With an analytical data management system (ADMS) built on the Spectrus Platform, we help gather all your analytical data in one place, including chromatography, MS, NMR, optical, and more. Data from different instrument vendors are standardized into a single format.
Gathering your data in software designed for analytical and chemical data means you will:
- Find data fast—no need to search numerous systems, rely on conversations with colleagues, or re-run experiments
- Share data easily—within your lab/department, or throughout your organization
- Collaborate effectively—with centrally stored data, colleagues in multi-disciplinary teams can access the data they need, when they need it
Live analytical data retains all the attributes scientists need to make decisions quickly and confidently.
You can manipulate and review comprehensive, live analytical data in our environment just like in instrument vendor software. Zoom in, overlay chromatograms and spectra, adjust integrations/baselines, and critically evaluate results from fully interactive data of different types. You can immediately re-process the data in the same application.
Our ADMS not only standardizes your analytical data, it also integrates and stores it with scientific context—structure, meta data, and other chemical information. So, you have all the information you need to make decisions about the identity and purity of structures/mixtures/formulations and to understand materials and processes.
Don’t waste time aggregating and transcribing data from different systems. Search for and visualize all the relevant data together so you can make decisions quickly, and with confidence. Data is searched and queried by chemically relevant criteria and reviewed/reprocessed in the same application, on-demand.
Increase the quality of decisions by making all the information available in real-time.
Our analytical data management system helps you preserve knowledge because the interpretation of data can be included with the spectrum/chromatogram. Subject matter experts (SMEs) can store their observations and conclusions along with the data to provide insights and context for future use.
Comprehensive, multi-technique reports can be generated at the click of a button.
Concerned about Data Integrity?
Manual transcription of data between systems risks the introduction of errors and data integrity.
Eliminate this risk by automating data aggregation. Ensure your data is complete, consistent, and accurate. Preserve data integrity. In addition, establish access and change permissions so only approved users can modify data.
Automation can be as simple as programming your data processing steps, a scripted procedure, or a custom solution for enterprise-wide deployment. Whatever your goal, we work with you to ensure that tedious, repetitive tasks no longer burden scientists.
Routinely automate the following:
- Sweep data from analytical instruments as it’s generated, and deposited to a designated location
- Process and interpret LC/MS, NMR, and other analytical data
- Attach chemical structure(s)
- Create a database record
- Notify scientists for review and revision if necessary
- Report results to the end-user
When routine tasks are automated, you can focus on the complex problems that deserve your expertise.
Example Automated Solutions
Automated Structure Verification (ASV)
- Data is swept from the instrument, processed, and proposed structures are attached.
- Comparison of experimental vs. predicted spectra provides a pass/fail result.
- Ambiguous and Fail samples are flagged for expert review.
- Pass results reported to end-user.
Automated LC/MS Purity
- Data files are automatically read from the instrument and processed.
- The system flags samples with out-of-range impurities for quick expert review.
- Pass results are reported to end-user.
Analytical data prepared and managed in our analytical data management system is both digitalized and standardized, with context. As such, it lends itself to artificial intelligence (AI), machine learning (ML), predictive analytics, and other data science applications.
- Get started with your data science project quickly with normalized, contextual data
- Gain new insights by applying enhanced algorithms or improved visualization techniques
- Drive strategic, data-driven decision-making
