Study Start-Up

Emerging applications of AI/ML, automation, and digitization are helping sponsors cut clinical trial start-up times to as little as four weeks, reduce data errors, and enhance patient engagement—demonstrating how tech-enabled processes are reshaping trial efficiency and experience across the study lifecycle.

Overcoming the illusion of knowledge in clinical research can enhance decision-making, training, and project success—helping ensure trials run smoothly and effectively.

It takes a village to raise a trial, but most stakeholders are siloed on isolated islands.

The activation of each clinical trial involves hundreds of tasks, along with many dependencies and handoffs, some of which may be automated, but many require manual processes.

Amplifying the size and diversity of participant pools in clinical trials enhances statistical power and increases the generalizability of study findings.

Optimizing feasibility through increased data collection.

Similar to a world-class symphony, a curated site start-up model can accentuate its individual components and lead to swift starts for clinical trials.

Sujay Jadhav, global vice president, study start-up, Oracle Health Sciences, spoke with ACT on how study start-up has been impacted by the pandemic and what its future holds beyond COVID.

With a major wave of post-COVID trial starts on the horizon, the industry’s need to accelerate clinical research through study start-up is intensifying.

Why? Because more often than not, you do not want to accrue only one participant to a clinical trial.

Despite the substantial difficulties associated with orphan drug trial recruitment, this segment of the drug development market is booming.