Clinical development
1.
The seven to scale
Essential digital programs that create meaningful value
Data-optimized clinical
trial design
Digital health-enabled
trial execution
2.
Supply chain and manufacturing
AI-driven yield optimization
3.
Data-driven scrap reduction
4.
AI-optimized planning and scheduling
5.
Commercial engagement
Digital and field orchestration and precision engagement
6.
Hyper-personalized
content marketing
7.
Digital foundation
Modern technology | Connected data ecosystem | Intelligent analytics Operating model | Digital talent and upskilling
See definitions
See definitions
See definitions
Clinical development
Back
Data-optimized clinical trial design involves using AI and analytics to optimize various aspects of the trial to accelerate development, such as recommending the removal of visits and assessments; evaluating study criteria versus RWD; and selecting countries, sites and investigators based on opportunity. It also aims to improve the overall patient and site experience and reduce patient drop-off as part of the design by minimizing burden and complexity and connecting stakeholder experience to trial speed and quality.
Digital health-enabled trial execution involves running clinical trials using digital health tools, decentralized methods and remote data collection. When used in combination, these digitally enabled approaches can reduce study completion times, improve and diversify patient recruitment and retention and reduce implementation costs.
Supply chain and manufacturing
AI-driven yield optimization uses AI and machine learning analysis to optimize processes and parameters that increase yields across manufacturing plants.
Data-driven scrap reduction reduces unplanned scrap of raw materials and finished goods that can be avoided through data-driven analyses.
AI-optimized planning and scheduling improves manufacturing production scheduling to increase overall run rates and open manufacturing capacity.
Commercial engagement
Digital and field orchestration and precision engagement involves shifting to an omnichannel model for field and marketing. In this model, field and marketing teams interact with healthcare providers (HCPs) and integrated delivery networks based on omnichannel orchestration and dynamic targeting algorithms. This engagement drives metrics for improved customer experiences, better access to those customers and, ultimately, product revenue increases.
Hyper-personalized content marketing uses AI to support the creation optimization and assembly of hyper-personalized content for the individualized preferences of HCPs and patients, thereby increasing relevance of pharma engagement with their customers and driving toward greater impact.
Back
Back
