BenevolentAI

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BenevolentAI utilizes AI to accelerate drug discovery, enhancing scientific innovation and the likelihood of discovering successful drugs.

How BenevolentAI can help you:

Empowers scientists with AI to uncover new insights from data.
Accelerates innovation in drug discovery.
Increases the probability of discovering successful drugs.

Why choose BenevolentAI: Key features

Versatile, scalable, and robust AI-enabled drug discovery platform.
Leverages multi-modal data foundations.
Rich drug pipeline with potentially best-in-class and first-in-class drug candidates.
Customizable SaaS products for better research productivity.

Who should choose BenevolentAI:

Biopharmaceutical companies seeking drug discovery acceleration.
Scientists looking for new insights in biomedical data.
Organizations aiming for collaboration in innovative therapeutics.

About BenevolentAI

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https://www.benevolent.com/

Release Date

March 2024

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Machine learning in drug discovery speeds up development - SiliconANGLE

Machine learning in drug discovery, along with artificial intelligence, is transforming the pharmaceutical industry by accelerating the development of new treatments. Historically, the process of discovering and developing new drugs has been painstakingly slow, fraught with high failure rates and incredibly expensive. However, new developments in AI-driven methodologies, particularly in digital chemistry and biology, are creating unprecedented opportunities to accelerate drug discovery, according to Stephen Mackinnon (pictured), vice president of applied machine learning at Recursion Pharmaceuticals Inc. "Machine learning helps us understand more about the world. It helps us understand more about biology so that when we take that risk, when we go through that grand experiment of a clinical trial," he said. "We're better equipped with knowledge of what that drug is doing, what that drug is doing to the system, what the drug is doing to the body so that we can make a more informed decision as what goes through." Mackinnon spoke with theCUBE Research's Savannah Peterson at Anyscale Ray Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming studio. They discussed how AI and machine learning are transforming drug discovery by accelerating research, improving predictions and enabling new experimental approaches. (* Disclosure below.) By leveraging AI and machine learning, companies can now conduct millions of experiments simultaneously. This scale is unthinkable without automation and advanced data analytics, Mackinnon explained. "The world of external data and the way that drug discoveries happened over the last 20, 40 years has been very targeted," he said. "Scientists have created very specific assays and experiments that they would run just for one program at a time to develop one drug at a time. And those do exist. There are little pockets of information here or there. But really at Recursion, what we do is challenge that to some extent." As AI continues to evolve, its role in drug discovery will only grow more significant. Companies are already seeing success in clinical trials, with new drug candidates emerging from AI-driven research methods, according to Mackinnon. "Recursion is one of the companies with the largest portfolios at the moment of clinical assets. There is a lag phase associated with that. A lot of the clinical trials going on now come from those earlier days of the research," he said. "But, ultimately, a lot of that was enabled by the compute. A lot of that was enabled by our ability to reconsider the scientific model for disease being right, looking at the cells and trying to perturb them in different ways. So, we definitely are seeing a lot more opportunities come up." Here's the complete video interview, part of SiliconANGLE's and theCUBE Research's coverage of the Anyscale Ray Summit 2024 event:

SiliconANGLE

Thu, 17 Oct, 12:12 AM UTC

Chasing AI's value in life sciences

In drug development, German pharmaceutical company Merck KGaA has partnered with several AI companies for drug discovery and development. And Exscientia, a pioneer in using AI in drug discovery, is taking more steps toward integrating generative AI drug design with robotic lab automation in collaboration with Amazon Web Services (AWS). Given rising competition, higher customer expectations, and growing regulatory challenges, these investments are crucial. But to maximize their value, leaders must carefully consider how to balance the key factors of scope, scale, speed, and human-AI collaboration. The common refrain from data leaders across all industries -- but specifically from those within data-rich life sciences organizations -- is "I have vast amounts of data all over my organization, but the people who need it can't find it." says Dan Sheeran, general manager of health care and life sciences for AWS. And in a complex healthcare ecosystem, data can come from multiple sources including hospitals, pharmacies, insurers, and patients. "Addressing this challenge," says Sheeran, "means applying metadata to all existing data and then creating tools to find it, mimicking the ease of a search engine. Until generative AI came along, though, creating that metadata was extremely time consuming." ZS's global head of the digital and technology practice, Mahmood Majeed notes that his teams regularly work on connected data programs, because "connecting data to enable connected decisions across the enterprise gives you the ability to create differentiated experiences." Majeed points to Sanofi's well-publicized example of connecting data with its analytics app, plai, which streamlines research and automates time-consuming data tasks. With this investment, Sanofi reports reducing research processes from weeks to hours and the potential to improve target identification in therapeutic areas like immunology, oncology, or neurology by 20% to 30%. Connected data also allows companies to focus on personalized last-mile experiences. This involves tailoring interactions with healthcare providers and understanding patients' individual motivations, needs, and behaviors. Early efforts around personalization have relied on "next best action" or "next best engagement" models to do this. These traditional machine learning (ML) models suggest the most appropriate information for field teams to share with healthcare providers, based on predetermined guidelines. When compared with generative AI models, more traditional machine learning models can be inflexible, unable to adapt to individual provider needs, and they often struggle to connect with other data sources that could provide meaningful context. Therefore, the insights can be helpful but limited.

MIT Technology Review

Thu, 31 Oct, 2:13 PM UTC

Accenture Collaborates with 1910 Genetics to Help Biopharma Companies Transform Drug Discovery with AI

Accenture (NYSE: ACN) has invested, through Accenture Ventures, in 1910 Genetics (or "1910"), a biotechnology company advancing small and large molecule drug discovery with a multimodal AI platform powered by laboratory automation. As part of this investment, Accenture and 1910 will collaborate to combine tailored solutions and scalable infrastructure to help clients in the biopharma industry accelerate drug target identification, reduce costs, and deliver better, more affordable therapies to patients. This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20241031043047/en/ 1910's proprietary Input-Transform-Output (ITO™) platform is a scalable, end-to-end AI solution designed to deliver better drug candidates with applications across all modalities and therapeutic areas. It is a multi-AI agent system comprising hundreds of models that leverages federated learning alongside three proprietary data streams -- computational data, wet lab ground truth biological data and wet lab proxy biological data. The platform helps enable drug discovery teams to achieve high precision target identification, optimize molecule design, and conduct advanced simulation throughout the R&D process. By facilitating data-driven decision making, it can increase the probability of clinical success, while shortening experimental iteration cycles and reducing the overall cost of drug development. "Taking an AI-driven approach is essential in order to reinvent the drug discovery and development process," said Tom Lounibos, global lead of Accenture Ventures. "Collaborating with 1910 Genetics allows us to integrate our AI expertise with their innovative technology and deliver solutions that can transform drug discovery and improve patient outcomes." Accenture's expertise in scaling AI solutions across enterprises can help biopharma companies smoothly integrate 1910's AI platform into their existing pipelines. Together, Accenture and 1910 will combine their experience and expertise to help drive breakthroughs in therapeutic development, improve the efficiency of drug discovery, and drive innovation for biopharma companies. Petra Jantzer, PhD, a senior managing director and global lead of Life Sciences at Accenture, added, "We look forward to joining up our diverse experience in implementing generative AI projects across enterprises and deep expertise in the life sciences sector with 1910 Genetics and its holistic, comprehensive AI platform. Our investment and collaboration support our vision for our biopharma clients to implement tech-enabled drug discovery, automating processes, breaking down silos and increasing productivity." "In our discussions with biopharma companies, the desire for AI transformation of their traditional R&D processes is evident," said Jen Nwankwo, PhD, founder and CEO of 1910 Genetics. "It's also clear that 1910's end-to-end AI platform -- from in silico to the wet lab and back -- addresses the challenges that biopharma companies face with point solutions. By collaborating with Accenture, we aim to bring 1910's AI platform to biopharma companies as an enterprise-wide horizontal infrastructure that breaks down barriers in data, model, and computing power to accelerate the discovery and development of both small and large molecule therapeutics across all therapeutic areas." In conjunction with this announcement, Dr. Petra Jantzer and Tom Lounibos will join the Business Advisory Board of 1910, and Dr. Kailash Swarna, a managing director in Life Sciences at Accenture, and Dr. Cecil Lynch, Biomedical Informatics lead at Accenture, will join the Technology Advisory Board of 1910. 1910 will also join Accenture Ventures' Project Spotlight, an engagement and investment program for startup companies that create or apply disruptive enterprise technologies. Accenture is a leading global professional services company that helps the world's leading organizations build their digital core, optimize their operations, accelerate revenue growth and enhance services -- creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 774,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world's leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at www.accenture.com. About 1910 Genetics 1910 Genetics is the only biotechnology company advancing small and large molecule drug discovery with a multimodal AI platform powered by laboratory automation. We integrate AI that leverages federated learning alongside three proprietary data streams -- computational data, wet lab proxy biological data, and wet lab ground truth biological data -- to deliver novel drug candidates and software solutions to leading biopharma and tech partners, and advance our internal pipeline for neurological, autoimmune diseases, and cancer. We recently established a commercial partnership with Microsoft to bring our ITO™ platform to biopharma companies at scale. 1910 was launched in 2021 with a combined seed and Series A funding of $26.1M from M12-Microsoft's Venture Fund, Playground Global, OpenAI's Sam Altman, FoundersX Ventures, and other leading investors. We have since established our HQ and lab facilities in Boston's Seaport District and continue to hire a world-class team. To learn more, visit www.1910genetics.com. Copyright ©2024 Accenture. All rights reserved. Accenture and its logo are registered trademarks of Accenture.

Market Screener

Thu, 31 Oct, 2:38 PM UTC

Dotmatics aims to speed drug development, break data silos with Geneious Luma

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Even as enterprises across sectors explore how to integrate generative AI, it's clear that biomedical research and the sciences are among the areas that could benefit most -- as highlighted in the recent Nobel Prizes in Chemistry and Physics awarded to AI researchers. Now Dotmatics, a leader in research and development scientific software, wants to give drug researchers the power of AI to speed up their development of new, life-saving and improving drugs. Today, the Boston-based company launches Geneious Luma, a powerful new bioinformatics solution for antibody discovery, built on its Luma Scientific Intelligence Platform. Geneious Luma is designed to streamline the process of biologic therapeutic discovery by integrating advanced sequence analysis, data management, and AI-powered automation. This release marks the first of several multimodal solutions aimed at transforming scientific research and accelerating the discovery of new therapies. Thomas Swalla, CEO of Dotmatics, explained the benefit of Geneious Luma in a recent video interview with VentureBeat: "The problem we're solving is that discovering new molecules and drugs has become increasingly complicated. It takes over a decade to bring a drug to market and costs anywhere from two to six billion dollars." With Geneious Luma, Dotmatics addresses the challenges of fragmented workflows and siloed data in biologic research. The platform integrates key tools like Geneious Prime and Geneious Biologics to streamline antibody sequence discovery and protein engineering, from in-silico design to wet-lab experimentation and decision support. As Swalla noted, "Dotmatics is addressing the fragmentation and complexity of drug discovery. The promise of new therapies, like cell and gene therapies, is tremendous, but the science is really complicated. We're working to pull all these areas together." As such, it goes up against other AI drug discovery platforms such as VeriSIM Life and Platforma.bio, but can also integrate data from them -- with the scientist users' permission, of course. Antibody research Dotmatics supports over 2 million scientists and 10,000 customers in 180 countries. Its solutions streamline R&D processes by connecting science, data, and decision-making. Dotmatics' team of over 850 employees operates globally, with its principal office in Boston. Geneious Luma builds upon the capabilities of the Luma platform to provide seamless bioinformatics solutions tailored specifically for antibody and protein engineering. The platform is designed to accelerate workflows across therapeutic modalities, including antibodies, antibody-drug conjugates (ADCs), RNA and gene therapies, and vaccines. t enables researchers to work more efficiently by automating complex data processes and centralizing all relevant data into a unified workspace. By incorporating tools like Geneious Prime, which offers industry-leading cloning and sequence analysis, and Geneious Biologics, which enhances antibody sequence discovery, Geneious Luma ensures that researchers have the advanced capabilities needed to tackle the complexities of antibody engineering. Swalla further emphasized how the platform enhances research efficiency: "With our new product, Luma, you can pull together massive datasets across these fragmented areas of science, putting language models on top of them to speed up the discovery of new molecules and drugs." Advances in AI The flexibility of Geneious Luma is one of its greatest strengths. It leverages AI and machine learning to automate workflows, enabling scientists to manage complex biological data with greater accuracy and speed. Michael Swartz, Chief Strategy Officer at Dotmatics, told VentureBeat in the same video interview call how the platform adapts to real-time needs: "Our software is able to adapt in near real-time to whatever the scientist decides to do. Luma can call out to external models like [DeepMind's] AlphaFold to assist, which hasn't been possible before." But that's just one of many external AI tools and resources that users can pipe into Geneious Luma. "Today, we enable AI models through Luma, but our customers can pick whichever model they want and put it closest to the data in their life sciences ecosystem," Swalla clarified. "We know we have to partner with companies that bring models and help with accelerated compute because that's what will make AI in drug discovery economically feasible." In addition to AI-assisted discovery, Geneious Luma incorporates powerful tools like Luma Lab Connect, which automates data ingestion from lab instruments such as flow cytometers and mass spectrometers, allowing researchers to efficiently collect, process, and analyze data from multiple sources. "When you think about instrument integration, it's not static," Swartz explained. "We grab the data off the software and deliver it precisely at the right time and in the right organizational framework, in a frictionless way." Solving for siloed data In the increasingly complex landscape of therapeutic discovery, the ability to manage large and diverse datasets is crucial. Geneious Luma offers a solution to one of the biggest hurdles in life sciences today -- siloed and unstructured data. Swalla commented, "The real issue in life sciences isn't a lack of AI models; it's that the data isn't big enough, structured enough, or trusted enough to train those models. That's the problem we're trying to solve with Luma." By integrating all the necessary tools and workflows into a single, cohesive platform, Geneious Luma enables researchers to overcome these data challenges, fostering collaboration across teams and speeding up the discovery process. Beyond antibodies While the initial focus of Geneious Luma is on antibody and protein engineering, Dotmatics plans to extend the platform's capabilities into other areas of biologic research, such as CAR-T therapies, CRISPR, and RNA-based medicine. Swalla sees this as a tremendous opportunity: "In this industry, people are still using paper and pencil, and there are companies that haven't moved to the cloud. We're 15 years behind in terms of tech adoption, which is a huge opportunity for us." The flexibility of the Geneious Luma platform ensures that it can be adapted for various therapeutic discovery processes, driving efficiency across the industry. Dotmatics is also exploring opportunities to extend the platform into other scientific domains, including material science and agritech. Geneious Luma is available now as part of the Dotmatics Luma platform, with further enhancements planned for the future. As Dotmatics continues to innovate, the company aims to push the boundaries of drug discovery through integrated bioinformatics and AI-driven research.

VentureBeat

Tue, 22 Oct, 2:31 PM UTC

Drug Discovery Informatics Market Size Set to Surpass USD 6.8 Billion by 2031 with 10.9% CAGR as AI Revolutionizes Data Analysis in Drug Development | Transparency Market Research, Inc.

Wilmington, Delaware, United States, Transparency Market Research Inc. - , Nov. 04, 2024 (GLOBE NEWSWIRE) -- The global drug discovery informatics market (약물 발견 정보학 시장) is estimated to flourish at a CAGR of 10.9% from 2023 to 2031. Transparency Market Research projects that the overall sales revenue for drug discovery informatics is estimated to reach US$ 6.8 billion by the end of 2031. Quantum computing, although in its nascent stage, holds immense potential. Its ability to process complex computations exponentially faster than traditional computers could revolutionize molecular simulations and accelerate drug discovery timelines significantly. This technology's full integration into informatics systems remains a work in progress. The advent of blockchain technology showcases promise in ensuring data integrity, transparency, and security within drug discovery processes. Implementing blockchain could streamline data sharing among researchers, pharmaceutical companies, and regulatory bodies, enhancing collaboration while safeguarding sensitive information. Download Sample PDF of the Report: https://www.transparencymarketresearch.com/sample/sample.php?flag=S&rep_id=33713 The rise of interdisciplinary approaches, such as the integration of omics data (genomics, proteomics, metabolomics), with informatics tools promises a more holistic understanding of disease mechanisms. This fusion facilitates the identification of novel drug targets and the development of precise therapeutics tailored to individual patient profiles, advancing the era of personalized medicine. Drug Discovery Informatics Market: Competitive Landscape The drug discovery informatics market navigates a dynamic landscape shaped by technological advancements, competition, and evolving research needs. Key players like Schrödinger, Genedata, and Certara drive innovation, offering robust informatics platforms. Emerging contenders such as Collaborative Drug Discovery and OpenEye Scientific contribute disruptive solutions. Cloud-based platforms and AI-driven tools from companies like IBM and Dassault Systèmes further intensify competition, revolutionizing data analysis and accelerating drug discovery. Consolidation and strategic collaborations, witnessed among major players, emphasize expanding portfolios and global market presence. With increasing demand for efficient solutions, the competitive landscape continually evolves, fostering innovation to expedite drug development and meet healthcare challenges. Some prominent manufacturers are as follows: Charles River Laboratories International Inc.Thermo Fisher ScientificPerkinElmer Inc.Biogen Inc.Boehringer Ingelheim GmbHInsilico Medicine Inc.International Business Machines CorporationSchrödinger LLCCuria Global, Inc.Certara USA Key Findings of the Market Report Discovery informatics spearheads the drug discovery informatics market, driving innovation and efficiency in early-stage drug research and development.In-house informatics leads the drug discovery informatics market, empowering companies with tailored solutions and enhanced control over research processes.Molecular modeling emerges as the leading function segment in the drug discovery informatics market due to its predictive modeling capabilities. Drug Discovery Informatics Market Growth Drivers & Trends Increasing integration of artificial intelligence and machine learning algorithms accelerates data analysis, enhancing efficiency in drug discovery processes.Adoption of cloud-based informatics platforms facilitates collaboration, scalability, and real-time data accessibility, driving operational agility.Growing emphasis on personalized medicine fuels demand for informatics tools tailored to individual patient profiles and treatment modalities.Leveraging big data analytics transforms data into actionable insights, optimizing decision-making and shortening drug development timelines.Collaborations between pharmaceutical companies and technology providers foster innovation, enabling the development of novel informatics solutions to address evolving research needs. Unlock Growth Potential in Your Industry! Download PDF Brochure: https://www.transparencymarketresearch.com/sample/sample.php?flag=S&rep_id=33713 Global Drug Discovery Informatics Market: Regional Profile North America stands as a frontrunner, driven by technological advancements, robust infrastructure, and substantial investments in R&D. The presence of key players like Schrödinger and Certara fuels innovation, fostering a thriving market for informatics solutions.In Europe, particularly in countries like Germany and the UK, a strong emphasis on research excellence and collaborations between academia and industry defines the landscape. Companies like Genedata lead with sophisticated informatics platforms, leveraging Europe's scientific expertise to advance drug discovery.The Asia Pacific region emerges as a burgeoning hub, witnessing rapid growth due to increasing investments in healthcare infrastructure and rising demand for novel therapeutics. Countries like China and India foster innovation, propelled by government initiatives and a burgeoning biotech sector. While the market is evolving, companies such as WuXi AppTec and Infosys contribute significantly, amplifying the region's prominence in the global drug discovery informatics arena. Product Portfolio Biogen Inc. pioneers in neuroscience, offering innovative therapies for neurological and neurodegenerative diseases like multiple sclerosis and Alzheimer's. With a focus on groundbreaking research, Biogen aims to redefine treatment approaches, improving lives worldwide through advanced biotechnology and pharmaceutical solutions.Boehringer Ingelheim GmbH excels in healthcare, dedicated to enhancing patients' lives. Focused on pharmaceuticals, the company delivers high-quality products in various therapeutic areas like respiratory, cardiovascular, and oncology, emphasizing innovation and patient-centricity in its global reach.Insilico Medicine, Inc. specializes in AI-driven drug discovery and development. Combining deep learning algorithms and bioinformatics, Insilico accelerates drug development, striving to address unmet medical needs efficiently. By revolutionizing traditional approaches, it aims to bring novel therapeutics to market faster, transforming healthcare landscapes globally. Drug Discovery Informatics Market: Key Segments By Product Discovery InformaticsDevelopment Informatics By Mode In-house InformaticsOutsourced Informatics By Function Sequencing and Target Data AnalysisDockingLead Generation InformaticsIdentification and Validation InformaticsMolecular ModelingOthers By End User Pharmaceutical and Biotechnology CompaniesContract Research OrganizationsOthers By Region North AmericaLatin AmericaAsia PacificEuropeMiddle East & Africa Buy this Premium Research Report - https://www.transparencymarketresearch.com/checkout.php?rep_id=33713&ltype=S More Trending Reports by Transparency Market Research - Stem Cell Manufacturing Market - The global stem cell manufacturing market size (줄기세포 제조 시장) is anticipated to touch value of USD 26.6 Billion by 2033. Medical Foods Market - The medical foods market(의료식품시장) to reach the valuation of US$ 33.3 Billion by 2030.PEEK Interbody Devices Market - The PEEK interbody devices market (PEEK 체간 장치 시장) is expected to grow at a CAGR of 7.7% from 2024 to 2034 and reach US$ 5.0 Billion by the end of 2034Peptide Therapeutics Contract API Manufacturing Market - The peptide therapeutics contract api manufacturing market (펩타이드 치료제 계약 API 제조 시장) is expected to grow at a CAGR of 6.8% from 2024 to 2034 and reach US$ 5.2 Billion by the end of 2034. About Transparency Market Research Transparency Market Research, a global market research company registered at Wilmington, Delaware, United States, provides custom research and consulting services. Our exclusive blend of quantitative forecasting and trends analysis provides forward-looking insights for thousands of decision makers. Our experienced team of Analysts, Researchers, and Consultants use proprietary data sources and various tools & techniques to gather and analyses information. Our data repository is continuously updated and revised by a team of research experts, so that it always reflects the latest trends and information. With a broad research and analysis capability, Transparency Market Research employs rigorous primary and secondary research techniques in developing distinctive data sets and research material for business reports. Transparency Market Research Inc. CORPORATE HEADQUARTER DOWNTOWN, 1000 N. West Street, Suite 1200, Wilmington, Delaware 19801 USA Tel: +1-518-618-1030 USA - Canada Toll Free: 866-552-3453 Website: https://www.transparencymarketresearch.com Email: sales@transparencymarketresearch.com Follow Us: LinkedIn| Twitter| Blog | YouTube Market News and Data brought to you by Benzinga APIs

Benzinga

Mon, 4 Nov, 4:03 PM UTC

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