧𝐭𝐬: Predictive modeling can assess the impact of biotechnological interventions on ecosystems, helping to ensure that innovations are sustainable and eco-friendly.🍃🌍 By reducing the time and cost associated with traditional methods, we can bring new therapies and solutions to market faster than ever. #Predictivemodelling #Bioinformatics #Modelsystems #Biotechnology #Drugdiscovery #AI #Machinelearning

“Since Insilico’s foundation in 2014, I have seen, with my own eyes, lots of proof-of-concept cases in AI-driven drug discovery, and they are scattered across diseases areas and stages of the drug R&D process,” says Alex Zhavoronkov, PhD, founder and CEO of Insilico Medicine. “The application of AI is revolutionizing the whole scientific research spectrum by enabling us to tackle complex challenges more efficiently and effectively, so that we’ll be living healthier, better, and more sustainable lives.” https://lnkd.in/eYdiBUqp

Repression of mRNA translation initiation by GIGYF1 via disrupting the eIF3-eIF4G1 interaction Science Advances https://lnkd.in/geW5e2GQ

🚨 Stay up to date with the Latest Breakthroughs in Biotech! 🧬🔬 🔍 This week, we review AI applications in medicine and drug development, a newly approved Parkinson’s treatment, the positive impacts of a ketogenic diet on mental illness, and a new antiviral CRISPR tool. 🔗 For the full insights, check out the link in my bio! #Biotechnology #AI #HealthInnovation #MedicalResearch #CRISPR https://lnkd.in/gbx_p254

In the field of RNA therapy, innovative approaches based on adenosine deaminases acting on RNA (ADAR)-mediated site-directed RNA editing (SDRE) have been established, providing an exciting opportunity for RNA therapeutics. ADAR1 and ADAR2 enzymes are accountable for the predominant form of RNA editing in humans, which involves the hydrolytic deamination of adenosine (A) to inosine (I). This inosine is subsequently interpreted as guanosine (G) by the translational and splicing machinery because of their structural similarity. Intriguingly, the novel SDRE system leverages this recoding ability of ADAR proteins to correct the pathogenic G to A nucleotide mutations through a short, engineered guide RNA (gRNA). Thus, ADAR-mediated SDRE is emerging as a powerful tool to manipulate the genetic information at the RNA level and correct disease-causing mutations without causing damage to the genome.

Dr. Zanella’s talk focuses on the importance of harmonization of iPSC culture methods across different labs and industries. However, due to the multitudes of reagents and growth methods, there is significant fragmentation in iPSC growth protocols. This issue is further complicated by needing to find alternatives for components that are not fully GMP compliant. He noted that while achieving full standardization may be difficult, developing specific paradigms for certain applications could improve reproducibility and efficiency in iPSC research and clinical production.  Dr. Zanella shared his work on optimizing iPSC expansion, cryopreservation, and recovery, ensuring robust growth and preserving genetic integrity and pluripotency. His team developed a controlled, cost-effective paradigm to minimize variability and stressors, resulting in a reproducible culture protocol tailored for Pluristyx’s PluriBank™ RUO Failsafe® iPSC lines. 🧬 Experiment Design 🧬 To establish a growth paradigm using reagents that support iPSC pluripotency, expansion, cryopreservation and recovery, while having a clear path towards clinical applications, two commercially available iPSC lines were tested under two conditions: daily media changes and a "skip-day" paradigm (media changes every other day). Over several passages, viability and growth metrics were tracked. At the final passage, cells were cryopreserved and later thawed to assess recovery, viability, pluripotency, and maintenance of genetic integrity.  🧬 A Controlled and reproducible iPSC Growth Paradigm with a path to the clinic. 🧬 Both paradigms achieved success criteria, including ≥8-fold growth in 4 days, 18–24h doubling time, and ≥95% viability at harvest. Post-cryopreservation viability exceeded 85%, with preserved pluripotency and maintenance of genetic integrity. Furthermore, the skip-day method matched daily feeding, offering a less labor-intensive alternative. The final result is a tailored culture paradigm that included:  💠Laminin-521 as cell culture substrate  💠HiDef-B8 Medium (a modified version of Essential 8) as PSC medium   💠PBS-EDTA as cell dissociation reagent for clump passaging  💠CEPT Cocktail a blend of pro-survival molecules to aid in recovery  💠PluriFreeze 10 a cryopreservation reagent developed specifically for PSCs