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        "body": "**tl;dr:** Signatur Biosciences is a B2B molecular diagnostics design company. Our technology expands PCR testing to a whole new range of conditions. We design smart PCR kits that can detect complex diseases as easily as a COVID test, using standard qPCR machines. Our tests seamlessly integrate into existing clinical workflows and ubiquitous laboratory instruments, empowering us to become _the_ enabling technology platform for a $20B industry.\n\n👋 Hey everyone! We’re Celestin and John. We are determined to transform the state of medical diagnostics. We set out to find a solution that delivers state-of-the art diagnosis on ubiquitous instrumentation to put cutting-edge healthcare within the reach of everyone, everywhere.\n\n### **The Problem.**\n\nRight now, PCR testing is limited to simple diseases. Covid is a good example. You take a sample from a patient and look for one biomarker. If the biomarker is there, the patient has the disease; no biomarker, no disease. Simple.\n\nBut most conditions aren't that simple. There’s a $20B industry using _patterns_ of multiple biomarkers that diagnose complex diseases, but to deploy their tests they’re relying on legacy technologies that are too slow and expensive to really help people, limiting their market reach.\n\n### **🧬 Signatur Biosciences’s solution.**\n\nOur platform expands PCR testing to a whole new range of conditions, beyond just infectious disease to include everything from chronic diseases, treatment selection, and disease monitoring.\n\nWe have re-engineered the molecular architecture of the polymerase chain reaction, empowering it to process the information from multiple biomarkers simultaneously. We combine the power of gene signature diagnosis with the **_ease and familiarity of a single PCR reaction._**\n\nEvery biomedical lab in the planet is equipped with PCR machines. This was true before the pandemic. But as a response to the pandemic, the PCR testing capacity in the US has increased by 5500% (3000% in the UK). We are giving those machines something new to do.\n\n### **🚀 How can Signatur Biosciences help me?**\n\nWe are partnering with companies to design our platform around their biomarker panels, offering broader market reach bringing such tests to more patients.\n\nIn parallel, we are building our own assay portfolio. We are developing our own internal pipeline of tests to tackle diseases that can only be interrogated by our technology.\n\n### **How you can help.**\n\nWe are looking for introductions to companies in the molecular diagnostics space. This could be companies developing portable hardware. Specifically developing genomic testing, or assays based on gene expression analysis.",
        "url": "https://www.ycombinator.com/launches/Gl3-signatur-biosciences-diagnoses-anything-with-a-simple-pcr-test",
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        "body": "Hello! We’re Bryan and David, the founders of [InVision](http://invisionmedtech.com/). At InVision, we develop AI tools to quickly and accurately diagnose heart disease. \n\n### **Challenges in Diagnosing Heart Disease**\n\n32 million heart ultrasounds are performed in the United States each year to diagnose heart disease. Acquiring and interpreting ultrasounds is time-consuming, requiring over an hour of physician and technician time for each exam. Additionally, there exists considerable human-to-human variability when interpreting the ultrasounds, resulting in misdiagnosis and underdiagnosis of heart disease. \n\n### **Our Solution**\n\nAt InVision, we use AI to help streamline the interpretation of ultrasounds and identify undiagnosed diseases. Our models have been tightly integrated into the clinical workflow to allow easy usage by clinicians. We’re leading the first and only blinded randomized trial of AI technology in cardiology, and we will be presenting as a [headliner clinical trial](https://twitter.com/David_Ouyang/status/1562834463343935491) at the largest cardiology conference ([European Society of Cardiology](https://www.escardio.org/Congresses-&-Events/ESC-Congress)) meeting tomorrow!\n\n### **About us**\n\nDavid majored in Statistics at Rice University, did his MD at UCSF, and did residency and fellowship training in cardiology at Stanford University. David then worked as an attending cardiologist at Cedars Sinai Medical Center, a leading heart health system which will be the first site of deployment of our technology. Bryan majored in CS at Caltech and did his CS PhD at Stanford. Together, we've worked together on this project for the last 4 years, first as a research project and now as clinical deployment of a viable product.\n\n### **Where We Are**\n\nOur work has previously been peer-reviewed and published in several top medical venues, including Nature (2020), Nature Medicine (2021), Lancet Digital Health (2021), JAMA Cardiology (2022). Results from our blinded and randomized clinical trial on evaluating cardiac function have also been recently presented as a Late Breaking Clinical Trial at the European Society of Cardiology.\n\nWe are currently working on securing FDA clearance for our heart failure model and starting up clinical trials for our model screening for cardiac amyloidosis, hypertrophic cardiomyopathy, and aortic stenosis.\n\n### **How You Can Help**\n\nIf you or anyone you know would be interested in helping out, we’d be grateful for introductions to:\n\n* Companies who have previously gone through the FDA regulatory process\n* Investors interested in medical technology\n* Hospitals and medical device manufacturers that may be interested in our product\n\nWe can be reached at [founders@invisionmedtech.com](mailto:founders@invisionmedtech.com). Thanks!",
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        "body": "Pando is an AI-driven synthetic biology company revolutionizing enzyme engineering for pharma. Our ultra-high-throughput screening platform screens 1000 times more enzymes, 75% faster, and 80% cheaper than traditional methods. This empowers our generative AI to optimize enzymes across multiple properties, delivering high-performing, tailored enzymes that cut costs and enhance efficiency.\n\n### The Problem\n\nEnzymes play a crucial role in driving market growth and profitability in the pharmaceutical industries. Inefficient or underutilized enzymes can lead to significant financial losses and missed opportunities. Therefore, developing optimized enzymes that possess a balance of key properties becomes a top priority but remains challenging and time-consuming.\n\n### Our Solution\n\nOur AI model designs enzymes with specific mutations that enhance multiple properties simultaneously. These AI-generated enzymes are tested using our unique ultra-high-throughput one-pot screening platform. This platform converts diverse biological signals into abundant and quantifiable data under various conditions. By integrating AI design with advanced screening, we’ve reduced the design-build-test-learn cycle to just one month. We efficiently evaluate enzyme performance across different criteria tackling the challenge of multi-property optimization.\n\nAt Pando, we help pharma companies improve existing enzymes and discover new ones, cutting costs and boosting productivity. We are also developing our own proprietary enzyme assets.\n\n### Our Team\n\nWe are experts in the field. @Will joined the synthetic biology unicorn Ginkgo Bioworks as an early employee. @Yang spent 6 years at Harvard Medical School before joining Ginkgo. AI-guided enzyme engineering is in our wheelhouse.\n\n### Want to be part of it?\n\nIf you are from a **pharma, diagnostic, or biotech company** and are interested in taking enzyme engineering to the next level, please don't hesitate to reach out to us at [founders@pando.bio](mailto:founders@pando.bio).\n\nThank you!\n\n![uploaded image](/media/?type=post&id=69169&key=user_uploads/875330/303f90f4-0887-4557-92b3-47f2bd20a39f)\n\n",
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        "title": "💧🧬Cleancard - Making cancer screening as easy as a pregnancy test",
        "tagline": "Combining SynBio and AI to make rapid and reliable at-home cancer testing possible",
        "body": "**Tl;dr:** We’re Cleancard, a pair of Rhodes Scholars on a mission to reinvent cancer diagnostics. We combine synthetic biology + AI to create powerful at-home cancer tests, with results from urine in just 30 minutes. **Check out our **[**website**](https://www.cleancard.bio/)** for more!**\n\nHey everyone - we’re Tom and Luca, the co-founders behind Cleancard!\n\n![uploaded image](/media/?type=post&id=73949&key=user_uploads/863380/9ea23e71-c6d5-4715-8236-7ed89e1d6a90)\n\n👨🏻 [Tom](https://www.linkedin.com/in/thomas-carroll-62a60367/): Clinical cancer researcher, expert in bioinformatics and methods development. No stranger to designing [better biomarker tests](https://www.cell.com/cancer-cell/fulltext/S1535-6108(23)00216-7). 👨🏻‍🦰 [Luca](https://www.linkedin.com/in/luca-springer-b3801b8a/): Computer scientist with a strong healthcare policy background. Years of experience growing healthtech and consumer businesses.\n\n### **Early cancer detection saves lives 🕑**\n\nMore than 18M Americans have cancer today. Unfortunately, this is a growth market (26M projected by 2040). 1 in 3 have a close family member with a history of cancer, and thus have a higher risk for cancer themselves (2x). We know these realities all too well from our personal lives, dealing with hereditary cancer syndromes and family histories of cancer.\n\nCancer will come for many of us. To give ourselves drastically better odds of surviving this disease, we need to diagnose it before it reaches an advanced stage.\n\n![uploaded image](/media/?type=post&id=73949&key=user_uploads/863380/10066d6b-22e6-4e98-a5cf-4fc34047d766)\n\n### **Problem: Cancer screening is failing us 🤬**\n\n* Cancer symptoms are often unnoticeable until the cancer is too advanced to cure\n* Current lab-based screening tests are **time-consuming** and **costly** - they fail to get people to screen before they are symptomatic (even for PSA, only [1 in 3 participate](https://jamanetwork.com/journals/jamaoncology/fullarticle/2797845))\n* At-home rapid tests would increase rates of asymptomatic screening but **just don’t perform well enough** to be trusted for cancer diagnostics\n* Current options are **not sufficient** to give people their best chance at surviving cancer\n\n### **Solution: Cleancard’s rapid testing platform 😍**\n\nWe’ve built a new rapid-test method enabling highly sensitive biomarker-guided diagnostics from the urine in just 30 minutes. Key advantages of our proprietary technology:\n\n* **10x quicker/cheaper** than lab-based tests\n* **10x more sensitive** than lateral flow\n* **No expensive machinery** or **complicated sample manipulation**.\n\nSee how we stack up:\n\n![uploaded image](/media/?type=post&id=73949&key=user_uploads/863380/ed2218af-7627-4f5b-9d17-7adec46c6632)\n\nCleancard technology combines synthetic biology, machine learning, and computer vision into a multiplexable, machine-readable format which allows us to detect multiple cancer biomarkers from a single sample.\n\nOur first rapid at-home screens will identify prostate, bladder, and ovarian cancers. Our method is highly agile - we’ve successfully targeted 10 new cancer biomarkers during this YC batch alone, with more to come soon. \n\nCleancard’s platform is the one-stop shop for reliable detection and tracking of multiple cancer biomarkers in the comfort of your own home.\n\n### **Our asks 🙏**\n\n* **Share this post!** Please help us spread the word with your networks.\n* **Join our team!** We are always looking for highly motivated scientists and engineers to join us in our mission to reinvent cancer diagnostics. If that’s you or someone you know, please get in touch ([contact@cleancard.bio](mailto:contact@cleancard.bio)).",
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        "id": 92017,
        "title": "Amina: The Agentic Protein Engineer",
        "tagline": "Design, simulate, and test your proteins 100x faster with our no-code platform for protein engineering!",
        "body": "**👋 Hey YC! We're Abhi and Adam from AminoAnalytica.**\n\n**Amina is the first AI agent for end-to-end protein engineering** – instead of wrestling with hundreds of fragmented tools, scientists can now design protein therapeutics through simple conversation.\n\n## **🎬 Trailer**\n\nhttps://www.youtube.com/watch?v=n8Pd9BJcbQA\n\n## **🧬 The Problem with Programmable Biology**\n\nThe 2024 Nobel Prize for Chemistry went to AlphaFold - proving we can predict and design proteins like software. These biological machines could solve climate change, cure diseases, and manufacture anything we need.\n\nBut here's the reality: **hundreds of new computational biology tools launch every week.** Even expert researchers stick to the same old methods they know, missing breakthrough tools that could accelerate their work by months or years.\n\n**Meet Dave, your friendly neighborhood protein engineer** 👨‍🔬\n\nDave is designing a cancer therapeutic, but his current workflow is broken:\n\n* **Inaccessible tools** → most have no UI, require specific hardware, must be built from source\n* **Fragmented ecosystem** → tools don't work together, requiring pages of glue code\n* **Constant obsolescence** → by the time he masters one tool, three better ones have launched\n\nThe result? **Scientists spend more time debugging code than designing life-saving therapeutics.**\n\n## **🚀 Our Solution**\n\n**What if you could just describe what you want in plain English?**\n\nInstead of wrestling with complex pipelines and staying up-to-date with every new tool, you simply tell Amina what protein you need and why.\n\n**Dave before Amina:**\n\n![uploaded image](/media/?type=post&id=92017&key=user_uploads/1754946/ad201bdd-6ed8-4b33-bb1f-fd8ca58f5262)\n\n**Dave with Amina:**\n\n![uploaded image](/media/?type=post&id=92017&key=user_uploads/1754946/3657d135-74af-4ed9-b261-394f14fe42a5)\n\n## **🔬 What Makes Amina Different**\n\nThis isn't just model hosting. Amina is trained on both scientific literature and our proprietary experience from engineering thousands of proteins for customers - it knows which tools to use when, how to chain them together, and how to interpret results. It's like having our entire computational team's expertise distilled into a single agent.\n\nWith our no-code interface, 50+ specialized tools work together seamlessly. Amina catches potential issues, suggests optimizations, and explains results in plain English.\n\n## **🎯 Our Vision**\n\n**Our ultimate goal is for Amina to design proteins autonomously** - think JARVIS, but dedicated to discovering breakthrough therapeutics. For now, it's like having an extra bioinformatician on your team that needs less care and attention than your cell cultures.\n\n## **🙏 Our Ask**\n\n**If you work in biotech, pharma, or have an interest in protein engineering** - we'd love your feedback on Amina.\n\n**Try it for free at [aminoanalytica.com](http://aminoanalytica.com)** - no setup required, start designing in 60 seconds.\n\nNeed extra credits? Just message us at [support@aminoanalytica.com](mailto:support@aminoanalytica.com)",
        "url": "https://www.ycombinator.com/launches/Nw9-amina-the-agentic-protein-engineer",
        "votes": 15,
        "created_at": "2025-07-09T18:31:25.117Z"
      },
      {
        "id": 82706,
        "title": "🧬 AminoAnalytica – Next generation proteins engineered with *protein* language models",
        "tagline": "We’re creating the next generation of peptides and enzymes using our proprietary pipeline, powered by protein language models.",
        "body": "Hey everyone – it’s [Abhi Rajendran](https://www.linkedin.com/in/abhirajen/), [Adam Wu](https://www.linkedin.com/in/akhwu/) and [Matteo Peluso](https://www.linkedin.com/in/matteo-peluso-872b85199/)\n\n**Tl;dr**: just look at the pictures ;)\n\n# **💞 The A(mino) Team**\n\n![uploaded image](/media/?type=post&id=82706&key=user_uploads/1754946/96f298df-f236-4401-91d5-2ce61024e644)\n\n👨🏾 **Abhi Rajendran** – From Imperial College London to the Mercedes F1 Team, Abhi builds AI tools in data-intensive environments. AminoAnalytica was inspired by his computational bio master’s project and was the top AI x Robotics venture from Imperial in 2024.\n\n👦🏻 **Adam Wu** – With experience in academic and industry wet labs, Adam is now building his own. He has a background in materials science, tissue engineering and biosensing as a Thermo Fisher Scholar from Imperial.\n\n👱🏼‍♂️ **Matteo Peluso** – Bioinformatics PhD from the University of Zurich. His skills in biology, machine learning, and software development tie up everything seamlessly.\n\n👨🏻‍🦱 **Dr. Stefano Angioletti-Uberti** – Senior lecturer at Imperial, specializing in modeling biological and soft matter systems. He ensures models are based on the latest scientific principles.\n\n# **❌ Problem: better proteins are needed to accelerate global innovation**\n\n* Industrial and pharma companies prefer to use enzymes and peptides over harsh chemicals as they are more specific and sustainable.\n* However, natural proteins often lack stability, efficiency, or specificity for their desired applications leading to poor performance\n* Improving these proteins has been a costly and inefficient 'trial-and-error' process, where biotech companies randomly mutate existing proteins, test them, and repeat until success.\n\n![uploaded image](/media/?type=post&id=82706&key=user_uploads/1754946/afb4dbcf-6cc7-43e1-915e-609278e798fa)\n\n# **✅ Solution: AminoAnalytica’s protein adaptation platform, powered by PLMs**\n\n* Like how ChatGPT understands human language, our **\"protein language models\" (PLMs)** understand biology and can optimize proteins for industrial and therapeutic use.\n* This allows us to perform in-silico protein property prediction, eliminating the need for thousands of lab tests.\n* We’re transforming the traditional ‘trial-and-error’ method into an ultra-high throughput and rational process.\n\n![uploaded image](/media/?type=post&id=82706&key=user_uploads/1754946/65fb8e1a-d749-4245-adca-a0abc1ad8529)\n\n# **🤝 Any industry working with proteins can benefit from our tech**\n\nCurrently, we’re working on:\n\n* **Aquaculture feed** → enzymes for maximizing fish feed nutritional efficiency\n* **Pharmaceuticals** → peptide drugs with improved stability and specificity\n* **Climate tech** → enzymes for eco-friendly carbon capture\n* **Consumer goods** → safer enzymes for everyday products\n\n![uploaded image](/media/?type=post&id=82706&key=user_uploads/1754946/30bf87a9-4ee8-49e6-a0ee-7f8dd85bf008)\n\n# **🐡 Get in touch with us!**\n\n* Upvote/share this post with your network and help spread the word!\n* If you (or anyone in your network) are as excited as we are about next generation industrial proteins and would like to learn more about what we’re doing, email us here - [founders@aminoanalytica.app](mailto:founders@aminoanalytica.app)\n* We’re also looking to expand **our advisory board** in the areas of aquaculture, fish testing, and feed manufacturing!\n\n![uploaded image](/media/?type=post&id=82706&key=user_uploads/1754946/908a3520-d234-4338-ad05-154aa3515672)\n\n",
        "url": "https://www.ycombinator.com/launches/LVy-aminoanalytica-next-generation-proteins-engineered-with-protein-language-models",
        "votes": 138,
        "created_at": "2024-08-04T00:01:55.931Z"
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    "all_locations": "Philadelphia, PA, USA",
    "long_description": "Finding new cures requires seeing what and where the abnormal molecules are in a diseased tissue, but current tools see less than 1% of those molecules. Biocartesian combines microscopy and new chemistries to see 50X more, offering unprecedented insights into disease biology and new therapies.",
    "one_liner": "Converting biology into digital molecular maps",
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    "batch": "Summer 2024",
    "status": "Active",
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    "year_founded": 2023,
    "city": "Philadelphia",
    "country": "US",
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        "full_name": "Ian Dardani",
        "title": "Founder/CEO",
        "founder_bio": "Co-founder of Biocartesian. Microscopy + molecular tools + engineering. Previously Bioscience Enterprise at Cambridge, Bioengineering PhD at UPenn.",
        "is_active": true,
        "linkedin_url": "https://linkedin.com/in/ian-dardani",
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      {
        "user_id": 1975436,
        "full_name": "Jess Li",
        "title": "Founder",
        "founder_bio": "Co-founder of Biocartesian. Genetics + epigenetics, next-gen sequencing. Previously PhD at UPenn, BD at imvaria.",
        "is_active": true,
        "linkedin_url": "https://www.linkedin.com/in/jessxli/",
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      {
        "id": 83575,
        "title": "Biocartesian - Converting biology into digital molecular maps",
        "tagline": "We use chemistry and microscopy to help scientists discover new drugs.",
        "body": "**Tl;dr**: Finding new cures requires knowing **what** and **where** the abnormal molecules are in a diseased tissue, but current tools see less than 1% of those molecules. [Biocartesian](https://www.biocartesian.com/) combines microscopy and new chemistries to see a comprehensive picture, offering unprecedented insights into disease biology and new therapeutic approaches.\n\n![uploaded image](/media/?type=post&id=83575&key=user_uploads/89898/ee18ecba-242d-4cb0-bb1b-d9ab6de69ddd)\n\n# **👩‍🔬 Team**\n\nWe’re [**Ian**](https://www.linkedin.com/in/ian-dardani) and [**Jess**](https://www.linkedin.com/in/jessxli/), two former UPenn PhDs on a mission to see every molecule in biological specimens. We’ve spent years advancing and troubleshooting the latest tools in biology, from DNA sequencing to microscopy, but even with these efforts, these tools revealed only a fraction of the underlying biology. We dreamed of a way for scientists to see everything (and fast) so they could reduce their guesswork and focus on the most promising therapeutic approaches.\n\n# ❌ **Problem**\n\nMost diseases remain a mystery because existing methods can see less than 1% of the molecules within a biological specimen. These methods can also take months for scientists to set up and often fail, wasting thousands of dollars per specimen and millions in failed drug programs.\n\n# 🔬 **Our approach**\n\nWe’re combining new chemistries and microscopy to see a full map of the molecules in biological specimens. Imagine if we could see into the \\~500 million existing tumor specimens to decode these cancers.\n\nTo use our technology, scientists simply ship their biological specimens to our laboratory, where we automate their conversion into digital molecular maps – saving them months of tedious data collection and troubleshooting.\n\n![uploaded image](/media/?type=post&id=83575&key=user_uploads/1116949/7deca4d9-cf29-45b4-852d-1fc471672b75)\n\nOur solution:\n\n* Enables scientists in any disease area to 50X their data collection\n* Saves scientists months of time\n* Lowers the cost of biological measurements\n* Expands access to bespoke assays developed by any scientist by integrating with our platform\n* Meets the growing demand for biological data as AI-led analysis supersedes the bottleneck of human-led analysis\n* Turns biology from 99% invisible to an interpretable problem\n\n# **🙏 Asks**\n\nIf you’re excited about this and would like to learn more, email us at:\n\n[**interested@biocartesian.com**](mailto:interested@biocartesian.com)\n\nor reach us at <https://www.biocartesian.com>",
        "url": "https://www.ycombinator.com/launches/Ljz-biocartesian-converting-biology-into-digital-molecular-maps",
        "votes": 265,
        "created_at": "2024-08-29T15:17:26.070Z"
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