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.

Continued Process Verification (CPV), Process Analytical Technology (PAT) and Quality by Design (QbD), are driving pharma to improve product and process quality and efficiency.

A biopharma company’s experimental records, recipes and scientific results were stored in multiple Excel files, scanned PDF documents and siloed lab solutions, many of which did not use the same conventions from lab to lab or scientist to scientist. disconnects were leading to additional lab work at late stages, workflow inefficiencies, long review times, delayed decisions, excessive effort and wasted material. They needed to implement a common solution across all CMC labs and for all therapeutic modalities—both small molecules and biologics.

Inefficient lab workflows and poor visibility across research data was threatening to jeopardize clinical programs, from discovery to registration and beyond for a biotechnology company. They needed to replace their legacy, paper-based processes with an entirely digitalized lab environment that supported the innovation lifecycle from target identification to compound discovery and process development.

A biopharma company that supports drug discovery activities had been using a legacy plug-in to Microsoft® Excel® spreadsheet software for performing scientific data aggregation, analysis and presentation. While the legacy spreadsheet tool was flexible, it was also slow. With the amount of data growing year after year, scientists had come to accept the inevitability of some queries taking up to 3 hours to process. By implementing a faster, more purpose-built tool running BIOVIA Pipeline Pilot protocols in Microsoft Excel spreadsheets the company has much more than simple spreadsheet capabilities.

With nearly 2,000 scientists and twice as many instruments spread across multiple global locations, the customer was managing eight different electronic notebook (ELN) systems and Laboratory Information Management Systems (LIMS). The customer’s challenge was to unify data collection and management across the different phases of early discovery, R&D, and clinical and commercial manufacturing. By implementing a comprehensive agile framework, the customer and BIOVIA were able to release 3 major and 2 intermediate software iterations within 12 months.

Electronic Lab Notebooks are a key component of an electronic lab environment that helps scientists execute faster, more informed, high-quality science. It’s a vision scientists have talked about for decades.

With cloud adoption significantly enhancing collaborative projects, increasing operational agility and lowering total cost of ownership (TCO), cloud computing has become a valuable and viable solution today; however, organizations are often uncertain about the best way to evaluate, select and implement a cloud collaboration platform. This paper will discuss the challenges of internal and external collaboration and how scientific research organizations can manage the transition to a more highly performant, flexible and agile partner workspace in the cloud with the help of a qualified cloud provider.

As this next wave of antibody-based therapies gains momentum, biochemists have begun to create even more innovative molecules with additional modes of action including multispecific antibodies and other so-called Frankenmolecules. However, informatics technologies have not kept pace with these scientific innovations. It’s unlikely that any single life science company, technology vendor or academic group will be able to solve these issues unaided. But together we can establish systems and processes that make working with these new entities more efficient.

With many biotherapeutics a strong immunogenic response can limit the effectiveness of the treatment or cause a more serious illness. This remains a challenge for scientists as the underlying mechanisms of unwanted immunogenicity still aren’t completely understood. Detecting and preventing unwanted sources of immunogenicity as early in the discovery process as possible has become a top priority for research organizations since biotherapeutic development becomes increasingly costly as it moves downstream.

Identification of Medicinal Products (IDMP) is an international pharmacovigilance and patient safety initiative addressing this need for global identification of regulated pharmaceutical products during their lifecycle. IDMP is an opportunity for pharmaceutical companies to transform the way in which the continuity of digital information is leveraged and presented to provide a complete definition of the medicinal product, bringing immense business benefits and competitive advantage.

The costly proliferation of parts and components that often accompanies the pressure for product differentiation and customization can be controlled through multiple strategies. One of the easiest and most effective of these is to deploy EXALEAD Sourcing & Standardization Intelligence. By combining information sources with semantic information, these new products and applications go beyond the limits of conventional analytics solutions and deliver simple user experiences for decision makers.

Working in a cloud-based information management and collaboration workspace provides a level of business agility and security that is not available with server-based, on-premises infrastructure.

Once primarily considered a focus in downstream drug development and manufacturing, quality now demands just as much attention in upstream discovery research.

“Digital transformation” is a common buzzword across industries today, but is it more than just jargon?  Faced by shifting consumer demand, rapidly evolving technology and increasing competition, organizations — to a large extent from science-based industries — are realizing that business as usual (or only incremental change to traditional approaches) does not address today’s challenges in a sustainable, long-term way.

Reacting to trends, including drug shortages and plant inspections that increasingly question manufacturing data integrity, FDA’s recent draft guidance Request for Quality Metrics promotes a “quality-driven corporate culture” as one of its goals.