The non-clinical (or pre-clinical) development phase primarily aims to identify which candidate therapy has the greatest probability of success, assess its safety, and build solid scientific foundations before it comes to testing humans. The non-clinical development process starts in parallel with research activities, and non-clinical testing is conducted throughout all phases of drug development to assess the safety profile and pharmacokinetic and toxicokinetic characteristics of drug candidates. Optimized non-clinical development is an important success factor for later clinical development. Data analysts, project and vendor managers, and report writers need to stay on top of all documentation along the process and need to deliver in later phases and into the eTMF for further reference.
The last few years have seen tremendous consolidation in both the pharmaceutical and contract research industries. The impact among pharma companies has created a heightened demand for productivity. Properly designed CRO Collaboration opens capabilities in various functions like the following:
When researchers start to collaborate over distances with imaging centers, using diagnostic services over internet connections the bandwidth and computation power easily exceeds the capabilities in remote areas.
Life science organizations developing or manufacturing pharmaceutical products will typically create, maintain and execute large amounts of standard operational procedures (SOP). The solid change control and deployment of SOPs are a fundamental to achieve compliance excellence.
Properly designed Standard Operating Procedures include step-by-step instructions as well as the following:
Comprehensive Imaging Science solution for research and production imaging processes. Process support that covers the whole workflow from imaging to conclusions. Improve and integrate image production, data ingestion/archiving, storage, access, analysis strategy, QA/QC, computation at scale, review of results, and implementation of custom algorithms and AI.
Quality Management System with features to secure and control data & documents. Collaborative platform for regulated content, processes and end-to-end compliance along the complete life sciences life cycle. Powerful and intuitive navigation, enhanced user experience, dynamic content management and search features. Connecting quality teams globally.
Trial Master File solution to securely review and audit TMF documentation. Digital process support with form-based workflow for the complete (pre-) clinical document processes. Visualize real-time completeness based on study, country and site indicators. Apply filters and different dimensions, view metadata to intuitively navigate through complex eTMF filings
Document and project management solution for life science. Tools for operations and oversight teams to prepare and review documents and records for the completion and successful submissions and correspondence. User centric collaboration, automation and quality workflows featuring the life cycle of documents and dossiers from authoring to (re-) submission.
arivis BM-Watcher is a 21 CFR Part 11 raw data management solution for the pharmaceutical industry. It integrates with nearly all types of laboratory instruments. It is able to provide data integrity features even for legacy systems. arivis BM-Watcher is an agent that is able to monitor the file storage of a laboratory device.
Complete document management, training management, CAPA, deviations, change control - all in one tool.
arivis BM-Watcher is a 21 CFR Part 11 raw data management solution for the pharmaceutical industry. It integrates with nearly all types of laboratory instruments. It is able to provide data integrity features even for legacy systems.
Modular software toolkit for extracting results from scientific images. Adjusts to hardware for maximum power and smooth interactivity on image datasets of unlimited size. Brings diverse tools into one environment and enables users to connect them into productive workflows. Highly interactive for optimization and quality at every step. Extendible directly via Python and connectable to other applications via libraries.
Display real image data in Virtual Reality by utilizing patent pending direct volume rendering techniques with no need to convert data or make surface models. Directly use your hands to move, rotate, scale, and shape your digital image data. Interactively proofread, edit, track or segment multi-dimensional images from nearly any source instrument.
A nucleus of computational activity and collaboration at scale. VisionHub enables design and execution of large-scale experiments that produce results from images, whether datasets are already stored or are actively being produced. Mass quantities of Imagery are onboarded and processed by a virtual team of computational workers. Smartly utilize processing cores in servers or workstations with the maximum speeds possible.