Garri Zmudze’s Post

PHARMA STARTUPS The field of pharmaceutical science and technology is witnessing a surge in innovative startups that are transforming healthcare. Here’s a comprehensive overview: ✴ Key Areas of Innovation ❇ Drug Discovery and Development 1. AI and Machine Learning: Startups like Receptor AI are using AI to design new drugs, accelerating the discovery process. 2. Targeted Therapies: Companies such as Nuvectis Pharma focus on targeted cancer therapeutics, which aim to treat cancer more precisely and with fewer side effects. ❇ Advanced Drug Delivery Systems 1. Mesoporous Magnesium Carbonate: Disruptive Pharma is developing drug delivery systems that enhance the efficacy of medications. 2. 3D Bioprinting: Systemic Bio uses hydrogel bioprinting platforms to create complex tissue structures for drug testing. ❇ Biotechnology and Gene Therapy 1. Gene Clustering: Cryptyx Bioscience works on silent biosynthetic gene clustering, unlocking new potentials in drug discovery. 2. Microbiome-based Therapeutics: MRM Health focuses on microbiome-based treatments, which are gaining traction for their potential in treating various diseases. ❇ Digital Health and Telemedicine 1. Digital Pharmacies: Capsule offers a digital platform for managing prescriptions and delivering medications directly to customers. 2. Telehealth Solutions: Startups are integrating telehealth with pharmaceutical services to provide comprehensive care remotely. ❇ Personalized Medicine 1. Organoid Disease Modeling: Cellartgen uses organoid models to study diseases and develop personalized treatments. 2. Proteomic Drug Discovery: Protai leverages proteomics to discover new drugs tailored to individual patient profiles. ✴ Trends and Future Directions ❇ Increased Use of AI: AI is becoming integral in various stages of drug development, from discovery to clinical trials. ❇ Focus on Rare Diseases: Many startups are targeting rare and orphan diseases, which have been underserved by traditional pharmaceutical companies. ❇ Sustainability: There is a growing emphasis on sustainable practices in drug manufacturing and distribution. ✴ Notable Startups to Watch 🎯 Nuvectis Pharma: Targeted cancer therapeutics. 🎯 Mallia Therapeutics: Hair loss treatment. 🎯 CytoTronics: Non-destructive live cell analysis. 🎯 Ariceum Therapeutics: Targeted radiopharmaceuticals. 🎯 IAMA Therapeutics: Pediatric neuropsychiatric disorders. 📑 These startups are at the forefront of innovation, leveraging cutting-edge technologies to revolutionize the pharmaceutical industry. The future looks promising with continuous advancements and new breakthroughs on the horizon. #Science_and_Technology_Parks

CRISPR-Cas9-Driven Drug Screening: Customizing Cell Models for Precision Medicine CRISPR-Cas9 technology has revolutionized the field of drug screening and toxicity testing by enabling researchers to create precisely tailored cell models that mimic specific genetic variants. Through targeted gene editing, CRISPR-Cas9 enables scientists to modify genes of interest within cell lines, mimicking the genetic background of different patient populations or disease states. This innovation has important implications for high-throughput drug screening, allowing researchers to assess how genetic variants affect drug response and toxicity profiles in different genotypes. In CRISPR-Cas9-enabled drug screening approaches, specific genes in cell models are modified to reflect specific genetic mutations associated with disease or drug metabolism. Researchers can then expose these cells to various drug compounds and observe their responses. For example, a drug that performs well in a cell line with a specific oncogenic mutation can be identified as a potential candidate for patients with that genetic signature. Similarly, CRISPR-modified cells can be used to screen for drug toxicity, revealing how certain drugs can produce harmful side effects in cells with specific genetic variants. This precision approach allows scientists to determine the efficacy and safety of potential drugs in a more targeted and personalized way, reducing the likelihood of adverse reactions later in development. In addition, CRISPR-Cas9 can be used for large-scale, high-throughput testing, accelerating the process of drug discovery by rapidly screening large numbers of compounds in different genetic backgrounds. By using CRISPR to create diverse, genetically customized cell models, researchers can streamline the drug development process and select only the most promising drug candidates for further development. This strategy not only improves the efficiency of drug discovery, but also supports the development of safer and more effective treatments tailored to individual genetic characteristics. References [1] Hui Xing and Ling-hua Meng et al., Acta Pharmacologica Sinica 2019 (https://lnkd.in/g46pgumu) [2] Shady Adnan Awad et al., Cell Reports Medicine 2024 (DOI: 10.1016/j.xcrm.2024.101521) #CRISPR #DrugDiscovery #PrecisionMedicine #GeneEditing #Biotech #Pharmaceuticals #DrugScreening #PersonalizedMedicine #Innovation

Exciting Innovations in Drug Discovery: Embracing New Age Technologies In the realm of pharmaceuticals, innovation is key to unlocking groundbreaking treatments and therapies. Today, we stand at the forefront of a new era in drug discovery, where cutting-edge technologies are revolutionizing the way we approach research and development. Here’s a glimpse into the transformative advancements shaping the future of medicine: 1. AI/ML: With the power of artificial intelligence and machine learning, researchers can sift through vast amounts of data with unprecedented speed and accuracy. From identifying potential drug candidates to predicting their efficacy and side effects, AI is streamlining the drug discovery process like never before. 2. High-Throughput Screening: Automated screening platforms are enabling researchers to rapidly test thousands of compounds for their therapeutic potential. This high-throughput approach accelerates the identification of promising drug candidates, expediting the journey from bench to bedside. 3. Gene Editing and cell gene therapy: The advent of CRISPR technology has opened new avenues for precision medicine. By precisely editing genes associated with disease, researchers can develop targeted therapies tailored to individual patients, offering hope for previously untreatable conditions. 4. Virtual Drug Design: Virtual modeling and simulation techniques allow researchers to design and optimize drug molecules in silico, reducing the time and resources required for traditional trial-and-error approaches. This virtual drug design approach holds immense promise for developing novel therapeutics with enhanced efficacy and safety profiles. 5. Omics Technologies: Advances in genomics, proteomics, and metabolomics are providing comprehensive insights into the molecular mechanisms underlying disease. By leveraging omics data, researchers can identify novel drug targets and biomarkers, paving the way for personalized medicine strategies. 6. 3D Bioprinting and Organ-on-Chip: 3D bioprinting and organ-on-chip technologies are revolutionizing preclinical drug testing. These platforms replicate the complex architecture and function of human tissues and organs, offering more physiologically relevant models for evaluating drug safety and efficacy. 7. Collaborative Platforms: In an era of open innovation, collaborative platforms and data-sharing initiatives are fostering synergies across academia, industry, and government agencies. By breaking down silos and sharing resources, researchers can accelerate the pace of drug discovery and development, ultimately benefiting patients worldwide. Vipragen is set out to harness the power of these new age technologies, we embark on a journey of innovation and discovery that holds the promise of transforming healthcare and improving lives. Together, let’s continue to push the boundaries of science and unlock new frontiers in medicine. #DrugDiscovery #Innovation #healthcarerevolution

The Innovation Imperative: Pioneering New Modalities for Therapeutic Leadership -- great report from Revvity Signals, creators of the ChemDraw software I used to operate for many years during my research career. Grateful for featuring BioPharmaTrend.com's article "The Explosion of Therapeutic Modalities: Small Molecules, Biologics, and Everything in Between!" "New drug modalities encompass a broad spectrum of therapeutic strategies, each distinct in its action mechanism and target specificity. These span from monoclonal antibodies (mAbs) and RNA-based therapies to advanced gene editing techniques and cell therapies. The classification of these modalities is multifaceted, considering both their therapeutic mechanisms and stages of development. Established methods like mAbs coexist with emerging frontiers like CRISPR and CAR-T cell therapies, illustrating the breadth and depth of this field." A noteworthy trend within the small-moleculemodality is the reemergence of PROteolysis TArgeting Chimeras (PROTAC) although they were first described in 2001. This class within small molecule therapeutics Targeted Protein Degraders (TPDs), along with covalent inhibitors, and macrocycles represent an exciting frontier in small molecule therapy. TPDs, for instance, are designed to harness the body’s own protein disposal systems to eliminate disease-causing proteins, a strategy that could offer a new therapeutic angle for challenging targets. Covalent inhibitors, with their ability to form permanent bonds with target proteins, offer enhanced specificity and potency. Macrocycles, characterized by their large, ringshaped structures, present a unique balance of specificity and stability, enabling them to interact with complex protein surfaces that were previously inaccessible." Links to report and article in the comments 👇 #medicinalchemistry #drugdiscovery #biotech #biologics #biopharmatrend Image credit: Revvity Signals

"𝐂𝐞𝐥𝐥 𝐂𝐮𝐥𝐭𝐮𝐫𝐞 Insights : Advancing Biotechnology and Beyond" ▶ 𝐂𝐥𝐢𝐜𝐤 𝐇𝐞𝐫𝐞 𝐅𝐨𝐫 𝐏𝐃𝐅 : https://lnkd.in/dkEiMN_d The cell culture market comprises various consumables and equipment required at different stages of the cell culture technique to understand the basic biology and biochemistry of cells. It acts as a model system and can be used for various applications such as bioproduction, cancer research, stem cell research, diagnostics, and drug screening. 𝐀𝐬𝐢𝐚-𝐏𝐚𝐜𝐢𝐟𝐢𝐜: 𝐅𝐚𝐬𝐭𝐞𝐬𝐭-𝐠𝐫𝐨𝐰𝐢𝐧𝐠 𝐑𝐞𝐠𝐢𝐨𝐧𝐚𝐥 𝐌𝐚𝐫𝐤𝐞𝐭 Based on geography, Asia-Pacific is expected to register the highest growth rate during the forecast period. The growth of this regional market is driven by the growing recognition of the region as a major outsourcing destination for pharmaceuticals & biopharmaceuticals companies, rapidly developing economies, and growing aging population coupled with the rising prevalence of chronic diseases and developing research infrastructure in this region. #Drivers 1. Growth in the Biopharmaceutical Market  2. Rising Demand for Biopharmaceuticals 3. Strong R&D Pipeline for Biopharmaceuticals 4. Government Initiatives to Promote Biosimilars 5. Capacity Expansions of Biopharmaceutical Plants 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: -Bioproduction -Monoclonal Antibody Production -Therapeutic Protein Production -Vaccine Production -Cell and Gene therapy -Drug Screening & Development -Cancer Research -Stem Cell Research -Other Applications TOP 10 COMPANIES IN CELL CULTURE MARKET https://lnkd.in/dpD493Hy #CellCulture Market by Product [#Consumables (#Media, #Reagents, #Sera, #CellLines), Equipment (#Bioreactor, #Centrifuge, #CellCounter)], Application (#Bioproduction, #CancerResearch, #StemCell, #Diagnostic), End User (#Pharma, #academic)

The combination of AI, mRNA, and CRISPR 2.0 is definitely reshaping the landscape, and quantum computing's potential is mind-blowing. One area I’m excited about (a bit biased 🧠) is its application for neuroscience drug discovery! With advancements in neurodegenerative treatments, like targeting misfolded proteins in Alzheimer’s and Parkinson’s, researchers are unlocking new ways to approach brain health. It’s incredible to see these innovations bringing us closer to groundbreaking therapies. It's a fascinating time for drug discovery, and we at Radyus Research are excited to support these innovations to help bring transformative therapies to market! #DrugDiscovery #Neuroscience #Biotech #AI #CRISPR #QuantumComputing #FutureOfMedicine #RadyusResearch #lifescience #Biotechnology

With the FTC investigation into the PBMs all over the news, I dove into the Social Capital 89-slide primer on drug development last night. Here are some of my takeaways: 1️⃣ The Odds Are Tough: Only about 5% of all drugs make it to commercial launch. Developing a new drug takes 10 to 15 years and requires over $1 billion in capital. Astonishingly, only 1 in 20 drug companies successfully bring a product to market. This underscores the immense risk and investment required in this field. 2️⃣ Investment Trends: Despite the low odds, venture capital funding for U.S. biotech companies remains robust. Investments grew from $86 billion in 2018 to a peak of $157 billion in 2021, before decreasing to $85 billion in 2023. In 2022, companies focused on oncology led the way with 118 financing rounds, followed by neurology, infectiology, immunology, and gastroenterology. Investment returns are low in this high risk/high reward drug discovery game as it typically returns less versus software & technology hardware firms. 3️⃣ Genomic Revolution: decoding of the human genome in 2003 was a pivotal moment in scientific history. It provided a complete map of human genetic information, significantly advancing medical research. Before this, genetic research relied heavily on trial and error. 4️⃣ CRISPR-Cas9 Breakthrough: Building on genomic mapping, CRISPR-Cas9 emerged as a groundbreaking gene-editing tool, allowing precise modifications to DNA. This has unlocked new classes of biologic drugs, including gene therapies that correct genetic mutations and cellular therapies like CAR-T therapy, which edit immune cells to fight cancer. 5️⃣ Advancements in Sequencing and Data Analysis: Next-generation sequencing (NGS) revolutionized genomics by enabling the simultaneous sequencing of millions of DNA fragments. This bolus of biological data necessitated new methods for data analysis, coinciding with breakthroughs in AI/machine learning. 6️⃣ Machine Learning's Impact: ML models, trained on vast genetic datasets, can analyze and predict genetic characteristics and outcomes. The combination of NGS and ML has opened new avenues in genomics, epigenomics, transcriptomics, and proteomics. 7️⃣ Efficiency Gains: Machine learning could potentially reduce the cost of drug development through the first two stages by 70% and reduce the time by 50%. For an optimistic person this could lead to cheaper therapies with lower costs/barriers to developing drugs in therapeutic areas with monopolies. 8️⃣ Market Pressures: Because drug development is so capital-intensive, companies are often forced to IPO sooner, creating more pressure in capital markets. An average Series B of 200 million with the pressure to go public sooner to fund clinical trials. As someone involved in ChadTough Defeat DIPG Foundation I'm excited to see how these trends will help find a cure for pediatric brain cancer. Pretty high level overview by Social Capital that I found easy to follow.

🚀 CRISPR-Cas9: Revolutionizing Drug Screening and Precision Medicine 🧬 In the ever-evolving field of biotechnology, CRISPR-Cas9 technology stands out as a game-changer, particularly in drug screening and toxicity testing. This innovative approach allows researchers to create precisely tailored cell models that mimic specific genetic variants, paving the way for more effective and personalized treatments. 🔬 Customized Cell Models for Precision Medicine: CRISPR-Cas9 enables scientists to modify genes within cell lines, reflecting the genetic background of different patient populations or disease states. This precision is crucial for high-throughput drug screening, allowing us to assess how genetic variants affect drug response and toxicity profiles across various genotypes. 💡Targeted Drug Screening: By editing specific genes in cell models to mirror genetic mutations associated with diseases or drug metabolism, researchers can expose these cells to various drug compounds and observe their responses. For instance, a drug that shows promise in a cell line with a particular oncogenic mutation can be identified as a potential candidate for patients with that genetic signature. ⚠️ Enhanced Toxicity Testing: CRISPR-modified cells also play a vital role in screening for drug toxicity. This process reveals how certain drugs can produce harmful side effects in cells with specific genetic variants, ensuring safer and more effective treatments. ⏩ Accelerating Drug Discovery: The ability to conduct large-scale, high-throughput testing with CRISPR-Cas9 accelerates the drug discovery process. Researchers can rapidly screen numerous compounds across different genetic backgrounds, streamlining the development of promising drug candidates. 🌟 Towards Personalized Medicine: By creating diverse, genetically customized cell models, CRISPR-Cas9 supports the development of treatments tailored to individual genetic characteristics. This strategy not only improves the efficiency of drug discovery but also enhances the safety and efficacy of new therapies. Join us in celebrating this groundbreaking technology that is transforming the landscape of drug discovery and precision medicine. Together, we can pave the way for a future where treatments are more personalized, effective, and safe. #CRISPR #Biotechnology #DrugDiscovery #PrecisionMedicine #Genetics #HealthcareInnovation #MedicalResearch #MedicalLaboratoryTechnology #Microbiology #Phlebotomy #LaboratoryTesting #DiagnosticTesting #HealthcareProfessional #MedicalTesting #ClinicalLaboratory #BiomedicalScience #HealthcareIndustry #MedicalScience #LaboratoryMedicine #ClinicalMicrobiology #InfectionControl #PhlebotomyTechnician #MedicalLabTechnician #MicrobiologyLab #ClinicalLab #HealthcareCareer #MedicalCareer #ScienceCareer #COVID19Testing #Virology #Bacteriology #Parasitology #MolecularDiagnosis #GeneticTesting #Cytology #Histopathology #Immunology #Serology

A very good framework to identify use cases of AI in Research and Clinical Development . Select use case descriptions provided here (not exhaustive) Drug Discovery--> Biomarkers Discovery: Identify new biomarkers that can be used to predict the progression of a disease. Drug Discovery : Virtual screening, lead optimization, and ADME-Tox prediction to identify and optimize potential drug candidates. Oncology Diagnostics and Treatment---> Clinical Decision Support : Provide personalized treatment recommendations and predict the response to a specific treatment. Patients Outcome Prediction: Analyze medical images, patient data, and treatment history to predict the likelihood of cancer recurrence Early Drug Development--> Target Identification :Analyze large amounts of data from genomics, transcriptomics, proteomics, and other high-throughput data sources. Compounds Classification : Classify large numbers of compounds and find best candidates. Predictive Drug Modeling: Identify patterns in data and make predictions about the potential effectiveness of a drug candidate. Lead Optimization: Optimize the properties of the hit compound to increase its potency, specificity, and pharmacokinetic properties. Virtual Screening: Identify the most promising drug candidates by filtering through large libraries of compounds. Hit Identification: Rapidly analyze and filter large libraries of compounds, helping to identify the most promising candidates for hit identification. Drug Repurposing: To analyze large amounts of data from various sources to identify new indications for existing drugs. Clinical Drug Development--> Identifying Suitable Patient : Analyze large amounts of clinical data and to identify patterns and characteristics that indicate a patient's suitability for a specific trial. Predictive Modeling :Identify patterns in data and make predictions about the potential effectiveness of a drug candidate. Preclinical Development --> ADME/PK Modeling: To predict the absorption, distribution, metabolism, and excretion (ADME) and pharmacokinetics (PK) of compounds Drug Safety Improving : Analyze preclinical trials data and identify potential side effects and predict interactions with other drugs. Preclinical Protocol Optimization: To analzye data from previous preclinical trials to identify patterns and make predictions about the best protocol design for future trials. High Throughput Screening: Identify compounds or genetic variations that have the desired activity or property End-to-End Drug Development---> Predictive Patient Reaction Modeling : Identify patterns in data and make predictions about the potential effectiveness of a drug candidate. Data Processing :Clinical Trials Data , Imaging Data, Lab Experiments Data and Chemical Data Source: www.deep-pharma.tech #artificialintelligence #drugdiscovery #clinicaltrial #oncology #generativeai #biomarkers #imaging #machinelearning Disclaimer: The opinion are mine and not of employer's