Labfolder

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Labfolder is a cloud-based Electronic Lab Notebook (ELN) that enables scientists to optimize their research data management and laboratory processes.

How Labfolder can help you:

Streamlines data entry and integration, centralizing all your research data in one place.
Enables quick data retrieval, allowing you to find your data in seconds.
Facilitates team collaboration, serving as the platform for successful teamwork.
Ensures data integrity and security, keeping your data secure and compliant.
Improves inventory management, helping you manage inventory with ease.

Why choose Labfolder: Key features

Centralized data management for easy data sharing and access.
Compliance with FDA, ISO, and GLP regulatory standards for research integrity.
Advanced features like sign & witness, XHTML export, and custom share settings for enhanced data handling.
Offers both cloud version and local server installation for flexible storage options.
Personalized onboarding and data management consultancy for optimized laboratory processes.

Who should choose Labfolder:

Individual researchers seeking a secure and integrated platform for their data.
Research teams looking for an ELN to coordinate their efforts and streamline workflows.
Organizations in need of a compliant and efficient system for managing laboratory data and processes.

About Labfolder

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https://labfolder.com/

Release Date

March 2024

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The AI-Powered Lab Assistant with Scientific Awareness

Interview conducted by Danielle Ellis, B.Sc.Oct 25 2024 insights from industryRob Brown Vice President of Product and Pre-SalesSapio Sciences In this interview, Rob Brown, Vice President of Product and Pre-Sales at Sapio Sciences, discusses Sapio's AI-powered lab assistant, ELaiN, and how it is positioning Sapio as a leader in science-aware lab informatics. Could you please introduce yourself and give us a brief overview of your career and current position at Sapio Sciences? I'm Rob Brown, Vice President of Product and Pre-sales at Sapio Sciences. I've been at Sapio since March 2023, but I've worked in the research informatics space for about 25 years with Dotmatics and Accelrys, which became BIOVIA. I started my career as a postdoc at Abbott Labs. Who is Sapio Sciences, and what does the company stand for in terms of its mission and values, especially within the healthcare and pharma industries? Sapio Sciences is a research and clinical informatics company. We have solutions that we sell to life science, pharma and biotech, and clinical diagnostic companies. Our platform spans across lab operations, from early discovery all the way through development to manufacturing. At the heart of the solution is the Sapio Lab Informatics platform, and built on that platform, we have our Electronic Lab Notebook (ELN), our Laboratory Information Management System (LIMS), and our scientific data management solution, Sapio Jarvis. What are the key solutions Sapio Sciences offers to the pharma sector, and what sets them apart from other competitors in the industry? Our main solutions are our ELN and LIMS, although what really sets Sapio apart is that everything we do is built on a common platform. Historically, a lab or research department might buy an ELN from one vendor and a LIMS from another vendor and then spend a lot of time trying to make them play nicely together. Sapio has built a platform where we can surface different capabilities depending on the use case or where a customer is in the research stage. For example, when a customer is in the discovery stage, they will be looking for ELN capabilities, but later in the workflow, they will likely require that same capability as a controlled LIMS process when they need to lock everything down or perform a sequence of experiments across multiple teams. Essentially, the ELN and the LIMS are different faces on a common platform. There's a common data model, a common way of searching, and a common way of visualizing and analyzing that information. What also sets us apart is that it is a low-code/no-code platform. Many legacy vendors in this industry's platforms build on some very old technology. Ours is very modern, web-based, SaaS, no-code/low-code, and fully integrated across our solutions and out-of-the-box applications, including medicinal chemistry, next-generation sequencing (NGS), histopathology, bioprocessing, and environmental monitoring. What range of industries can benefit from Sapio Sciences' solutions, and how do your products adapt to different sectors' needs? Practically, any industry that conducts scientific research could use our platform, but the majority of our customers are in biotech, pharma, and clinical diagnostics. That's why we call our platform "science-aware." We present the tools and the data in a way that makes sense to scientists. This differentiates what we do from generic IT companies. These organizations are proponents of using "data lakes" to store information, which is fine in finance, telecoms, or other "non-science" industries, but scientists work with scientific data types and not just text/numbers. . For example, they will want to see the 3D structure of the protein or the entire structure of the small molecule attached to an antibody, which can't be achieved in a data lake. But "science-aware" goes further. When a scientist queries a set of data, they will be looking to apply very specific scientific algorithms to figure out what makes a set of molecules active or what makes a particular set of genes have the response that they're seeing. Scientific analytics and algorithms are required to do that, and they are all built right into our platform. In an industry as complex as healthcare, how does Sapio Sciences make lab informatics simpler while driving better results for researchers? We look at this in two ways: how to make life simpler for the scientists using our software and how to make life simpler for the IT departments that have to maintain our software. On the IT side, it's really about our low-code/no-code approach. We've designed the Sapio platform to integrate easily into an existing lab and a broader corporate IT landscape. It's easily configurable and integrates into data models and workflows without having to write vast amounts of difficult-to-maintain code. For the scientist, we ensure that all of their data is unified, so there is no requirement to look across multiple applications to find a key piece of data. Everything's presented graphically in clean, modern interfaces, without the requirement to know structured query language (SQL) to search. It's very easy for a scientist to go in and do their work. Like any software, you still need to learn how to use it -- how to build a data query or enter an experiment, for example. But with ELaiN, Sapio's Electronic Laboratory Artificially Intelligent Notebook, we have a built-in AI natural language interface directly in the platform that removes that requirement. As a scientist, I know I want to do it, and the ELaiN, effectively an AI assistant, powers the software for you. If I want to run a search, I could ask, "Find all my samples with particular properties," and the AI assistant instructs the software to run the search and deliver the results in the most effective way. It's a complete paradigm change, and it's hugely more efficient for scientists, putting them back in the lab doing research instead of trying to figure out software. Scientists know the problem they want to solve. They now increasingly don't even have to learn how to use the software to be able to use the software, which is great. Now they're back in the lab doing something. What are the key benefits that customers in the medical sector can expect when using Sapio Sciences' solutions, particularly in terms of efficiency, data management, and research outcomes? A key benefit of our solutions is the shortening of discovery cycles. For example, using a modern ELN allows scientists to easily capture, analyze, and manage data throughout their research project. This streamlines the decision-making process and makes tracking down data simple, allowing them to move forward much more quickly, potentially saving hours on each research "cycle." But it's not just about speed. It's also about making more informed decisions. Our platform provides researchers with centralized access to critical data across the organization, which helps them make smarter choices or gain more accurate insights at every step. As a result, they might reach a clinical candidate in half the number of research cycles. Considering that each cycle is measured in weeks, that's a huge time saver. When you consider that drug discovery takes years and costs billions of dollars, shaving fractions off the timeline can save huge amounts of money and speed up the time it takes to bring a clinical candidate to market. When you consider that drug discovery takes years and costs billions of dollars, shaving fractions off the timeline can save huge amounts of money and speed up the time it takes to bring a clinical candidate to market. What are some of the key challenges you face when developing and refining lab informatics products for the pharma industry, and how do you address them? Across the pharmaceutical industry, you have a very diverse range of organizations, from small startup biotechs to multinational pharmaceutical companies with thousands of researchers and years of research data. One of the main challenges is how to build a solution that meets the requirements of all research organizations across this broad spectrum. With our platform, we've identified the main requirements that allow us to meet about 80% of the functionality that's common across research teams. Every company's going to have a specific way of working, but 80% seems to cover the core functionality. Then, we have a very easy way for customers to configure the final 20% to make the technology work for them, matching processes, workflows, or team structures. A second challenge, especially with larger, more established organizations, is that their existing infrastructure might be 10, 20, or 30 years old, and scientists absolutely rely on those systems to solve a problem in a particular area. So you can't just rip out the entire infrastructure; you have to play nice, which we do! Everything comes back to the platform being open, unified, easy to configure, and having pre-configured core capabilities that are common across research and drug discovery. How is Sapio Sciences leveraging artificial intelligence (AI) in its solutions, and what impact do you see AI having on the future of lab informatics and pharma research? ELaiN - Science-Aware AI Chat - Search and Plate Set Up Using VoicePlay AI is going to change everything, but we are still at a comparatively early stage from a drug discovery point of view. The approach Sapio is taking is to use AI, machine learning (ML), and natural language processing (NLP) to accelerate our vision of making life easier for scientists. We're doing this by training the AI embedded in our platform to understand what is required when a scientist says, "Make me an experiment with ten samples laid out on a plate," and to instruct the software in the steps needed to complete the request. By giving ELaiN access to scientific algorithms, we empower the system to help the scientists. For example, ELaiN can help a researcher make a particular molecule by providing the reaction schemes, essentially performing the task of an expert chemist in a lot less time. The next step is to apply AI and machine learning to all the research data available within an organization. There are a number of challenges with this, not least ensuring that proprietary information stays secure and confidential and is not shared across other LLMs (Large Language Models). AI isn't going to replace scientists, but it might replace those scientists who don't leverage what AI can do. AI isn't going to replace scientists, but it might replace those scientists who don't leverage what AI can do. In what ways do you anticipate the pharma industry's needs changing in the coming years, and how is Sapio Sciences positioning its products to meet those future demands? When our CEO Kevin (Cramer) founded the company in the early 2000's, he took a very different approach from many of the other vendors in the industry. They were all about selling a single solution to solve a specific problem. But Kevin spent a lot of time building the platform and making sure that the core of the Sapio solutions was a robust, scalable, and future-proofed foundation on which to build applications and tools that would make scientists' lives easier. Having this platform to build on means our developers in York, PA, can be super creative in building out solutions that solve the real problems of our customers and keep pace with the rapidly changing landscape in life sciences. A great example is our GMP LIMS. Working with our customers, we saw the challenges they were having around ensuring GMP compliance in environmental monitoring and stability testing in manufacturing. Our developers were able to build a LIMS that specifically solves these customer problems really quickly as they were building on a robust platform. Sapio is uniquely positioned in the market to have that dynamic, future-proofed, and innovative approach, so as new science comes along, we can adapt to our customers' evolving needs Where can readers find more information? https://www.sapiosciences.com/ About Rob Brown Rob Brown is Senior Director of Product Marketing and Presales at Sapio Sciences. He was previously at Dotmatics, where he was Head of Global Presales, Product Marketing & Product Management. Earlier in his career, he ran product marketing teams at Accelrys, SciTegic, and MSI. Rob started his career as a postdoc and later research scientist at Abbott Laboratories (now Abbvie). He received his PhD in Cheminformatics from the University of Sheffield, UK.

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The Role of Data and Automation in Advancing Life Sciences

Recent developments in data management and automation are transforming the landscape of life sciences research. This story explores the challenges of handling scientific data and the potential of automation to enhance flexibility in laboratories.

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How cloud-first automation is transforming lab workflows

Sponsored Content by AutomataReviewed by Louis CastelSep 12 2024 In the ever-evolving world of laboratory automation, labs have traditionally relied on on-premises solutions to optimize solutions. The rise of flexible and secure cloud-first automation brings with it a new era of platforms whose high levels of responsiveness can harness the transformative potential of data. These platforms can also overcome the physical and geographical boundaries that impede the collaborative process. This article will explore cloud-first automation, its role in the future for innovative laboratories, and the potential benefits compared to non-cloud solutions. Image Credit: metamorworks/Shutterstock.com An introduction to cloud-first automation Automation platforms like Automata's LINQ combine instruments, human insight, robotics, visualization tools, multi-point data collection, and solving technologies. By simplifying and automating actions, these platforms free up scientists' time and improve the scale and quality of experiment results. By selecting a platform with cloud-based software, the impact and benefits of automation extend beyond physical boundaries. Researchers across the organization can easily access the lab's cloud-connected workcells, enhancing scientific progress and maximizing the return on investment for capital equipment. Additionally, fully contextualized experimental results are stored in a unified data warehouse, accessible from anywhere within the organization. Cloud-first automation offers a number of other benefits, including: Flexibility Remote accessibility Easy integration with third-party software such as AI Greater visibility and collaboration Secure and cost-effective Eliminates data inconsistency issues Round-the-clock operational capabilities Stringent adherence to regulatory requirements Ease of use, regardless of automation experience It is suitable for installation in most regions around the world The benefits of cloud-first automation platforms Cloud-first solutions are particularly beneficial to those who require their data to be fully traceable and of high quality, work in collaborative environments, want to maximize return on investment, and require access to the latest technology and secure updates. The relationship between cloud-first lab automation and quality, manageable data Cloud-first lab automation enables the rapid generation of robust datasets by providing users with secure, 24/7 access to their systems from anywhere in the world. Unlike on-premise solutions, cloud-based automation considers the purpose of the data throughout the entire experiment lifecycle, not just in terms of generating larger quantities of data. LINQ can automate entire workflows, allowing users to record every environmental condition for each machine at every step of the process, with all user and automation actions being closely monitored The quantity of data collected will ensure fully contextualized workflow results, which can be segmented and analyzed for numerous reasons. On-premise solutions often rely on manual data collection and transcription processes, particularly when automation lacks software connectivity. In such cases, scientists must manually manage and export information from multiple local, instrument-specific hubs. This can lead to data collection delays, data loss, and transcription errors. Even when remote access is available, the inability to control workflows can restrict its effectiveness, ultimately compromising the reliability of results and the quality of the data produced. In contrast, platforms with cloud-based connectivity, such as LINQ Cloud, network instruments to a central location, enabling automatic, instant, and error-free data collection. This data is immediately available for analysis and global collaboration. Automatic transfer and connectivity alleviate the workload on scientists, allowing for the effortless collection of a greater number of data points, which in turn enhances the quality of metadata and improves the experimental context. Gathering information required by regulatory bodies like the FDA will also be quicker and more robust, and collaboration -- especially with external teams -- becomes significantly easier. The positive impact of cloud-first automation on collaboration Cloud-first solutions enhance the collaborative process for labs transitioning from offline to online working. Automata uses Google Workspace to create and store shareable documents with minimal issues, a significant improvement over the traditional method of installing Office from a disc or CD on a local machine and sharing files via USB sticks or file transfers. By utilizing cloud-based lab automation, the entire workforce has the opportunity to access a fully connected network of instrument resources, enabling multiple users to share equipment, perform workflows, and view experiment results collaboratively. Collaborating on workflow management Cloud-based automation, offered by companies like LINQ, enables the use of a shared platform for the design, simulation, and interrogation of experiments. This approach allows workflows to be designed, built, and simulated by anyone at any time, with run instructions that can be uploaded, monitored, amended, and downloaded from anywhere in the world. Workflows can be remotely scheduled, executed, and triaged. In theory, different individuals can be responsible for various parts of the workflow, as everything is managed through secure user permissions validated by a scheduling engine. Actions are recorded at the user, workflow, and instrument levels, with audit trails and log files easily accessible for review. Collaborating with shared data Thanks to cloud-based automation platforms, collected data can be transferred in real time to a specific data source, allowing users to work from one centralized source. In an automated scenario, cloud connectivity can allow an entire organization to access a world of contextualized data for a range of needs. This valuable repository of high-quality, traceable data is a strong foundation for building multidisciplinary teams that can efficiently iterate and improve processes. Cloud-first automation and maximizing performance The initial and main impetus for purchasing a lab automation platform is to enhance productivity. While the automation of any process will offer some efficiencies, utilizing an end-to-end, cloud-based solution can facilitate even greater opportunities to impact performance. Efficient workflows Cloud-based lab automation can assist users in optimizing workflows in a variety of unique ways: Direct communication with instruments means the system can check that set-up, calibration, and conditions are completely accurate compared to the workflow's design and instructions. Users can understand each conditional and constraint in play without the need to access separate on-site repositories. Since everything is stored in the cloud, resourcing deficits can be easily rectified, meaning, for example, ensuring that the absence of a team member no longer leads to delayed activities. Users in any location can offer assistance with anything from tackling workflow design challenges to checking run instructions and predictions. Shared visualizations can become a source of inspiration to others and assist users in upskilling. Activity audit trails facilitate the full interrogation of information, allowing further opportunities to identify issues and improve workflows. Online validation and remote-access workflow management allow any user to identify and instantly correct workflow issues early on, helping share responsibility and keep productivity on track. Maximized resources Cloud-based lab automation connects multiple systems to a single online interface, enabling more effective planning and resource allocation. For example: Capacity can be monitored, and loads can be shared more evenly. Resources can be ringfenced for specific clients, experiments, or teams with full visibility. Instrument data can help track equipment performance, facilitating proactive maintenance. Planned downtime is no longer an issue as tasks can be assigned to other instruments or workcells. Cloud-based automation allows tasks to be performed online quickly and transparently. There is no unexpected downtime or maintenance, and granular lab productivity information can be shared with leadership as required. Cloud-first automation and future-ready processes Artificial intelligence (AI)-ready cloud-first automation will play a vital role in delivering what the industry needs now and in the future. True collaboration, without boundaries and underpinned by scientifically valid and high-quality data, can help deliver cost-efficient sequencing, faster drug discovery, and facilitate greater access to personalized therapeutics. AI is being employed to support these goals, and while AI in its many forms can certainly play a role, there are challenges at an industry scale and for those planning to invest in lab automation platforms. In terms of industrial-scale applications, AI can only be as good as the size of the model used to train it, as well as the quantity and quality of the data utilized. There is a data issue in life sciences, as too much of the sector's data is untraceable, unreliable, and uncontextualized. Cloud-based lab automation has the capacity to generate and collect vast sets of fully contextualized results by connecting all elements to one data lake without error. This produces large, unified, high-quality data sets that are perfectly suited to the needs of AI models. Opting for a cloud-based solution now establishes a strong foundation for integrating AI in the future. Cloud-first automation and operational readiness The widespread uptake of internet-based tools such as online ticketing systems and remote viewers has raised customer expectations in terms of multi-layered security, automatic updates, and fast support from technology providers. Possessing a cloud-based lab automation platform ensures access to all these and more, on a larger and faster scale than ever before. There are several advantages to this approach, including: Instant online support reduces lab downtime, and response times can be reduced from days to hours or less. New equipment can be seamlessly integrated by downloading and applying drivers and integrations online. Remotely visible data logs can simplify the troubleshooting process for users or their automation provider. As errors are instantly reported to operators via a remote interface, the user is always in control. The ability to remotely trigger software updates means these can be applied seamlessly and at any time without needing an on-site visit. Cloud-first automation and security The sensitive nature of data in life sciences, along with the value of materials utilized in experiments, means security is of the utmost importance. To address concerns about internet reliability, cloud-based access, and potential disruptions from updates, Automata has developed various methods to ensure that users of cloud-based scientific platforms remain online and secure. LINQ offers a range of tenancy options that provide a unique, isolated cloud environment that can be domiciled in any of AWS's regional locations. This setup gives users control over updates and enables the creation of more detailed and specific audit trails. Users can decide whether to keep a software version locked or accept periodic updates, with the ability to pin historical protocols, scheduling, and security settings to workcells. This ensures that results do not need to be re-validated after each update. LINQ features an offline mode for added security in the event of a local networking failure or internet outage. This allows workflows to continue running, with experimental data being collected and ready for upload once the connection is restored. Already-built workflows can be executed repeatedly, even when offline. User-based access permissions are applied to ensure that all profile types can access LINQ Cloud without risking unauthorized changes. Cloud-first lab automation solutions are transforming how laboratories operate, offering unparalleled accessibility, flexibility, and efficiency compared to traditional on-site systems. Platforms like Automata's LINQ allow labs to automate complex workflows, collect and manage high-quality data, and improve cross-team collaborations. These solutions will improve productivity and resource utilization, ensuring labs remain secure, agile, and future-ready. They will also be ready to integrate emerging technologies, such as artificial intelligence, when needed. As the scientific landscape continues to evolve, the adoption of cloud-first automation and cloud-based solutions is becoming increasingly essential. LINQ: The cloud-based automation from Automata Automata's LINQ platform houses and connects instruments on a space-saving, robot-enabled lab bench, allowing users to design, schedule, and manage workflows remotely using cloud-based software. Video Credit: Automata Acknowledgments Produced from materials originally authored by Automata Technologies Ltd. About Automata Born from a world-leading research lab, Automata is making total workflow automation accessible to labs frustrated by the limitations of their own environment. Accelerating the innovation evolution When two architects from Zaha Hadid's research lab first approached robotics, their idea was to explore applications specific to architectural engineering. But they soon discovered that modern automation wasn't just unnecessarily complex - it was actively restricting innovation. And not just within their industry - within many others too. It was clear that robotic automation was a field where their combined experience in computational research and design could make a real difference. Assembling a team of industry experts, Automata was founded, with a clear aim: to enable new opportunities for innovation with automation. A clearer path to progress Automata's focus narrowed on an industry where they felt their expertise could have the most impact - life sciences, and particularly within biolab environments. Since then, the team has been working closely with leading pathology labs to pioneer protocols that enable labs to scale with precision Automata Labs is the product of that philosophy - simplifying lab environments and empowering the people working tirelessly in the pursuit of progress. Sponsored Content Policy: News-Medical.net publishes articles and related content that may be derived from sources where we have existing commercial relationships, provided such content adds value to the core editorial ethos of News-Medical.Net which is to educate and inform site visitors interested in medical research, science, medical devices and treatments.

News-Medical

Thu, 12 Sept, 2:01 PM UTC

Effective lab data management: Advancing scientific research (Part 1)

Sponsored Content by Sapio SciencesReviewed by Andrea SalazarAug 12 2024 The substantial volume of data collected and analyzed by modern laboratories - irrespective of their sector - means that effective lab data management has never been so important. In this context, laboratory data management can be understood as the storage and organization of scientific data. Image Credit: Gorodenkoff/Shutterstock.com Inadequate data management processes can lead to siloed data, and even traditional informatics solutions such as Laboratory Information Management System (LIMS) systems (or LIS) and Electronic Lab Notebooks (ELN) can result in data inefficiencies in many scenarios. This article explores the use of on-premise or cloud-based lab data management solutions. It discusses the precise definition of lab data management and why it is so important. It also summarizes the key software functionality required to successfully achieve effective, real-time laboratory data management. Defining lab data management Lab data management methodically handles and organizes the wide range of data generated in a typical laboratory environment. It incorporates automated data collection and storage, validation processes, metadata management, quality control, validation, metrics, and decision-making processes. Any laboratory setting contains diverse data sources, and appropriate laboratory data management and operating procedures are vital in preventing these data sources from being siloed. Siloed systems pose several challenges, such as inefficiencies and issues accessing existing data, inadequate cross-referencing capability across data sources, and disjointed insights where it is impossible to effectively combine data sources. The importance of effective lab data management Effective lab data management in healthcare and life sciences laboratories is especially key because this ensures that critical data collection remains reliable, accurate, and accessible. Integrating a centralized data management system into existing laboratory operations makes data more readily accessible, enabling researchers to retrieve, analyze, and compare relevant data rapidly. By incorporating data from various sources into a centralized data management system, researchers are afforded a more comprehensive and holistic overview of their research projects - a key consideration for any researcher looking to maximize the usefulness of their data. These capabilities continue to expand as AI technology advances, with researchers now able to feed their data into AI tools to reduce the time spent analyzing the data or conducting other routine tasks. Effective laboratory data management improves efficiency and ensures operational scalability. It may even act as a catalyst for innovation and continued scientific development. Leveraging effective lab data management to enhance scientific research outcomes Effective lab data management notably enhances scientific research outcomes because data collection is consistently accurate, reliable, and accessible. Accurate, accessible data allows researchers to effortlessly retrieve, analyze, and compare data as required, driving discovery and improving reproducibility. Integrating data from different sources helps researchers develop a more comprehensive understanding of their research, enabling more profound insights and conclusions with added impact. Centralized data management systems are also key to fostering scientific collaboration, enabling efficient knowledge sharing and streamlined interdisciplinary research. These benefits contribute to scientific advancements. Improving management of laboratory data Lab data collection and management have evolved from traditional paper-based methods to digital systems such as LIMS and ELN. However, the practice of lab data management is still primarily siloed. This siloing of scientific data stems from laboratories working with multiple unintegrated data management systems, such as separate LIMS and ELNs. Scientific information is held across various systems in these laboratories, presenting several issues regarding retrieving and utilizing this data. Siloed systems also pose several problems for users looking to cross-examine their data. A contemporary scientific approach to data system integration is essential for implementing and maintaining an effective laboratory data management system. Sapio Jarvis from Sapio Sciences is a powerful solution that allows users to connect and collect their entire range of data from systems such as ELNs and LIMS into a single platform. Not only does Sapio Jarvis centralize collected data, but it can also automate data parsing, processing, and sending it to experiments and additional workflows using natural language rules. Integrating existing data sources with a robust tool like Sapio Jarvis vastly improves lab data management and further contextualizes research projects. Summary This article examined the importance of lab data management, a concept understood as the systematic storage, analysis, and sharing of a wide range of data generated in a laboratory. By ensuring effective laboratory data management, researchers can be confident that data collection is reliable, accurate, and accessible. This improves laboratory processes and enhances productivity, allowing for more contextualized data analysis. Sapio Jarvis is a code-free data integration solution that empowers laboratories to incorporate unified integration, collaboration, and data management into their operations. The platform seamlessly integrates data from various existing data sources, such as LIMS and ELN software, providing users with comprehensive insight into their scientific data. Read part 2 of Effective lab data management: Advancing scientific research here. About Sapio Sciences Sapio Sciences' mission is to improve lives by accelerating discovery, and because science is complex, Sapio makes technology simple. Sapio is a global business offering an all-in-one science-aware (TM) lab informatics platform combining cloud-based LIMS, ELN, and Jarvis data solutions. Sapio serves some of the largest global and specialist brands, including biopharma, CRO/CDMOs and clinical diagnostic labs across NGS genomic sequencing, bioanalysis, bioprocessing, stability, clinical, histopathology, drug research, and in vivo studies. Customers love Sapio's platform because it is robust, scalable, and with no-code configuration, can quickly adapt to meet unique needs. Sponsored Content Policy: News-Medical.net publishes articles and related content that may be derived from sources where we have existing commercial relationships, provided such content adds value to the core editorial ethos of News-Medical.Net which is to educate and inform site visitors interested in medical research, science, medical devices and treatments.

News-Medical

Mon, 12 Aug, 2:00 PM UTC

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