Discovery by Axial

Discovery by Axial provides an in-depth analysis of the latest trends, innovations, and research within the life sciences sector. It covers advancements in microscopy, immunometabolism, biomanufacturing, kidney disease, life sciences marketplaces, voice technology in healthcare, personalized trials, phenotypic screening, machine learning for drug discovery, cell therapies for autoimmunity and fibrosis, CRISPR technology, and financial aspects of drug development.

Life Sciences Innovation Drug Discovery and Development Biomanufacturing Disease Treatment and Therapies Healthcare Technology Genetic Engineering Clinical Trials Market Trends in Life Sciences

The hottest Substack posts of Discovery by Axial

And their main takeaways
21 implied HN points 28 Nov 22
  1. Fluorescent dyes are crucial for microscopy innovations and breakthroughs in biology.
  2. Innovations in super-resolution microscopy depend on the development of diverse and brighter dyes.
  3. Progress in dye design is essential for advancing live-cell imaging, drug discovery, and molecular research.
6 implied HN points 14 Mar 23
  1. Metabolism in tumor microenvironments affects immune cell function and responses to therapies.
  2. Companies are exploring targeting metabolism to treat cancer, but the field is complex.
  3. Opportunities in immunometabolism research include measuring metabolic differences, assessing immune cell requirements, and targeting weak spots for new medicines.
3 implied HN points 18 May 23
  1. Outsourcing marketplaces in life sciences have emerged with companies like Science Exchange providing trust and confidentiality for R&D services.
  2. Talent marketplaces are growing in the field of life sciences, with platforms like Clora matching consultants with companies and projects.
  3. Marketplaces for consumables and reagents (C&R) in life sciences offer opportunities for connecting suppliers and customers, such as Quartzy and Zageno.
3 implied HN points 27 Mar 23
  1. Phenotypic screening focuses on identifying specific physical or biochemical traits of interest for drug discovery.
  2. Key rules for effective phenotypic screens include selecting relevant cell models, designing disease-specific assays, and defining clinical-like endpoints.
  3. Advancing phenotypic screening requires improving throughput of complex models, developing translational disease models, enhancing proteomic tools, and integrating phenotypic and target-based screening.
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3 implied HN points 06 Mar 23
  1. Kidney disease affects over 30 million people in the US with high healthcare costs.
  2. New tools like genomics, proteomics, and metabolomics show promise in understanding kidney biology and drug development.
  3. CKD is a big opportunity for new treatments, focusing on new MoAs like loss of podocytes, chemokines, JAK inhibitors, and ECM deposition.
3 implied HN points 27 Feb 23
  1. N-of-1 trials focus on understanding individual patient responses to interventions.
  2. N-of-1 trials are valuable for rare diseases, chronic pain, and long-term treatments.
  3. Using N-of-1 trials can help in predicting response to medications and improve drug development for rare conditions.
3 implied HN points 20 Feb 23
  1. Voice technology in healthcare can help patients and doctors by transcribing conversations and reducing errors.
  2. Companies like Abridge and Suki are developing voice products to enhance patient care and doctor efficiency.
  3. Building voice assistants for healthcare has potential for personalized patient and doctor interactions, but faces technical challenges and privacy concerns.
3 implied HN points 13 Feb 23
  1. DNA-encoded libraries (DEL) use unique DNA barcodes to screen billions of chemical compounds efficiently.
  2. Machine learning is being utilized in DELs to train models for virtual screening and map out structure-activity relationships more rapidly.
  3. Challenges in DELs include improving diversity, developing better filters for virtual screening, and expanding screens to select for features like toxicity and ADME.
1 implied HN point 08 Sep 23
  1. Clinical trial statistical analysis involves collecting and interpreting data to evaluate new treatments.
  2. Startups have opportunities to develop software for automating and streamlining statistical analysis processes due to increasing data complexity.
  3. Software development for data integration, visualization, and communication can improve efficiency in clinical trial statistical analysis.
2 HN points 05 Dec 22
  1. High fidelity CRISPR gene editing is transforming medicine with the promise of potential cures for genetic diseases.
  2. Success in gene editing depends on refining CRISPR proteins into products and developing successful medicines.
  3. Different versions of CRISPR, like base editing and prime editing, continue to evolve to increase fidelity and efficiency in editing DNA for potential disease treatments.
2 HN points 21 Nov 22
  1. Cell therapies are being explored to cure autoimmunity, such as using CAR-T therapies to treat diseases like lupus.
  2. Lupus, an autoimmune disease, has a complex history of drug development, and new technologies like cell therapies are offering hope for better treatment options.
  3. Advancements in precision medicine from oncology are being adapted to autoimmune diseases like lupus, paving the way for potential cures and better management of symptoms.