Polaris - Benchmarks for methods that matter’s Post

🚀 Today, we’re excited to launch Polaris! 🚀 Polaris is a platform where the ML community working on drug discovery problems can easily share and access datasets and benchmarks. Get started with just a few lines of code: https://polarishub.io/ Benchmarking in computational drug discovery is already complicated because we don’t have standardized datasets, clear guidelines, or tools for method evaluation and comparison. It also doesn’t help that datasets and benchmarks are also scattered throughout the literature. We believe the first step towards improving the state of benchmarking is by providing a single source of truth for the community to easily access and compare methods. That’s what Polaris aims to be. ⭐ Whether you’re working with small molecules, phenomics, proteins, or something else, we’re here for you. We aim to support all file types and sizes with simple, fast data access. We’ve also put together a steering committee of experts across industry and academia (AstraZeneca, Relay Therapeutics, Pfizer, Merck, Nimbus Therapeutics, Blueprint Medicines, Johnson & Johnson, Valence Labs/ Recursion, and Mila - Quebec Artificial Intelligence Institute) to propose guidelines around dataset curation, method evaluation, and comparison - starting with a focus on small molecules. This is just the beginning of more industry-academia collaborations. Stay tuned!

🚀 Today, we’re excited to launch Polaris! 🚀 Polaris is a platform where the ML community working on drug discovery problems can easily share and access datasets and benchmarks. Get started with just a few lines of code: https://polarishub.io/ Benchmarking in computational drug discovery is already complicated because we don’t have standardized datasets, clear guidelines, or tools for method evaluation and comparison. It also doesn’t help that datasets and benchmarks are also scattered throughout the literature. We believe the first step towards improving the state of benchmarking is by providing a single source of truth for the community to easily access and compare methods. That’s what Polaris aims to be. ⭐ Whether you’re working with small molecules, phenomics, proteins, or something else, we’re here for you. We aim to support all file types and sizes with simple, fast data access. We’ve also put together a steering committee of experts across industry and academia (AstraZeneca, Relay Therapeutics, Pfizer, Merck, Nimbus Therapeutics, Blueprint Medicines, Johnson & Johnson, Valence Labs/ Recursion, and Mila - Quebec Artificial Intelligence Institute) to propose guidelines around dataset curation, method evaluation, and comparison - starting with a focus on small molecules. This is just the beginning of more industry-academia collaborations. Stay tuned!

🚀 Today, we’re excited to launch Polaris! 🚀 Polaris is a platform where the ML community working on drug discovery problems can easily share and access datasets and benchmarks. Get started with just a few lines of code: https://polarishub.io/ Benchmarking in computational drug discovery is already complicated because we don’t have standardized datasets, clear guidelines, or tools for method evaluation and comparison. It also doesn’t help that datasets and benchmarks are also scattered throughout the literature. We believe the first step towards improving the state of benchmarking is by providing a single source of truth for the community to easily access and compare methods. That’s what Polaris aims to be. ⭐ Whether you’re working with small molecules, phenomics, proteins, or something else, we’re here for you. We aim to support all file types and sizes with simple, fast data access. We’ve also put together a steering committee of experts across industry and academia (AstraZeneca, Relay Therapeutics, Pfizer, Merck, Nimbus Therapeutics, Blueprint Medicines, Johnson & Johnson, Valence Labs/ Recursion, and Mila - Quebec Artificial Intelligence Institute) to propose guidelines around dataset curation, method evaluation, and comparison - starting with a focus on small molecules. This is just the beginning of more industry-academia collaborations. Stay tuned!

Today, we are thrilled to announce that we have entered into a definitive agreement with Exscientia (Nasdaq: EXAI). This proposed combination of Recursion’s high throughput target biology and Exscientia’s generative AI drug design and chemistry automation capabilities will help us deliver better treatments to patients faster and at a lower cost. We’re combining strengths and realizing synergies across several key areas: ◾ Platform: The proposed combination enables us to assemble a platform that leverages technology to enable a full-stack discovery solution spanning patient-centric target discovery, hit discovery, lead optimization, automated chemical synthesis, predictive ADMET and translation, biomarker selection, clinical development, and more. ◾ Pipeline: Combining our portfolios will allow us to expand into new areas of oncology and immunology and result in a diverse portfolio of clinical or near-clinical programs with approximately 10 clinical readouts in the next 18 months. Most of these programs, if successful, could have peak sales opportunities in excess of $1 billion. ◾ Partnerships: Together, we will also advance transformative therapeutic discovery collaborations with some of the most prominent biopharma companies in the world, including Roche-Genentech, Sanofi, Bayer, and Merck KGaA, with the potential for approximately $200 million in milestone payments over the next 24 months, and over $20 billion overall before potential royalties over the course of the partnership. We couldn’t be more excited to bring together these two incredible teams to accelerate our ability to deliver first-in-class and best-in-class treatments to patients who need them most. Learn more: https://lnkd.in/eZ9U8vwN #ai #pharma #techbio #agreement #portfolio #platform #tech #biology #drugdiscovery

Today, we are thrilled to announce that we have entered into a definitive agreement with Exscientia (Nasdaq: EXAI). This proposed combination of Recursion’s high throughput target biology and Exscientia’s generative AI drug design and chemistry automation capabilities will help us deliver better treatments to patients faster and at a lower cost. We’re combining strengths and realizing synergies across several key areas: ◾ Platform: The proposed combination enables us to assemble a platform that leverages technology to enable a full-stack discovery solution spanning patient-centric target discovery, hit discovery, lead optimization, automated chemical synthesis, predictive ADMET and translation, biomarker selection, clinical development, and more. ◾ Pipeline: Combining our portfolios will allow us to expand into new areas of oncology and immunology and result in a diverse portfolio of clinical or near-clinical programs with approximately 10 clinical readouts in the next 18 months. Most of these programs, if successful, could have peak sales opportunities in excess of $1 billion. ◾ Partnerships: Together, we will also advance transformative therapeutic discovery collaborations with some of the most prominent biopharma companies in the world, including Roche-Genentech, Sanofi, Bayer, and Merck KGaA, with the potential for approximately $200 million in milestone payments over the next 24 months, and over $20 billion overall before potential royalties over the course of the partnership. We couldn’t be more excited to bring together these two incredible teams to accelerate our ability to deliver first-in-class and best-in-class treatments to patients who need them most. Learn more: https://lnkd.in/eZ9U8vwN #ai #pharma #techbio #agreement #portfolio #platform #tech #biology #drugdiscovery

Today, we are thrilled to announce that we have entered into a definitive agreement with Exscientia (Nasdaq: EXAI). This proposed combination of Recursion’s high throughput target biology and Exscientia’s generative AI drug design and chemistry automation capabilities will help us deliver better treatments to patients faster and at a lower cost. We’re combining strengths and realizing synergies across several key areas: ◾ Platform: The proposed combination enables us to assemble a platform that leverages technology to enable a full-stack discovery solution spanning patient-centric target discovery, hit discovery, lead optimization, automated chemical synthesis, predictive ADMET and translation, biomarker selection, clinical development, and more. ◾ Pipeline: Combining our portfolios will allow us to expand into new areas of oncology and immunology and result in a diverse portfolio of clinical or near-clinical programs with approximately 10 clinical readouts in the next 18 months. Most of these programs, if successful, could have peak sales opportunities in excess of $1 billion. ◾ Partnerships: Together, we will also advance transformative therapeutic discovery collaborations with some of the most prominent biopharma companies in the world, including Roche-Genentech, Sanofi, Bayer, and Merck KGaA, with the potential for approximately $200 million in milestone payments over the next 24 months, and over $20 billion overall before potential royalties over the course of the partnership. We couldn’t be more excited to bring together these two incredible teams to accelerate our ability to deliver first-in-class and best-in-class treatments to patients who need them most. Learn more: https://lnkd.in/eZ9U8vwN #ai #pharma #techbio #agreement #portfolio #platform #tech #biology #drugdiscovery