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Recursion Announces the Release of OpenPhenom-S/16 in Google Cloud’s Model Garden

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Recursion (NASDAQ: RXRX) has released OpenPhenom-S/16, a publicly available foundation model in Google Cloud's Vertex AI Model Garden. The model, trained on over three million microscopy images from public datasets, sets a new performance standard for microscopy data analysis, outperforming traditional methods like CellProfiler. The model enables automated classification of cellular structures and pattern detection without requiring additional tuning. Alongside the model, Recursion is releasing the RxRx3-core dataset, which includes labeled images of 735 genetic knockouts and 1,674 small-molecule perturbations, designed to advance research in drug mechanism mapping.

Recursion (NASDAQ: RXRX) ha lanciato OpenPhenom-S/16, un modello di base disponibile pubblicamente nel Google Cloud's Vertex AI Model Garden. Il modello, addestrato su oltre tre milioni di immagini microscopiche provenienti da dataset pubblici, stabilisce un nuovo standard di prestazioni per l'analisi dei dati microscopici, superando i metodi tradizionali come CellProfiler. Il modello consente la classificazione automatica delle strutture cellulari e il rilevamento dei pattern senza richiedere ulteriori tarature. Insieme al modello, Recursion sta rilasciando il dataset RxRx3-core, che include immagini etichettate di 735 knockout genetici e 1.674 perturbazioni di piccole molecole, progettato per avanzare la ricerca nella mappatura dei meccanismi dei farmaci.

Recursion (NASDAQ: RXRX) ha lanzado OpenPhenom-S/16, un modelo de base disponible públicamente en el Google Cloud's Vertex AI Model Garden. El modelo, entrenado con más de tres millones de imágenes de microscopía de conjuntos de datos públicos, establece un nuevo estándar de rendimiento para el análisis de datos de microscopía, superando métodos tradicionales como CellProfiler. El modelo permite la clasificación automática de estructuras celulares y la detección de patrones sin necesidad de ajustes adicionales. Junto con el modelo, Recursion está lanzando el conjunto de datos RxRx3-core, que incluye imágenes etiquetadas de 735 knockouts genéticos y 1,674 perturbaciones de pequeñas moléculas, diseñado para avanzar en la investigación sobre la mapeo de mecanismos de acción de los fármacos.

Recursion (NASDAQ: RXRX)은 Google Cloud의 Vertex AI Model Garden에서 공개적으로 사용할 수 있는 기본 모델 OpenPhenom-S/16을 출시했습니다. 이 모델은 공개 데이터 세트에서 수집한 300만 장 이상의 미세사진 이미지로 훈련되어, CellProfiler와 같은 전통적인 방법을 초월하여 미세사진 데이터 분석의 새로운 성능 기준을 설정합니다. 이 모델은 추가 조정 없이 세포 구조의 자동 분류와 패턴 감지를 가능하게 합니다. 모델과 함께 Recursion은 735개의 유전자 결실 및 1,674개의 소분자 변형의 레이블이 붙은 이미지를 포함하는 RxRx3-core 데이터 세트도 출시하여 약물 메커니즘 매핑 연구를 발전시키고자 합니다.

Recursion (NASDAQ: RXRX) a lancé OpenPhenom-S/16, un modèle de base accessible au public dans le Google Cloud's Vertex AI Model Garden. Ce modèle, entraîné sur plus de trois millions d'images de microscopie provenant de jeux de données publics, établit une nouvelle norme de performance pour l'analyse des données de microscopie, surpassant des méthodes traditionnelles comme CellProfiler. Le modèle permet la classification automatique des structures cellulaires et la détection de motifs sans nécessiter d'ajustements supplémentaires. Parallèlement au modèle, Recursion publie le jeu de données RxRx3-core, qui comprend des images étiquetées de 735 knockouts génétiques et 1.674 perturbations de petites molécules, conçu pour faire avancer la recherche sur la cartographie des mécanismes d'action des médicaments.

Recursion (NASDAQ: RXRX) hat OpenPhenom-S/16 veröffentlicht, ein öffentlich verfügbares Basis-Modell im Google Cloud's Vertex AI Model Garden. Das Modell, das auf über drei Millionen Mikroskopbildern aus öffentlichen Datensätzen trainiert wurde, setzt einen neuen Leistungsstandard für die Analyse von Mikroskopiedaten und übertrifft traditionelle Methoden wie CellProfiler. Das Modell ermöglicht die automatisierte Klassifizierung von Zellstrukturen und die Mustererkennung, ohne dass zusätzliche Anpassungen erforderlich sind. Zusammen mit dem Modell veröffentlicht Recursion das RxRx3-core-Datensatz, das gekennzeichnete Bilder von 735 genetischen Knockouts und 1.674 kleinen Molekülverschiebungen umfasst, das darauf ausgelegt ist, die Forschung zur Kartierung von Wirkmechanismen von Arzneimitteln voranzutreiben.

Positive
  • Release of new AI model that outperforms existing industry standards
  • Partnership with Google Cloud enhances accessibility and scalability
  • Model can process large-scale data more efficiently than traditional methods
  • Potential to accelerate drug discovery process through improved microscopy analysis
Negative
  • Model to non-commercial research use only

Insights

<p>The release of OpenPhenom-S/16 represents a significant technological advancement in drug discovery and microscopy analysis. This foundation model, trained on over <b>3 million microscopy images</b>, demonstrates superior performance over traditional methods like CellProfiler, particularly in identifying biological relationships from the StringDB database.</p><p>The integration with Google Cloud's Vertex AI Model Garden significantly enhances accessibility and scalability for life science researchers. This democratization of advanced AI tools could accelerate drug discovery processes and reduce operational costs for research institutions. However, the non-commercial limitation means direct revenue impact will be minimal, as Recursion maintains separate proprietary models for commercial applications.</p>

OpenPhenom is a non-commercial, publicly available foundation model built on microscopy data that has set the new "gold standard" outperforming CellProfiler

SALT LAKE CITY, Nov. 12, 2024 (GLOBE NEWSWIRE) -- Recursion (NASDAQ: RXRX), a leading clinical stage TechBio company decoding biology to industrialize drug discovery, announced today the release of OpenPhenom-S/16, a publicly available foundation model in Google Cloud’s Vertex AI Model Garden. This will enable Life Science companies to use OpenPhenom-S/16 on Google Cloud when building apps that require microscopy data to assess the effectiveness of drug treatments, analyze cultures, study tissues and ultimately accelerate drug discovery and for other uses.

“We are thrilled to announce that Recursion is setting a new gold standard for the industry with the release of OpenPhenom-S/16, a foundation model for microscopy data trained using masked-autoencoder-based self-supervised learning on more than three million microscopy images from publicly accessible datasets (RxRx3 and JUMP-CP),” said Ben Mabey, chief technology officer at Recursion.

Large-scale cell microscopy assays have become instrumental in unveiling novel biological processes, potential drug candidates, and targets. Traditionally, laboratories have relied on legacy image segmentation and feature extraction software packages that need to be tuned for each new assay and are often brittle to minor changes in assay conditions. With the increasing scale and complexity of private and public datasets, such as RxRx3 and JUMP-CP, these existing software packages and associated downstream analysis methods struggle to handle the sheer volume of data effectively.

OpenPhenom-S/16 will allow non-commercial researchers to potentially replace their existing workflows with this off-the-shelf model that outperforms traditional microscopy analysis pipelines without requiring any additional tuning or training. For example, with OpenPhenom-S/16, Recursion presents an unprecedented improvement in recalling known biological relationships from the StringDB database in the public JUMP-CP cpg0016 dataset.

Figure 1 demonstrates the improvement in recalling known biological relationships (PLoS Comp Bio 2024) from the StringDB database in the public JUMP-C

Figure 1 demonstrates the improvement in recalling known biological relationships (PLoS Comp Bio 2024) from the StringDB database in the public JUMP-CP dataset when using OpenPhenom-S/16 embeddings compared to the gold standard approach with CellProfiler.

"We’re pleased Recursion is bringing OpenPhenom-S/16 to the life science community through Google Cloud's Vertex AI Model Garden,” said Shweta Maniar, global director of Life Science Strategy & Solutions, Google Cloud. “This powerful foundation model, combined with the scalability and accessibility of our Vertex AI platform, has the potential to accelerate microscopy analysis by automating classification of cellular structures, detecting patterns and anomalies, and extracting valuable insights from complex microscopy data. By democratizing access to this cutting-edge technology, Recursion will empower researchers around the globe to make new discoveries and advance the field of biomedicine."

As a leader in this space, Recursion also has models for commercial use for its own pipeline and partnership programs. Recursion has featured the performance of two generations of proprietary models trained on Recursion’s internal microscopy, Phenom-1 (CVPR 2024) and Phenom-2 (NeurIPS FM4S 2024).

To accompany OpenPhenom-S/16, Recursion is releasing the RxRx3-core dataset, a challenge dataset in phenomics optimized for the research community. RxRx3-core includes labeled images of 735 genetic knockouts and 1,674 small-molecule perturbations drawn from the RxRx3 dataset, image embeddings computed with OpenPhenom-S/16, and associations between the included small molecules and genes. “Mapping the mechanisms by which drugs exert their actions is an important challenge in advancing the use of high-dimensional biological data like phenomics. We are excited to release the first dataset of this scale probing concentration-response along with a benchmark and model to enable the research community to rapidly advance this space,” commented Imran Haque, Ph.D., SVP of AI and Digital Sciences at Recursion.

To access OpenPhenom-S/16 on Google Cloud, through Hugging Face, please visit RxRx.ai/phenom. For more details on RxRx3-core, find the dataset at https://rxrx.ai/rxrx3-core. Please sign up at RxRx.ai to receive updates on all data and model releases from Recursion.

About Recursion

Recursion (NASDAQ: RXRX) is a clinical stage TechBio company leading the space by decoding biology to industrialize drug discovery. Enabling its mission is the Recursion OS, a platform built across diverse technologies that continuously expands one of the world’s largest proprietary biological and chemical datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale — up to millions of wet lab experiments weekly — and massive computational scale — owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology and chemistry to advance the future of medicine.

Recursion is headquartered in Salt Lake City, where it is a founding member of BioHive, the Utah life sciences industry collective. Recursion also has offices in Toronto, Montréal, London, and the San Francisco Bay Area. Learn more at www.Recursion.com, or connect on X (formerly Twitter) and LinkedIn.

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Forward-Looking Statements

This document contains information that includes or is based upon "forward-looking statements" within the meaning of the Securities Litigation Reform Act of 1995, including, without limitation, those regarding the performance of the OpenPhenom model and its impact on the pharmaceutical industry, other life sciences companies, and drug discovery and other uses; and all other statements that are not historical facts. Forward-looking statements may or may not include identifying words such as “plan,” “will,” “expect,” “anticipate,” “intend,” “believe,” “potential,” “continue,” and similar terms. These statements are subject to known or unknown risks and uncertainties that could cause actual results to differ materially from those expressed or implied in such statements, including but not limited to: challenges inherent in pharmaceutical research and development, including the timing and results of preclinical and clinical programs, where the risk of failure is high and failure can occur at any stage prior to or after regulatory approval due to lack of sufficient efficacy, safety considerations, or other factors; our ability to leverage and enhance our drug discovery platform; our ability to obtain financing for development activities and other corporate purposes; the success of our collaboration activities; our ability to obtain regulatory approval of, and ultimately commercialize, drug candidates; our ability to obtain, maintain, and enforce intellectual property protections; cyberattacks or other disruptions to our technology systems; our ability to attract, motivate, and retain key employees and manage our growth; inflation and other macroeconomic issues; and other risks and uncertainties such as those described under the heading “Risk Factors” in our filings with the U.S. Securities and Exchange Commission, including our Annual Report on Form 10-K and Quarterly Report on Form 10-Q. All forward-looking statements are based on management’s current estimates, projections, and assumptions, and Recursion undertakes no obligation to correct or update any such statements, whether as a result of new information, future developments, or otherwise, except to the extent required by applicable law.

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/4ab2ee8f-0ec0-4917-90f7-6aa9f09e1feb


FAQ

What is OpenPhenom-S/16 and when did Recursion (RXRX) release it?

OpenPhenom-S/16 is a foundation model for microscopy data analysis released by Recursion in November 2024 through Google Cloud's Vertex AI Model Garden.

How many microscopy images was OpenPhenom-S/16 trained on?

OpenPhenom-S/16 was trained on more than three million microscopy images from publicly accessible datasets (RxRx3 and JUMP-CP).

What advantages does OpenPhenom-S/16 offer over traditional microscopy analysis methods?

OpenPhenom-S/16 outperforms traditional microscopy analysis pipelines without requiring additional tuning or training, and can better handle large volumes of data compared to legacy software packages.

How can researchers access Recursion's (RXRX) OpenPhenom-S/16 model?

Researchers can access OpenPhenom-S/16 through Google Cloud's Vertex AI Model Garden and Hugging Face by visiting RxRx.ai/phenom.

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