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Although there are much larger problems in clinical research, storing obsolete study records is a totally unnecessary cost.

Industry leaders discuss how technology can help companies adapt to the regulatory changes and accomplish their DE&I goals.

Exploring ways to boost the adoption of eCOA provider-specific libraries—an often-frustrating migration process, but one with significant payoffs in simplified workflows and reduced timelines.

The FDA has taken a clear position with Project Optimus in shifting toward more progressive tailored approaches while rejecting antiquated study designs to evolve clinical trial strategies to better align with newer drug classes.

Webcasts
Webinar Date/Time: Tue, Mar 26, 2024 11:00 AM EDT

Agency reports concerns amid an increase in submitted data that has been fabricated, duplicated, or unreliable from third-party laboratories.

Many companies have implemented new technologies and are adopting clinical trial models that are more patient-centric.

Webcasts
Webinar Date/Time: Thursday, March 14th, 2024 at 11am EDT | 8am PDT | 3pm GMT | 4pm CET

Webcasts
Webinar Date/Time: Tuesday, March 12th, 2024 at 12pm EDT | 9am PDT | 4pm GMT | 5pm CET

Breakout session at SCOPE Summit 2024 discusses the potential use of artificial intelligence to improve clinical trial strategy generation.

Addressing challenges with eCOA at the site-level.

Webcasts
Webinar Date/Time: Wed, Mar 27, 2024 11:00 AM EDT

Leveraging a “diversity by design” approach can build patient narratives and optimize protocols from the onset.

Recent study tests the ability of machine learning to effectively classify patient safety event reports.

The pursuit of balance between data utility, privacy protection, and equitable representation.

By promoting the use of a standardized terminology and coding system, IDMP eliminates inconsistencies in regulatory processes.

Testing in humans in clinical trials and the regulatory approval process itself are candidates for technology solutions where artificial intelligence is playing a role.

Natural language processing models are able to automate the extraction of pertinent information from a vast array of scientific literature.

New machine learning technology combines artificial intelligence with automated experiments.

Because artificial intelligence use in healthcare is powered by patient data, it is imperative to guard privacy by verifying that security measures are in place to protect against any data breaches.

Scaling seven common digital programs inside a typical top 10 pharma company could be worth $1.4 billion to $2.2 billion in operating income over five years.

Robust data sets which can effectively represent diverse populations are key to driving greater inclusivity in trials.

Study highlights efficacy of effectively monitoring attention-deficit hyperactivity disorder treatment effects with Qbtest.

DCTs, data, and analytics are all areas that could be impacted in the near future.

Effects of newly implemented NIH policy on data sharing could be profound for clinical research.














