Pharma data practices have evolved with the times. Today, approaches such as AI and machine learning afford the opportunity to enhance drug development and safety, culminating in AI-driven insights that promise better patient outcomes.

‘Smart labs’ is a term that is incredibly prevalent in the world of pharma data management. But what are the building blocks of these laboratories that are proving ever-more important in modern research?

Recent developments in healthcare include the integration of AI chatbots in order to support primary care providers, offering improved patient care and efficiency in providing healthcare solutions.

Pharma data company Array Insights has launched a cutting-edge data federation platform to enable patient-focused organisations to securely access and share patient data for collaborative healthcare research while prioritising patient privacy.

FAIR data principles aim to standardise and enhance the management of scientific data through unique identifiers and standardised protocols. The gradual implementation of these principles can improve research efficiency, facilitating better data utilisation by both humans and machines.

Key opinion leaders discuss how to approach challenges and opportunities which arise when looking to optimise lab processes.

Looking to the next few years of data management in clinical trials, hybrid models which interpolate AI and ML approaches to assist trial coordinators will increasingly become the new normal.

AI startup raises funds to advance commercialisation of groundbreaking biological intelligence operating system.

How can you overcome challenges and unleash the potential of Real-World Evidence for impactful healthcare insights?

As the capacities of multi-omics integration continue to grow, key opinion leaders discuss the main setbacks and outlooks for the field.