Best AI tools for< Optimize Drug Candidates >

Iambic Therapeutics is a cutting-edge AI-driven drug discovery platform that tackles the most challenging design problems in drug discovery, addressing unmet patient need. Its physics-based AI algorithms drive a high-throughput experimental platform, converting new molecular designs to new biological insights each week. Iambic's platform optimizes target product profiles, exploring multiple profiles in parallel to ensure that molecules are designed to solve the right problems in disease biology. It also optimizes drug candidates, deeply exploring chemical space to reveal novel mechanisms of action and deliver diverse high-quality leads.

Atomwise is an AI-powered drug discovery company that uses machine learning to identify new small molecule medicines. The company's platform combines the power of convolutional neural networks with massive chemical libraries to discover new drug candidates. Atomwise has a portfolio of wholly owned and co-developed pipeline assets, and is backed by prominent investors.

Recursion is a techbio company that uses artificial intelligence to accelerate drug discovery. The company's platform combines hardware, software, and data to create a more efficient and effective drug discovery process. Recursion has a broad pipeline of drug candidates in development, and it has partnered with several leading pharmaceutical companies. The company is headquartered in Salt Lake City, Utah.

Variational AI is a company that uses generative AI to discover novel drug-like small molecules with optimized properties for defined targets. Their platform, Enki™, is the first commercially accessible foundation model for small molecules. It is designed to make generating novel molecule structures easy, with no data required. Users simply define their target product profile (TPP) and Enki does the rest. Enki is an ensemble of generative algorithms trained on decades worth of experimental data with proven results. The company was founded in September 2019 and is based in Vancouver, BC, Canada.

Allchemy is a resource-aware AI platform for drug discovery. It combines state-of-the-art computational synthesis with AI algorithms to predict molecular properties. Within minutes, Allchemy creates thousands of synthesizable lead candidates meeting user-defined profiles of drug-likeness, affinity towards specific proteins, toxicity, and a range of other physical-chemical measures. Allchemy encompasses the entire resource-to-drug design process and has been used in academic, corporate and classified environments worldwide to: Design synthesizable leads targeting specific proteins Evolve scaffolds similar to desired drugs Design “circular” drug syntheses from renewable materials Interface with and instruct automated synthesis platforms and optimize pilot-scale processes Operate “iterative synthesis” schemes Predict side reactions and create forensic “synthetic signatures” of hazardous/toxic molecules Design synthetic degradation and recovery cycles for various types of feedstocks and functional target molecules

HUAWEI Cloud Pangu is an AI tool designed for accelerating drug discovery by optimizing drug molecules. It offers features such as Molecule Search, Molecule Optimizer, and Pocket Molecule Design. Users can submit molecules for optimization and view historical optimization results. The tool is based on the MindSpore framework and has been visited over 300,000 times since August 23, 2021.

Kuano is an AI tool that focuses on redefining drug discovery using Quantum and AI technologies. The platform offers world-class scientific expertise in quantum physics, AI, and medicinal chemistry to revolutionize the drug design process. Kuano aims to leverage cutting-edge technologies to accelerate the discovery of new drugs and improve healthcare outcomes.

DrugCard is an AI-enabled Data Intelligence platform designed to streamline drug safety routines by providing continuous and regular, traceable, transparent, accurate, complete, and scalable solutions for pharmacovigilance processes. The platform supports over 100 languages, monitors 1000+ local journals, and saves up to 70% of time compared to manual approaches. DrugCard caters to CROs, MAHs, and freelancers, offering efficient local literature screening services to ensure compliance with regulatory requirements and enhance productivity.

Synthace is a software and expertise platform designed for Discovery Biology Teams to streamline and optimize their experiments in assay development, media optimization, and purification process development. The platform offers software solutions, training, and on-site support from specialists to help scientists conduct experiments more efficiently and effectively. By leveraging multifactorial methods and automation, Synthace aims to accelerate drug discovery processes and deliver faster, definitive results.

Lavo Life Sciences is an AI-accelerated crystal structure prediction application that helps in drug development by providing accurate predictions for small molecule drugs. The application utilizes AI technology to optimize solid-state formulations, reduce turnaround time, mitigate risks, and discover novel polymorphs, ultimately streamlining the pharmaceutical research and development process.

Intelligencia AI is a leading provider of AI-powered solutions for the pharmaceutical industry. Our suite of solutions helps de-risk and enhance clinical development and decision-making. We use a combination of data, AI, and machine learning to provide insights into the probability of success for drugs across multiple therapeutic areas. Our solutions are used by many of the top global pharmaceutical companies to improve their R&D productivity and make more informed decisions.

The Unlearn Platform is an AI-powered tool designed to streamline clinical trials by creating digital twins of patients using clinical trial data. It offers unparalleled precision in predicting clinical outcomes at future time points, ultimately minimizing trial failure, reducing costs, and accelerating approval processes. The platform enhances trial efficiency, insights, and impact, tailored to the specific needs of each study.

neurons.bio is an AI application that offers a unique collection of over 100 AI agents designed for drug development, medicine, and life science research. These agents perform specific tasks efficiently, retrieve data from various sources, and provide insights to accelerate research processes. The platform aims to revolutionize drug discovery and development by integrating cutting-edge LLM technology with domain-specific agents, reducing research costs and time to clinic.

Salt AI is a development engine tailored for life sciences organizations, aiming to accelerate advancements in the field by enabling faster adoption and utilization of AI technologies. The platform offers reliable and reproducible AI processes, optimized for speed and efficiency, and promotes transparency and collaboration within workflows. With a focus on supporting best-in-class life sciences research models, Salt AI empowers users to enhance their understanding of biological processes through flexible and performant AI solutions.

Dang.ai is an AI Tools Directory that provides a comprehensive list of AI tools and services. It offers a platform for users to discover and explore various AI-powered applications across different categories such as image design, writing, business, chat, audio, chatbot, art, productivity, video, TTS, marketing, code search, and more. Users can find tools for automating emails, marketing strategies, content optimization, video summarization, writing enhancement, anime art generation, web accessibility, survey platforms, sketch rendering, content generation, highlight finding, web accessibility, digital commerce insights, study tools, photo editing, drug development, media creation, logo design, and much more.

Qualtrics XM is a leading Experience Management Software that helps businesses optimize customer experiences, employee engagement, and market research. The platform leverages specialized AI to uncover insights from data, prioritize actions, and empower users to enhance customer and employee experience outcomes. Qualtrics XM offers solutions for Customer Experience, Employee Experience, Strategy & Research, and more, enabling organizations to drive growth and improve performance.

The Shopify App Store is a platform that offers a wide variety of applications to enhance and customize Shopify stores. With over 8,000 apps available, users can find tools for sales channels, product sourcing, marketing, store design, order management, and more. These apps are designed to help merchants optimize their online stores, improve customer experience, and boost sales.

Cloudflare is a platform that offers a range of products and services to help users build, secure, and optimize their websites and applications. It provides solutions for web analytics, troubleshooting errors, domain registration, content delivery, and more. Cloudflare also offers developer products like Workers and AI products like AI Vectorize and AI Gateway. Additionally, Cloudflare provides Zero Trust Access, Tunnel Gateway, and Browser Isolation services to enhance security and performance. The platform aims to simplify the process of managing online assets and improving user experience.

Jobscan is a comprehensive job search tool that helps job seekers optimize their resumes, cover letters, and LinkedIn profiles to increase their chances of getting interviews. It uses artificial intelligence and machine learning technology to analyze job descriptions and identify the skills and keywords that recruiters are looking for. Jobscan then provides personalized suggestions on how to tailor your application materials to each specific job you apply for. In addition to its resume and cover letter optimization tools, Jobscan also offers a job tracker, a LinkedIn optimization tool, and a career change tool. With its powerful suite of features, Jobscan is an essential tool for any job seeker who wants to land their dream job.

TestMarket is an AI-powered sales optimization platform for online marketplace sellers. It offers a range of services to help sellers increase their visibility, boost sales, and improve their overall performance on marketplaces such as Amazon, Etsy, and Walmart. TestMarket's services include product promotion, keyword analysis, Google Ads and SEO optimization, and advertising optimization.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

Awesome OpenVINO is a curated list of AI projects based on the OpenVINO toolkit, offering a rich assortment of projects, libraries, and tutorials covering various topics like model optimization, deployment, and real-world applications across industries. It serves as a valuable resource continuously updated to maximize the potential of OpenVINO in projects, featuring projects like Stable Diffusion web UI, Visioncom, FastSD CPU, OpenVINO AI Plugins for GIMP, and more.

AI-Drug-Discovery-Design is a repository focused on Artificial Intelligence-assisted Drug Discovery and Design. It explores the use of AI technology to accelerate and optimize the drug development process. The advantages of AI in drug design include speeding up research cycles, improving accuracy through data-driven models, reducing costs by minimizing experimental redundancies, and enabling personalized drug design for specific patients or disease characteristics.

The Ersilia Model Hub is a unified platform of pre-trained AI/ML models dedicated to infectious and neglected disease research. It offers an open-source, low-code solution that provides seamless access to AI/ML models for drug discovery. Models housed in the hub come from two sources: published models from literature (with due third-party acknowledgment) and custom models developed by the Ersilia team or contributors.

New AI Drug Discovery is a repository focused on the applications of Large Language Models (LLM) in drug discovery. It provides resources, tools, and examples for leveraging LLM technology in the pharmaceutical industry. The repository aims to showcase the potential of using AI-driven approaches to accelerate the drug discovery process, improve target identification, and optimize molecular design. By exploring the intersection of artificial intelligence and drug development, this repository offers insights into the latest advancements in computational biology and cheminformatics.

Zeta is a tool designed to build state-of-the-art AI models faster by providing modular, high-performance, and scalable building blocks. It addresses the common issues faced while working with neural nets, such as chaotic codebases, lack of modularity, and low performance modules. Zeta emphasizes usability, modularity, and performance, and is currently used in hundreds of models across various GitHub repositories. It enables users to prototype, train, optimize, and deploy the latest SOTA neural nets into production. The tool offers various modules like FlashAttention, SwiGLUStacked, RelativePositionBias, FeedForward, BitLinear, PalmE, Unet, VisionEmbeddings, niva, FusedDenseGELUDense, FusedDropoutLayerNorm, MambaBlock, Film, hyper_optimize, DPO, and ZetaCloud for different tasks in AI model development.

Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups.

The 'llms' repository is a comprehensive guide on Large Language Models (LLMs), covering topics such as language modeling, applications of LLMs, statistical language modeling, neural language models, conditional language models, evaluation methods, transformer-based language models, practical LLMs like GPT and BERT, prompt engineering, fine-tuning LLMs, retrieval augmented generation, AI agents, and LLMs for computer vision. The repository provides detailed explanations, examples, and tools for working with LLMs.

NVIDIA BioNeMo Framework is a collection of programming tools, libraries, and models for computational drug discovery. It accelerates building and adapting biomolecular AI models by providing domain-specific, optimized models and tooling for GPU-based computational resources. The framework offers comprehensive documentation and support for both community and enterprise users.

GOLEM is an open-source AI framework focused on optimization and learning of structured graph-based models using meta-heuristic methods. It emphasizes the potential of meta-heuristics in complex problem spaces where gradient-based methods are not suitable, and the importance of structured models in various problem domains. The framework offers features like structured model optimization, metaheuristic methods, multi-objective optimization, constrained optimization, extensibility, interpretability, and reproducibility. It can be applied to optimization problems represented as directed graphs with defined fitness functions. GOLEM has applications in areas like AutoML, Bayesian network structure search, differential equation discovery, geometric design, and neural architecture search. The project structure includes packages for core functionalities, adapters, graph representation, optimizers, genetic algorithms, utilities, serialization, visualization, examples, and testing. Contributions are welcome, and the project is supported by ITMO University's Research Center Strong Artificial Intelligence in Industry.

KG-RAG (Knowledge Graph-based Retrieval Augmented Generation) is a task agnostic framework that combines the explicit knowledge of a Knowledge Graph (KG) with the implicit knowledge of a Large Language Model (LLM). KG-RAG extracts "prompt-aware context" from a KG, which is defined as the minimal context sufficient enough to respond to the user prompt. This framework empowers a general-purpose LLM by incorporating an optimized domain-specific 'prompt-aware context' from a biomedical KG. KG-RAG is specifically designed for running prompts related to Diseases.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

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