Wellness & Lifestyle

Recursion is a clinical-stage TechBio company dedicated to decoding biology through AI to radically improve lives. Founded over a decade ago, Recursion utilizes its proprietary Recursion OS, an AI-native, end-to-end drug discovery and development platform. This platform integrates biology, chemistry, and clinical development into a unified intelligence system, powered by multimodal data, purpose-built AI models, and bilingual teams. Recursion aims to reduce the massive 90% failure rate of traditional drug discovery by using AI to understand cellular disruptions driving disease. The company has yielded an advanced pipeline of potential first-in-class and best-in-class treatments for conditions with high unmet need, including aggressive cancers and rare diseases, demonstrating significant improvements in speed, efficiency, and reduced costs from hit identification to IND-enabling studies.

DeepVariant is an advanced analysis pipeline developed by Google that leverages deep neural networks to identify genetic variants from next-generation DNA sequencing data. It functions by taking aligned reads, generating pileup image tensors, classifying each tensor using a convolutional neural network, and then reporting the results in standard VCF or gVCF files. The tool is highly accurate, having won multiple PrecisionFDA Truth Challenges, and maintains this accuracy across diverse sequencing technologies, prep methods, and species. DeepVariant is flexible, supporting PCR-positive samples and low-quality sequencing runs, and can be adapted for non-human species. It is also cost-effective and offers various usage options, including Docker, binaries, and support for hardware accelerators like GPUs and TPUs. DeepTrio, a related tool, extends DeepVariant's capabilities for trio variant calling.

Leash Bio is revolutionizing drug design by building a massive, proprietary dataset of protein-molecule interactions. The platform screens millions of compounds against thousands of proteins, generating over 30 billion data points. This extensive dataset is ideal for training advanced machine learning models, enabling faster and more effective drug discovery. Leash Bio employs a dynamic, cyclical engine that continuously harnesses data, iterates machine learning, and refines its approach, with each cycle taking only a few months. Their innovative software designs and refines novel chemical matter, leading to molecules with desired activities. The company is developing internal oncology programs and partnering with biopharma companies to explore new molecule opportunities.

Aigensei is an Enterprise Agentic Workflow Platform designed to automate and execute business playbooks end-to-end, particularly for regulated industries. Unlike traditional AI that answers or retrieves information, Aigensei operates by running processes autonomously, eliminating manual handoffs and queues. Users define their existing playbooks, connect their CRM, knowledge bases, and other live data sources via Model Context Protocol (MCP), and then scale execution without limits. The platform ensures controlled execution, with every decision logged, auditable, and explainable. It supports various applications including sales qualification, customer service resolution, onboarding, operations, HR, and finance, providing an enterprise-grade solution built for clarity, compliance, and scale.

fairchem is a comprehensive, open-source library developed by the FAIR Chemistry team, offering machine learning methods specifically tailored for chemistry. It serves as a centralized repository for data, models, demos, and applications in materials science and quantum chemistry. The library supports various tasks, including relaxing adsorbates on catalytic surfaces, optimizing inorganic crystals, running molecular dynamics simulations, and calculating spin gaps. It features pretrained models like UMA, which can be used with the ASE FAIRChemCalculator for a wide range of applications. fairchem also supports multi-GPU inference and LAMMPs integration for large-scale simulations, making it suitable for complex computational chemistry problems.

RoseTTAFold is a deep learning model and script package designed for the accurate prediction of protein structures and interactions. This tool is an official implementation of the RoseTTAFold architecture, which employs a 3-track neural network to achieve its predictions. It is primarily intended for research in computational biology, enabling scientists to model complex protein structures and protein-protein interactions (PPIs). The package includes scripts for installation, dependency management, and running predictions for both monomer structures and complex modeling. It also features a faster 2-track version for PPI screening, making it a versatile tool for advanced biological research.

DrugCards offers AI-powered solutions for comprehensive literature screening and pharmacovigilance, streamlining drug safety routines for pharmaceutical companies, Contract Research Organizations (CROs), and freelancers. The platform automates literature monitoring, regulatory intelligence, and adverse event management, significantly reducing the time spent on manual tasks. It supports over 100 languages and covers medical journals from 121+ countries, continuously monitoring more than 2200 local journals. DrugCards aims to improve compliance, enhance traceability, and provide accurate, complete, and holistic data. It is designed to be scalable, multi-language, multi-region, and cost-effective, offering up to 60% time savings compared to human-only approaches.

Profluent Bio is at the forefront of authoring new biology, leveraging advanced AI to design and engineer proteins. The platform aims to revolutionize fields like medicine and agriculture by creating novel biological solutions. A key innovation is OpenCRISPR, the world's first AI-designed gene editor, showcasing the company's capability in authorship. Profluent's AI can design proteins from scratch or inspired by natural scaffolds, addressing complex challenges in protein design. The company collaborates with partners to drive innovation and applies its AI-authored proteins across various industries, from new therapeutics to industrial enzymes. Their expert team combines machine learning and biology to unlock these solutions.

Stratipath is an AI company dedicated to revolutionizing cancer treatment decisions and improving patient outcomes by assisting physicians in delivering optimal treatment to every patient. Stratipath’s pioneering solutions and AI-based precision diagnostic software platform transform tissue sample analysis, enabling breakthrough insights for enhanced and faster patient stratification across healthcare, clinical trials, and drug development. By expanding the reach of precision medicine, Stratipath aims to make this advanced healthcare approach accessible to a wider patient population. Founded as a spin-out of Karolinska Institutet in Stockholm, Sweden, Stratipath is built upon years of groundbreaking research and development. Stratipath Breast, their first-in-class AI solution, provides prognostic risk profiling of invasive early-stage breast cancer, offering a faster and more cost-effective alternative to gene expression tests.

Lunit Oncology develops advanced medical AI software designed to transform cancer care through earlier detection and precision oncology. Their platform includes Lunit INSIGHT for cancer screening, offering AI-powered analysis for mammography (2D and 3D) and chest X-rays to improve detection rates and streamline workflows. For precision oncology, Lunit SCOPE provides AI-driven insights for tumor microenvironment analysis, IHC quantification, and genotype prediction, aiding in treatment decisions and drug development. The modular platform integrates seamlessly into existing clinical workflows, connecting multimodal data and interoperable solutions. Lunit's technology is built on diverse global datasets, ensuring scalability and driving precision care across various stages of cancer management, from screening to treatment and drug development.

Cradle is an advanced AI platform designed for protein engineering, enabling scientists to accelerate the discovery and optimization of protein candidates. The tool uses machine learning to generate novel protein sequences and predict their properties, significantly reducing the number of experiments needed. Users can upload their experimental data, which Cradle then analyzes to refine its models, leading to increasingly performant variants. It supports co-optimization of multiple properties like binding affinity, specificity, activity, and stability, across various protein types including antibodies, enzymes, vaccines, and peptides. Cradle ensures data privacy and security, with user data remaining proprietary and never used to train models for other organizations.

Health Prediction On Encrypted Data Using Fully Homomorphic Encryption is an innovative AI tool available on Hugging Face Spaces, designed to offer secure health predictions. It leverages fully homomorphic encryption (FHE) to analyze user-provided symptoms while keeping the data encrypted throughout the process. This ensures that sensitive health information remains private, addressing critical concerns in healthcare data security. Users can input at least five symptoms, encrypt them, and send them to the server for processing, receiving a disease diagnosis without compromising their privacy. This tool is particularly valuable for privacy-preserving machine learning (PPML) applications in the medical field, making advanced diagnostic capabilities accessible while maintaining data confidentiality.

awesome-deepbio is a curated, open-source list of deep learning applications specifically tailored for the field of computational biology. This GitHub repository serves as an invaluable resource for researchers, academics, and practitioners seeking to explore the intersection of deep learning and biological problems. It meticulously compiles research papers, often including links to their implementations, covering a wide array of topics from protein homology detection and contact map prediction to genetic variant annotation and drug discovery. The list is organized chronologically by publication date, making it easy to track the evolution and advancements in the field. It is freely available and constantly updated, providing a dynamic overview of cutting-edge deep learning techniques applied to biological data.

EquiBind is a cutting-edge, open-source geometric deep learning model designed for the rapid and accurate prediction of drug binding structures. It utilizes SE(3)-equivariant geometric deep learning to directly predict both the receptor binding location (blind docking) and the ligand’s bound pose and orientation. This approach significantly speeds up the process compared to traditional and other recent baseline methods. EquiBind is particularly valuable for accelerating drug discovery by providing insights into how small molecules interact with proteins. Users can input ligand and receptor files in various formats, set up the environment using Anaconda, and then run inference to obtain binding structure predictions, with results saved as .sdf files.

TrumpRx is a platform dedicated to delivering the lowest prescription prices in the world for Americans. It aims to rewrite the script on prescription drug costs by leveraging Most-Favored-Nation pricing, which guarantees substantial savings on essential medications. The website provides cost comparisons for common drugs like Gonal-F, Wegovy, Ozempic, and Zepbound, illustrating how prices are drastically reduced compared to previous US market rates and global references. TrumpRx emphasizes putting more money back into Americans' pockets and making healthcare more accessible by ensuring competitive pricing on medications.

SWARM Biotactics specializes in creating Biobots and autonomous cyborg swarms capable of entering, sensing, and reporting in environments where traditional technology cannot operate. Their system, SWARM OS, provides mission control, swarm autonomy, and sensor fusion, enabling persistent presence and real-time intelligence gathering. This technology is designed for critical applications in defense, security, police, and search & rescue, offering solutions for GPS-denied, cluttered, and high-risk terrains. SWARM Biotactics focuses on providing low-signature, always-on ground truth, reducing risk and protecting personnel and infrastructure.

Valo Health is a technology company revolutionizing drug discovery and development by integrating human and machine intelligence. Their approach combines real-world data, AI, advanced causal inference techniques, and predictive chemistry to create a powerful engine for accelerating life-changing cures. Valo harnesses AI to find patterns in large-scale human data, identify novel disease targets, and rapidly engineer novel small molecules through human causal biology and closed-loop chemistry. This deep integration across biology, chemistry, and engineering disciplines allows them to explore vast chemical spaces and advance promising lead series into candidates, ultimately aiming to reduce costs and failure rates in drug development.

Chemprop is an open-source repository that implements message passing neural networks for molecular property prediction. It is a powerful tool for researchers and data scientists in chemical informatics, offering capabilities for predicting various chemical properties. The tool has undergone a significant rewrite, with version 2.0.0 introducing enhanced efficiency and modularity. Chemprop has been successfully applied in drug discovery, including the identification of novel antibiotics like Halicin, and in ADMET prediction platforms. It provides extensive documentation, tutorial notebooks, and examples to facilitate its use in research and development.

OpenChem is a deep learning toolkit specifically designed for computational chemistry and drug design research, built with a PyTorch backend. Its primary goal is to simplify the application of deep learning models for researchers in these fields. Key features include a modular design with a unified API, allowing for easy combination of different modules, and the ability to build new models using only a configuration file. The toolkit supports fast training with multi-GPU capabilities and provides utilities for data preprocessing. It also integrates with Tensorboard for visualization. OpenChem handles various tasks such as classification, regression, multi-task learning, and generative models, supporting data types like character sequences (SMILES, amino acids) and molecular graphs, with automatic conversion of SMILES to graphs.

Asher Orion Group specializes in activating medical AI to improve healthcare outcomes. They offer consulting services for both healthcare organizations and AI vendors, guiding them through the complexities of medical AI strategy and implementation. For healthcare organizations, they help determine the right AI strategy and optimize its execution to deliver clinical value. For AI vendors, they assist in focusing on the right solutions and accelerating their market entry. Their services include expertise in Imaging AI, Enabling Technology, and Innovation & Research, with a focus on areas like product market data, AI validation, deployment, and surveillance. They have a strong track record, as evidenced by testimonials from clients like The Health Value Alliance and The Alliance for Innovation in Integrated Healthcare.

CaryHealth provides an interconnected digital health experience by integrating intelligence into its digital pharmacy services. The platform offers scalable AI solutions and integrated services designed to strengthen patient relationships, improve fill and adherence rates, close care gaps, and reduce administrative burden. Key offerings include Rx Fulfillment & Hub Services, Care Gap Closure, Clinical Reference & Decision Support, Digital Therapeutics, and Direct To Patient services. CaryHealth's proprietary AI model drives smarter care and stronger outcomes, leveraging a comprehensive digital ecosystem for health organizations. Its products like CaryConnect, OnLabel, OneDash, CaryRx, and Clair are built to speed up care and streamline operations for various healthcare stakeholders.

1910 Genetics is an AI-native biotechnology company focused on drug discovery and development. Their ITO™ platform leverages a multimodal, modality-agnostic AI infrastructure that integrates wet lab, computational, and proxy data. This comprehensive approach enables the discovery of both small and large molecule therapeutics, aiming to reliably drug previously undruggable targets. The company emphasizes challenging the status quo through a diverse team of scientists and engineers, pushing the boundaries of innovation in AI-driven drug discovery. They offer co-engineering opportunities, allowing collaboration at the data, AI model, and compute levels to develop bespoke discovery modules.

10x Science provides AI-native software specifically designed for scientists working with protein therapeutics. The platform significantly upgrades peptide mapping, offering processing speeds that are 10 times faster than traditional methods. It is engineered to uncover insights that existing tools might overlook, enhancing the depth and accuracy of protein characterization. A key differentiator is its ability to eliminate the need for file conversions, streamlining the workflow and reducing friction for researchers. This focus on speed, enhanced discovery, and user-friendly integration makes 10x Science a powerful tool for advanced scientific research.

Ritivel is an AI-native regulatory platform designed for the life sciences industry, including Pharma, Biotech, Medtech, and CROs. It automates the drafting of critical regulatory submissions like Clinical Study Reports (CSRs) and CTD modules, significantly reducing the time from weeks to minutes. The platform ensures 100% reproducibility and offers word-level traceability, allowing users to instantly identify the source of every statement. Ritivel's AI is specifically trained on life sciences and regulatory content, ensuring accuracy and consistency in domain-specific terminology. A key differentiator is its commitment to data security, offering 100% local deployment with no cloud storage, ensuring sensitive data remains within the user's infrastructure and is never used for model training.