Pharmaceutical companies face increasing pricing pressure on new medicines, and many have turned to automation to shorten product development timelines, facilitate compliance and reduce costs. By automating repetitive manual tasks, such as..
We are in the Age of Information. The recent exponential increase in computational power now enables data-driven decisions across organizations, streamlining workflows and improving efficiency. Therefore, many companies are searching for the best..
In preclinical drug development, in vivo studies are a mandatory step in the process of turning lead compounds into drug candidates. Regulatory agencies require in vivo safety and efficacy data from animal models before approving novel candidates..
The Fourth Industrial Revolution or Industry 4.0 is characterized by a fusion of the digital, biological, and physical worlds. The main feature of this revolution has been an increased incorporation of new technologies featuring lab digitization and..
Current Good Manufacturing Practice (cGMP) regulations require that companies maintain minimum standards for processes, equipment, facilities and quality management systems. However, it can be challenging to accurately record and track various data..
The COVID-19 pandemic has highlighted the importance of pharmaceutical R&D. Billions of people around the world are pinning their hopes on a new COVID-19 vaccine to end the exponential infections, death rates and social restrictions. The..
We all expect that the medicine we receive is safe and effective. For pharmaceutical products to meet these requirements, regulatory authorities, such as the European Medicines Agency (EMA) or the U.S. Food and Drug Administration (FDA), ensure..
Drug discovery and development lead to new treatments for diseases. However, it is a costly, time-consuming and challenging process—developing a marketable drug can take more than 10 years and cost around a billion dollars. One of the reasons for..
With cloud technology, pharma companies can leverage big data, automation and advanced analytics to create nimble, collaborative processes. In a recent interactive roundtable, experts from Bayer, Cytiva and LabTwin discussed how cloud..
In recent years, the reproducibility of scientific research has come under the spotlight. A major barrier to clinical development is the inability of translational scientists to replicate early discovery findings. In 2016, Nature surveyed nearly..
Data integrity is not a new problem and continues to be the major focus in regulated cGMP laboratories worldwide due to data falsification, poor data management practices, or ignorance of the regulations. Several regulatory agencies such as the..
When the human genome was sequenced in 2003, it became possible to identify the gene and protein changes that occur in various diseases, such as cancer. Ever since, the field of proteomics has been booming to respond to the ever-increasing..
Steve Jobs famously said of his customers, “Our job is to figure out what they're going to want before they do.” This user-centered design approach saw Apple grow into a household name, and today there are 1.4 billion active Apple devices around the..
Research scientists spend 50-80% of their time at the bench with no easy way to record data or access information. New voice-powered digital tools solve this problem by connecting scientists with information at the point of experimentation.
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KEY TAKEAWAYS - Digitization, the process of turning paper-based information into a digital format, makes research more efficient and reproducible, saving time and money. In the U.S. alone, over $28B are lost annually on research that is not..
Like other industries, biopharma is grappling with an enormous explosion of data and is turning to artificial intelligence (AI) to make sense of what the data reveal. AI allows scientists to review data efficiently and accurately, uncover patterns,..
