Leading the Way in Effective Drug Development
Medication Adherence Tech and Predictive Analytics Support Patient Retention in Schizophrenia Clinical Trials
The rising prevalence of Central Nervous System (CNS) disorders due to a growing population and aging society has resulted in a major unmet health need. CNS drug development has stagnated in some areas despite concerted effort over the past few decades.
How Predictive Drug Adherence Can Forecast Patient Dropout in Asthma Clinical Trials
Poor medication adherence has a significant impact on the viability of asthma clinical trials. Inhaled corticosteroids, for instance, have an adherence rate of ∼50%, according to a systematic review of 51 observational studies.
Predicting Medication Adherence in Stroke Clinical Trials May Boost Patient Retention
Enrollment recently completed in 20 clinical trials of stroke prevention and recovery therapeutics, according to data and analytics provider GlobalData. As challenging as it is to find participants for these studies, equally important is ensuring that every participant successfully completes the trial as designed.
How AI Can Help Reduce Attrition Rates in Randomized Controlled Trials
Patient attrition can be a major barrier to the successful execution of a randomized controlled trial (RCT). When patients drop out of a trial after enrollment or randomization, not only does it impact the results, but it also introduces delay and higher costs. Today, with the help of artificial intelligence (AI), clinical study managers have access to the data they need to proactively reduce attrition rates in RCTs.
Artificial Intelligence and Machine Learning Accelerate Rapidly in FDA Submissions
People working in clinical trials are sometimes criticized as late adopters of technology. However the reality is more complex. The Gartner 2019 CIO Agenda survey clearly outlined the biggest barriers to adoption of AI and machine learning (ML) as staff skills, understanding benefits and uses of AI/ML technologies, as well as data scope and quality.