CO/AI’s Post

this week in bio: - controlling gene expression using direct current stimulation via a bioelectronic interface to treat diabetes - a framework for assessing data quality for drug discovery (volume, variety, velocity, veracity, and value) - the current state of generative AI for peptide and small molecule design (insufficient access to therapeutically-relevant datasets that move beyond binder design is the most important bottleneck) - MultiMedBench, a new benchmark for evaluating generalist biomedical AI from Google and Deepmind - theories of cancer’s origins, including somatic mutation theory, tissue field organization theory, ground state theory, and gold ol’ fashioned bad luck - a case study on how $1.6B was spent on 16 IGF-1R inhibitors for oncology, with no approvals, and how to improve pre-clinical models and organizational decision making before nominating clinical candidates https://lnkd.in/gJiBSZg4

🔬 Artificial intelligence is science and not just technology As a passionate advocate for the integration of AI in the pharmaceutical sector, I firmly believe that AI is science and not just technology. And when developed with this mindset it has a true potential for impact. At AnalysisMode our AI models are designed to deeply understand the complexities of biological materials, such as antibodies, cell therapies, and gene therapies. Our focus at AnalysisMode is clear: we aim to revolutionize the drug development process. By leveraging advanced AI, we can cut down on the time and cost it takes to develop these life-saving treatments. Imagine accelerating the journey of a new gene therapy from concept to clinical use, ensuring it reaches patients faster and at a lower cost. This isn't just about making drugs more affordable; it's about bringing cutting-edge therapies—like personalized cell therapies for cancer or novel antibodies for autoimmune diseases—to those who need them most, sooner. AI allows us to predict biological interactions with greater accuracy, optimize experimental designs, and streamline experiments. I'm genuinely excited about the tangible impact we can make on people's lives. By pushing the boundaries of AI in drug development, we are not just advancing science—we are improving real-world health outcomes. 🚀 #AI #Science #Pharma #Biotech #DrugDevelopment

"Exploring the Synergy of CRISPR Technology and Quantum Computing" here's what I would do, if I was asked to make something new to further enhance the #crispr technology for optimum speed and accuracy. In the ever-evolving landscape of biotechnology, the marriage of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and quantum computing (QC) unveils a promising frontier for revolutionary advancements. Let's delve into the potential solutions this dynamic duo can provide. **Optimizing Genetic Analysis:** CRISPR technology, known for its precise gene-editing capabilities, encounters complex computational challenges in genetic analysis. Quantum computing's unparalleled processing speed could significantly expedite the identification of target genes, unraveling new possibilities for therapeutic interventions. **Enhancing CRISPR Processes:** The synergy between CRISPR and quantum computing holds the potential to streamline and enhance the efficiency of gene-editing processes. Faster and more accurate simulations empowered by QC may contribute to predicting outcomes and potential side effects, thereby advancing the field of personalized medicine. **Paving the Way for Precision Medicine:** The integration of CRISPR and quantum computing not only accelerates genetic research but also opens avenues for precision medicine. This synergy could usher in a new era where tailor-made treatments for genetic diseases become more feasible and precise. As technology continues to converge, the collaboration between CRISPR and quantum computing showcases a promising trajectory for the future of biotechnology. The acceleration of genetic research and the refinement of gene-editing techniques may lead us towards a realm of possibilities previously deemed unreachable. What are your thoughts on this convergence of CRISPR and quantum computing? 🧬💻 #Biotech #CRISPR #QuantumComputing #TechAdvancements

Other ways are **1. Drug Discovery and Design:** The amalgamation of CRISPR and quantum computing could revolutionize drug discovery. Quantum computers may expedite the simulation of molecular interactions, aiding researchers in designing pharmaceuticals with greater precision. This accelerated process could lead to the development of more effective and targeted medications. **2. Quantum Machine Learning for Genetic Data:** Quantum machine learning algorithms could be applied to vast sets of genetic data, complementing CRISPR's capabilities. This fusion might uncover hidden patterns and associations within genomic information, providing deeper insights into the functions of genes and potential therapeutic targets. **3. Quantum Encryption for Genetic Privacy:** As genetic data becomes increasingly valuable and sensitive, quantum encryption techniques could be integrated into the storage and transmission of genomic information. This heightened security could address concerns related to genetic privacy, ensuring the confidentiality of individuals' genetic profiles. **4. Simulation of Biological Systems:** Quantum computing's ability to simulate complex biological systems could enhance our understanding of intricate cellular processes. This could lead to more accurate predictions of how gene edits might impact entire biological systems, contributing to safer and more effective CRISPR applications. **5. Ethical Considerations and Governance:** The collaboration of CRISPR and quantum computing raises ethical considerations regarding the responsible use of advanced technologies. Developing robust governance frameworks to address ethical concerns, privacy issues, and potential misuse becomes crucial as these technologies advance. **If I'm been sincere , I see numerous opportunities here. The convergence of CRISPR and quantum computing not only holds promise for breakthroughs in medicine and genetics but also prompts us to carefully navigate the ethical dimensions of this transformative synergy. How do you envision the ethical considerations surrounding the integration of these technologies? 🔬🔐 #CRISPR #QuantumComputing #Biotech #TechEthics

Predicting RNA structures and functions by artificial intelligence. https://lnkd.in/erQBH7FQ "RNA is essential for a variety of biological processes, including protein synthesis and gene regulation. Understanding RNA structure-dependent regulatory mechanisms and cellular functions could help develop better RNA-based therapeutics. The structural flexibility, target binding, and environmental circumstances are just a few examples of the many variables that may affect RNA function. Given their complexity and dynamic nature, it is difficult to predict and analyze RNA structure and function accurately. Many fields have benefited significantly from advances in artificial intelligence (AI) technology, which has also opened previously unimaginable possibilities for understanding RNA structure and function. Recent progress in AI-based techniques for predicting RNA structure and function as well as RNA design provide directions and insights for future research on the sequence–structure–function relation of RNAs." Interesting review by Jun Zhang and larger team

RNA structures and their functions

Human cell is astonishingly complex!! A gene inside the cell, when activated by a cell signal, crafts an mRNA blueprint for protein creation. Yet, within the same cell, its expression varies based on diverse signals. This gene function is governed by a web of complex interactions as follows: - Cell Type Specificity: Gene expression varies across cell types due to unique transcription factors and regulatory elements. - Signal Dynamics: Gene expression is influenced by the strength and duration of signals. - Combinatorial Signals: Multiple signals can jointly determine gene expression levels. - Feedback Loops: Genes can self-regulate, altering their own expression based on feedback. - Epigenetic Context: Chromatin structure and modifications affect gene responsiveness. - Post-Expression Adjustments: mRNA and protein modifications post-transcription and translation impact final outcomes. - Cellular Ambiance: The cell's internal factors can tweak a gene's response to signals. - Gene Interactions: A gene's response can be influenced by the activity of its peers. Cognit AI is on the brink of unlocking these complexities, offering unprecedented insights into the world of genomics. Are you intrigued? Cognit AI is the pioneer in crafting the first Generative AI-based "Large Genomic Model" from ground up, designed to pinpoint diseases with remarkable functional precision. This innovation empowers life-science researchers to accelerate the creation of therapeutics for complex polygenic diseases, paving the way for enhanced longevity. Do keep an eye on this space ;) 🚀 #Genomics #AI #FutureOfBiology #ArtificialIntelligence

AI Revolutionizes Pharma & Biotech: Ushering in a New Era of #DrugDiscovery The global AI in pharma and biotech market is poised for explosive growth, projected to reach US$ 13.1 Bn by 2034. This surge is driven by the transformative power of AI in streamlining drug development and unlocking new possibilities in #geneediting. Here's why #AI is taking center stage: Faster #DrugDiscovery: AI algorithms can analyze vast amounts of data to identify promising drug candidates, significantly reducing time and cost associated with traditional methods. Enhanced Clinical Trials: AI-powered platforms can simulate clinical trials, accelerating the development process and paving the way for more effective treatments. Precision #MedicineRevolution: AI plays a crucial role in developing personalized treatment plans by analyzing individual genetic data. Genome Editing Breakthroughs: AI assists in predicting and optimizing techniques like CRISPR-Cas9, leading to more precise and effective gene editing therapies. This is just the beginning! We can expect continued innovation in areas like: AI-powered drug design: Tailoring drugs to specific disease targets and patient populations. Advanced #clinicaltrial optimization: Refining trials for greater efficiency and patient safety. Breakthroughs in gene therapy: Utilizing AI to unlock the full potential of gene editing for a wider range of diseases. Get detailed insights: https://lnkd.in/dYVw9KFF Is your organization ready to embrace the #AIrevolution? Join the discussion! #AIinPharma #DrugDiscovery #FutureofHealthcare #marketexpert #researchstudy

WHAT IS CRISPR TECHNIQUE? CRISPR, or Clustered Regularly Interspaced Short Palindromic Repeats, is a revolutionary gene-editing technology. The basic CRISPR technique involves: ✅Guide RNA (gRNA) Design: A synthetic gRNA is created to match the target gene sequence. ✅Cas9 Protein: The Cas9 protein, acting as molecular scissors, is guided by the gRNA to the specific DNA sequence. ✅DNA Cleavage: Cas9 cuts the DNA at the target site, initiating the cell's natural repair mechanisms. ✅Repair Process: The cell repairs the cut using either non-homologous end joining (NHEJ) or homology-directed repair (HDR), resulting in gene modifications. These modifications can include gene disruptions, insertions, or replacements, enabling precise genome editing. The simplicity and versatility of CRISPR have made it a powerful tool in biological research and potential therapeutic applications. Thank you for reading 🕺❤️

Artificial intelligence is playing a revolutionary role in DNA research and molecule development. By quickly and efficiently analyzing vast datasets, AI aids in identifying potential drug targets and optimizing drug candidates, accelerating the traditional drug discovery process. In developing new molecules, AI platforms are proving instrumental. They design molecules based on polypharmacology, which targets multiple disease pathways at once. Leading to advancements in the discovery of potential therapeutic molecules. Furthermore, AI is greatly impacting research and development in DNA and molecular biology. The technology helps in identifying target genes, predicting gene functions, and understanding genetic variations. It's a significant contributor to gene activation research and the development of gene therapies. In the forthcoming blog, we will explore the impact of AI on improving DNA sequencing and analysis, integrating data, and fostering collaboration in the scientific community. The crucial role of human expertise and domain knowledge in AI utilization will also be discussed. Stay tuned for a compelling discourse! Full Article found here : https://lnkd.in/gYu_-VF5