The COVID-19 outbreak compelled the life sciences industry to innovate and transform digitally. However, the current global macroeconomic and socio-political uncertainty, coupled with increasing research and development IT expenditure, have created immense pressure on the pharmaceutical industry to expedite the drug discovery and development process while reducing resource consumption. As a result, pharmaceutical companies are prioritizing investments with the potential for quicker return on investment over moonshot investments.
Legacy technologies lack the real-time or data integration capabilities that AI and analytics solutions offer, leading to a lack of visibility for pharmaceutical enterprises into the interplay among stakeholders in the life sciences technology landscape. This has caused pharmaceutical companies to partner with product and IT service providers to improve their in-house talent, reduce time-to-insights, replace obsolete models, and understand fast-evolving customer behavior.
Although AI offers significant benefits, it presents unique challenges such as the availability and quality of training datasets from multiple sources, a demand-supply mismatch for talent with industry and technology expertise, and infrastructure and complex integration issues. Therefore, pharmaceutical companies need to prioritize use cases based on specific market requirements and business needs. In this report, we discuss how a blueprint for success can enable enterprises to maximize the value of their AI-empowered initiatives and investments.
Scope
- Industry: life sciences
- Geography: global
Contents
In this report, we examine:
- The current state of AI in the pharmaceutical industry
- Trends driving the adoption of AI across the pharmaceutical value chain
- Roadblocks and controversies around AI in the pharmaceutical industry
- Prominent AI use cases across the pharmaceutical value chain
- Sourcing considerations for AI solutions and suppliers
Membership(s)
Life Sciences Information Technology
Sourcing and Vendor Management
