All Whitepapers

What if you could predict potential safety issues before clinical development begins? Innovative new signal detection and management approaches have been developed to help clinical trial sponsors, manufacturers, and CROs combat safety-related challenges and provide insight to be used to predict potential safety issues even before clinical development begins. Applying those learnings to their choice of initial research candidates can ultimately mean safer medicines for patients.

With the increasing volumes of adverse event reports and stagnant budgets, the time is now for a revolutionary change in drug and device safety case management. A robust management process is necessary for identifying and evaluating adverse events (AE) and reporting them properly to regulators.

Pharmaceutical sales operations teams often rely on outdated or inaccurate data when prioritizing HCP targets, limiting promotional effectiveness. By applying artificial intelligence and machine learning to real world data, pharmaceutical companies can more effectively target physicians hiding in plain sight and PCPs behaving like specialists.

Specialty and rare diseases have undefined patient populations with patients who are undiagnosed or misdiagnosed, healthcare providers who are unaware of disease states and their manifestations, as well as diagnostic and treatment journeys that are not well-understood. By applying artificial intelligence and machine learning to real world data, pharmaceutical companies can improve outcomes at scale.

The Pharmaceutical Executive® APEX Awards feature some of today’s best creative work in the pharmaceutical industry. Come and see how you did, along with other agencies, at our live virtual event on September 9.

This whitepaper looks at the requirements for High Throughput Screening, High Content Screening and Surface Plasmon Resonance and makes suggestions for how to make these processes more flexible and repeatable.