A new report by MIT Technology Review Insights, named, “Transforming R&D: Digital innovation in the pharmaceuticals and chemicals industries,” has recently been published, which gives the readers an insight into how quantum computing, machine learning, artificial intelligence, and other digital technologies are transforming R&D and scientific innovations in the pharmaceuticals and chemicals industries.
MIT Technology Review Insights, in association with PerkinElmer Informatics, interviewed R&D executives at various organizations including Roche, Novartis, BASF, Merck and Syngenta, to find out the best practices, use cases, and plan-of-action for digitalization of science.
The findings of the report have been summarized below.
Digital technologies are helping researchers analyze complex data for precision medicine
Till now, generalized medicines were used to treat patients, based on their symptoms. It was a trial-and-error based approach and often not very reliable. Using data and machine learning, the researchers are trying to bring personalization in treatment of diseases. By developing robust metadata, focusing on FAIR(findable, accessible, interoperable, and reusable) data principles, governance protocols, and using advanced analytics and data visualization tools, researchers are exploring patterns and trends in gigantic amounts of complex data.
This will provide them opportunities for decentralized clinical trials, and ability to predict with precision which medicines will work the best in different groups of people. It will also enable the researchers to predict which diseases are likely to occur in a person and the ways to prevent them.
Digital technologies are helping researchers avoid wastage of time, efforts, and money
Experiments and clinical trials require lots of investment in terms of time, money, human, and scientific resources. Using AI-based analytics, advanced simulation, modeling and quantum computing, the strongest candidates for new therapies, products, or materials are identified, allowing only the ones with the best possibilities to move to the costly experimental phase.
As per Kevin Willoe, VP and GM of PerkinElmer Informatics, the Digitalization of scientific research and data management has created exciting opportunities for organizations to leverage information in new ways for improving scientific discovery and product development.
A boon or a threat?
The growth of AI and automation is often seen as a threat to the role of humans in Research and Development. However, the opposite is becoming true. Ways of working in scientific research are undergoing a huge transformation, thanks to AI and digitalization. These technologies are providing new opportunities for collaboration in the pharmaceuticals and chemicals industry and extending the resources and capabilities of the researchers in pursuit of better and cost-effective outcomes.
