Goto

Collaborating Authors

 pharmaceutical manufacturing


Bringing digital twins to boost pharmaceutical manufacturing

#artificialintelligence

Pharmaceutical manufacturers are increasingly interested in the tenets of Industry 4.0, including the use of digital twins to simulate, test and optimize manufacturing processes on a computer before using them in production, according to technology advisory firm ABI Research. It projects spending by pharmaceutical manufacturers on data analytics tools--including the digital twin -- to grow by 27% over the next seven years, to reach $1.2 billion in 2030. As with other manufacturers, pharmaceutical makers plan to use the digital tools to boost productivity and to track their operations. Toronto-based Basetwo recently moved into this market with its software-as-a-service (SaaS) artificial intelligence (AI) platform. Today, the year-old company announced an upcoming $3.8 million seed financing round led by Glasswing Ventures and Argon Ventures.


Connected lab: what RPA can do for biopharmaceuticals

#artificialintelligence

The development stage can be one of the most expensive and critical in the life sciences value chain, and is often bogged down in an oversight process that is highly manual and paper based. A clinical-stage study costs an average of $1.1 billion over 6.6 years, according to EY, and so any potential for increasing speed and efficiency in biopharmaceuticals development can have a dramatic impact on the bottom line. Luckily, we're now in the era of the smart connected lab, with robotic process automation (RPA) software deployed to transform the very nature of clinical development. James Ewing, UK regional director of Digital Workforce, says automation is changing pharmaceutical manufacturing in three key ways: streamlining operations through automating high-volume, low-value repetitive tasks, such as comparing datasets; helping researchers increase accuracy when dealing with large quantities of data; and cutting down the administrative tasks associated with regulation. "Given that biopharma research is a heavily regulated industry, there is a large amount of internal documentation which needs to be updated and submitted to external parties. This compliance paperwork process is time consuming, but can be easily automated using RPA," he says.