Developing the proper formulation of active ingredients (APIs) and excipients is almost as important in designing a new therapeutic as the APIs themselves. Sanofi’s challenge was removing the formulations bottleneck in its pharmaceutical development workflow by improving its autoxidation risk assessments of potential formulations. By implementing BIOVIA Materials Studio they were able to removed the need for “trial-and-error” driven experiments and maximized the value of scientists’ time.

Data gathering was very cumbersome for an emerging specialty pharmaceutical company, as data resided in paper-based documents, spreadsheets and complex equipment systems. Manually aggregated data sets represented only 15% of the total parameters their teams measured and the model could only explain 59% of the results. These gaps were what drove them to look for a solution that could accelerate data aggregation, modeling and prediction.

Following several mergers and acquisitions, a biopharmaceutical company had to manage an increasing amount of data from disparate online and offline sources.  As these data spanned long timeframes, it was very resource-intensive (time, people, money) to establish the relevant time window.  A solution that allowed them to to access data from online and offline sources and to feed other systems with data and quickly became their analytics tool for extracting and contextualizing data in support of the company’s digital science and manufacturing informatics strategies.

Meta Biomed's scientists ran hundreds of experiments, but they lacked a clearly defined way of sharing information and knowledge between individuals and teams. They also wanted to centralize their product development data and achieve a more structured way of working to boost innovation, embed quality throughout the supply chain and accelerate product certifications—especially as they sought to become a leading supplier of surgical sutures in the global market. A single, centralized database solution now allows them to hold all of their product development data.

A leading biotechnology company's existing CISPro system did not include freezer inventory management for use by their process development team. By implementing the BIOVIA CISPro they can manage all the chemicals and materials across their facilities at the container level, keep track of where they are in real-time and monitor usage.

Chemical inventory management processes that have not been optimized with technology and best practices can negatively affect operational effectiveness and efficiency. A real-time chemical inventory management system increases the organization’s efficiency and productivity by: consolidating the resources needed for inventory reporting, MSDS management and inventory management; reducing chemical purchase, storage and disposal costs; and, most importantly, providing greater operational efficiency in the laboratory.

Laboratory organizations need an environment that facilitates and optimizes collaboration, experiment execution, documentation and data management in the different labs from R&D through manufacturing to commercialization. By implementing a digital lab solution you can bridge the innovation and productivity gaps in research, development, manufacturing and quality, and enable successful technology transfer across new product development and production operations.

Many research organizations are facing a maelstrom of increasing regulation concerning on-site chemicals and an ever-growing volume of chemical-related data to manage and report. Chemical inventory management can be time-consuming; it can hamper workflows; and – worst of all – it can trigger numerous non-compliance determinations. This guide presents a best practices solution to this dilemma; e.g., how to compare and select a digital chemical inventory management system that streamlines workflows  throughout the organization and brings chemical inventory under control.

Over the last few decades, replacement of outdated paper-based data management systems has been identified as a means to accelerate this process. While the implementation of electronic systems led to reduced cycle times and compliance risk, issues remain with systems existing in departmental silos and non-standardization of data across the drug development continuum. To satisfy the requirement of drug development companies for efficient data and technology transfer, standardization of data and technology transfer across the entire pharmaceutical product lifecycle is needed.

When federal, state and local safety regulations regulations concern chemicals, it is vital that the organization deploy efficient processes and systems that enable laboratory and Environmental, Health and Safety (EHS) personnel to easily comply with the regulations, ensure safe chemical management and produce accurate chemical inventory reports. This white paper discusses the obstacles organizations face ensuring chemical compliance and how different organizations have solved the compliance challenge.

When it comes to drug discovery and development, employing these technologies has become an existential challenge for the pharmaceutical industry. So how can these technologies help the pharmaceutical companies reduce the staggering expense and amount of time it takes to develop new therapeutics, getting there sooner, with less compounds needing to be tested and proved? AI & Machine Learning (ML) are deployed to explore potential drug candidates faster, able to meet a particular target product profile.

Enhancing project management with analytics creates project intelligence, shifting a task-based activity to a performance-driven one. This article discusses the importance of using actionable insights within pharmaceutical and biotech industries and the benefits that they provide.

Larger pharma organization have evolved into hierarchical silos due to a combination of legacy organizational structures, mergers and acquisitions, and lack of a holisitic approach to innovation.

One tool holds a unique position among R&D informatics systems -- electronic laboratory notebooks (ELNs). ELNs both produce data and consume information and are particularly powerful.

Explore best practices in SaaS selection and how its incorporation into laboratory practices enable organizations to focus on core competencies while utilizing best-of-breed software.