🎙️ Join our webinar co-hosted with Accenture: New technologies to accelerate ADC design! Antibody-drug conjugates (ADCs) are transforming cancer therapy, with 15 approved drugs on the market — but over 100 discontinued programs highlight the complexity of ADC design. How can we overcome these challenges to accelerate development? 🗓️ When: December 12, 2024 - 3pm (GMT) 🎙️ Speakers: Eleni Tokali (Host) Daniel Veres MD PhD (Co-founder & CSO, Turbine) Hassan Naseri (Scientific & Next Gen. Computing Lead, Accenture) 💡 Topics: 1️⃣ Overview of the ADC market and challenges of ADC design 2️⃣ How can simulations help in understanding payload response and matching them to the right patients? 3️⃣ How can AI-driven tools help in designing cleavable linkers for ADCs? Don’t miss this opportunity to explore the future of ADCs! https://lnkd.in/d_ifg_Kb
Turbine
Biotechnology Research
Budapest, Budapest 5 758 followers
We are building the world’s leading predictive simulation of patient biology.
Rólunk
Truly meaningful medicine comes from breakthroughsin deeply understanding patient biology. We are building the world’s leading predictive simulation of patient biology. We will empower the biopharma industry by informing the right experiments that identify and validate disease driving hidden effects.
- Weboldal
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http://turbine.ai/
Külső hivatkozás a következőhöz: Turbine
- Ágazat
- Biotechnology Research
- Vállalat mérete
- 51–200 munkavállaló
- Központ
- Budapest, Budapest
- Típus
- Privately Held
- Alapítva
- 2016
- Szakterületek
Helyek
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Elsődleges
Szigony u. 26-32.
Budapest, Budapest 1083, HU
Alkalmazottak a Turbine
Frissítések
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Honored to share that Turbine has been selected as a finalist for MSD's Innovation Award of the Citeline Scrip Awards 2024. Congratulations to Generate:Biomedicines for winning the category! Being recognized alongside such groundbreaking innovations is truly inspiring. This acknowledgment underscores the transformative potential of our Simulated Cell™ platform, and we’re proud to contribute to advancing new frontiers in R&D. https://lnkd.in/eaAKmrWF
Scrip Awards 2024 | Citeline
citeline.com
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We are thrilled and honored to be among the nominees for the #FutureUnicornAward! Huge thanks to the organizers and the incredible network behind this initiative. Let’s shape the future of European innovation together! 🚀✨
👀 𝗨𝗡𝗩𝗘𝗜𝗟𝗘𝗗! We're excited to announce that the #FutureUnicornAward RETURNS in 2025 with 26 nominees, all selected by our network of 41 national digital associations across Europe. For the first time ever, the competition is split into TWO exciting categories: 🏅 Future Unicorn, spotlighting Europe's next tech giants: 🦄 Capra Robotics 🦄 Hevi AI🦄 iPRONICS 🦄 Klearcom 🦄Matteco 🦄 Pactum AI 🦄 Picus Security 🦄 Rekono d.o.o. 🦄 Scaleout 🦄 Turbine 🦄 walk15.app 🏅 Dual-use technologies, recognising innovative solutions for civilian and military purposes: 💎 Adarga 💎 Aerospacelab 💎BRANDEFENSE 💎 CREAPLUS 💎Esper Bionics 💎 HIMERA💎 𝗢𝗞𝗢 𝗞𝗔𝗠𝗘𝗥𝗔 💎Orqa FPV 💎 Phoenix Systems💎 Qamcom Group 💎 Quantum Systems 💎Roboneers💎 SensusQ 💎 Swarmer 💎 UADAMAGE Who will prevail? The winners will be crowned at #MoD2025. Stay tuned.
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🧠 Why does a tech-bio team choose to cater a wide market instead of point solutions? 🧬 What impact does an integrated platform like this offer to biopharma companies? 🇭🇺 How do you build a global AI for bio success story from Hungary? Tune in for Philip Hemme of Flot.bio and our CEO Szabolcs Nagy discussing even more crunchy details with some sneak peek into their personal history. https://buff.ly/48MKakn
The Flot.bio Show - Europe’s Biotech Podcast
https://flot.bio
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Current single-cell foundational models, including scGPT, can underperform compared to simpler approaches in predicting cellular responses to perturbations, highlighting significant limitations in existing benchmark datasets: 🌲 Turbine's benchmarking showed scGPT lagging behind simpler approaches like averaging training samples and Random Forest. 🐾 Models with biologically relevant features can significantly outperform scGPT. 🔻 Perturb-Seq datasets used for benchmarking are limited by low perturbation counts and lack of intra-perturbation variance. ⛓ Pseudo-bulked expression profiles outperform foundational models, suggesting little-to-no advantage in single-cell level modeling, especially in low-heterogeneity cell lines. Findings suggest revisiting benchmarking practices for more effective evaluation of post-perturbation gene expression prediction. Read more in the following preprint: https://lnkd.in/dKBGpYxr
computational systems biologist | principal bioinformatics scientist & research team lead at Turbine
Accurately predicting #cellular responses to #perturbations is crucial for understanding cell behavior in both healthy and diseased states. Recently, several large language model (LLM)-based single-cell #foundational models have been proposed for this task. But how well are they performing? At Turbine, we conducted #benchmarks on one of these models, scGPT, and uncovered some surprising results - see our new preprint: https://lnkd.in/dmHKbYQj Even simple models, like averaging training samples, outperformed scGPT. A straightforward machine learning model, Random Forest, incorporating biologically meaningful features, outperformed it by a large margin. We also discovered that current Perturb-Seq benchmark datasets generally contain a low number of perturbations and lack intra-perturbation variance, limiting their usefulness for robust benchmarking. Additionally, models using pseudo-bulked expression profiles outperformed foundation models, suggesting that single-cell level modeling may offer little advantage, especially in low-heterogeneity cell lines. Our findings reveal important limitations in current benchmarking practices and offer new insights for more effective evaluation of post-perturbation gene expression prediction models. Thanks to the coauthors, Kristóf Szalay and especially Gerold Csendes who led these efforts.
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"Hungary & #CentralEasternEurope is getting pretty good at nurturing tech startups. But any #DeepTech founder grappling with commercializing scientific breakthroughs faces too many barriers." Click to read more from our CEO Szabolcs Nagy!
Mulling over the first years after we spun-out of Semmelweis University in Hungary to teach AI to simulate biology @ Turbine, the lesson is clear. Hungary & #CentralEasternEurope is getting pretty good at nurturing tech startups. But any #DeepTech founder grappling with commercializing scientific breakthroughs faces too many barriers. Lack of mentors & role models. Lack of VCs that could evaluate their idea & fund its development. Lack of market understanding. With engineering and R&D achievements from the region that can and do rival any other market, some break through. But there must be more we can do to help them. Shared more about the key challenges & opportunities with Forbes Hungary (I'm helpfully linking it in Hungarian for those of you speaking this truly global language, but attached the ENG version too). Appreciate all of you collaborating on this with me: Csongor Biás Gyorgy Simo Györkő Zoltán Startup Hungary Daniel Veres MD PhD Kristóf Szalay Milán Golovics Gergő Zsiborás https://lnkd.in/dTgGgYUZ
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Our dearest Anna Török-Böröcz has just secured her place among the top 🇭🇺 HR leaders of year 2024! 🎊
🏆 "Az év HR-vezetője 2024" verseny kisvállalati kategóriájának győztesei: 1. helyezett: Boglarka Szentpetery, Danone Magyarország 2. helyezett: Judit Kmosko, ICF Tech Hungary 3. helyezett: Anna Török-Böröcz, Turbine Gratulálunk! 🎉
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As elegant as ADC-based therapies promise to be for oncology, as hard it is to deliver them. Our obstacles range from the very depth of biological understanding to drug design. Turbine's simulations help in: 🧬 Identifying drivers of response for payloads to guide rational patient selection 🧪 Finding the right payloads for disease-subtypes to address ADC-resistance in the clinic Our team is visiting World ADC Summit in San Diego, presenting a poster during today's scientific session. Please see our poster by clicking the link below and feel free to reach out through [email protected]! https://buff.ly/3UFoyR3
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It's not the first time we talk about the biases in training data that lead AI disease models astray. In this podcast episode we discuss the methodology we use to accurately assess computational model performance. We also share insights from our big pharma collaboration on how we use public, internal, and partner datasets to create patient avatars for simulations. Tune in to listen or visit benchmark.turbine.ai to learn more about the EFFECT Benchmark Suite! Let's work on finding ways to make more sense of ground truth data for better models of disease biology!
Discover Turbine’s way to build avatars true to patient biology
fiercebiotech.com
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We believe that RNA sequencing (RNAseq) is the best data source currently to computationally model cell behavior. Our CTO, Kristóf Szalay explores this topic in his latest blog post. 💡 Key takeaways: 1️⃣ RNAseq is cost-effective and scalable, making it ideal for large datasets with multiple perturbations. 2️⃣ Baseline RNAseq data correlates well with proteomics. 3️⃣ Basic machine learning models achieve comparable performance when predicting post-perturbation cell viability using either RNAseq or proteomics features. 4️⃣ With the right approach, downstream gene expression reveals crucial insights about upstream signaling pathways. Dive into the details by clicking the link below!
In defense of RNASeq
turbineai.substack.com