For over a decade, fewer than 10% of clinical trials that enter Phase I achieve FDA approval. Too many new drug submissions receive a rejection letter, request for further analysis, or label restriction, significantly delaying market entry, impacting patients and shareholder value.
Often, these issues are not about the efficacy of the treatments or devices but the quality of the clinical data. Medidata offers a new way to preempt submission of data errors, by using machine learning algorithms, put in the hands of Medidata’s team of former FDA statisticians.
Medidata Edge Trial Assurance, already used in over 30 trials, has consistently detected 50-75 data anomalies per study by:
Utilizing Artificial Intelligence (AI) to detect data entry errors, outliers, potential fraud or misconduct and misreported adverse events from sites
Delivering a turn-key, comprehensive report of the results by a team of clinical analysts led by former FDA statistical reviewers
Enabling the study team to proactively correct data issues before regulatory submission
Medidata’s AI capabilities have received industry recognition. Recently, Medidata’s risk-based monitoring solution Edge Strategic Monitoring earned a prestigious CARE Award for being the first and only end-to-end solution that combines the same advanced anomaly detection in Edge Trial Assurance with centralized issue management.
Medidata co-founder and president Glen de Vries said: “The outcome of a regulatory submission has a profound impact, not only to the business but also for patients in need.
“Medidata’s advanced machine learning capabilities and former FDA expertise empower organizations to confidently manage regulatory submissions and significantly reduce risk.”
Source: Company Press Release.