Clinical trials allow pharmaceutical companies to bring new drugs and therapies to market by testing treatment options on a select group of patients in a controlled setting before they are approved. They are the first phase of a lengthy and expensive process of developing a new drug. The cost of a failed clinical trial ranges anywhere from $800 million to $1.4 billion.

AI Enhances Clinical Trial Enrollment

With a move towards precision medicine, each drug has a smaller target audience from which to recoup R&D costs. Furthermore, both payers and patients are pushing back against rising drug prices. This means pharmaceutical companies will need to find more efficient and cost-effective means discovering, developing and ultimately bringing new drugs to market.

A considerable expense in drug development is the clinical trial process. There is a high failure rate in clinical trials attributed to the difficulty in finding and attracting qualified candidates. Drug companies lose millions of dollars every year from clinical trial patients applying to but failing the screening process (enrollment), or patients participating but for a variety of reasons drop out part way through the trial (retention). Therefore, it is imperative that pharmaceutical companies develop a new effecient, but cost effective means of recruiting clinical trial candidates.

Failed clinical trials are expensive, result in the loss of jobs and hinder research.

As a result of Healthcare’s historically outdated legacy data systems, the pharmaceutical industry has collected enormous amounts of structured and unstructured data in data silos but has until now been unable to effectively drive actionable insights from the disparate data. With advanced storage and machine learning, algorithms, analysis tools, and other technologies now available, pharmaceutical companies can leverage Big Data tools coupled with machine learning tools to develop better enrollment strategies. AI can make the clinical trial process much more efficient and effective.

Artificial Intelligence (AI) has the potential to transform clinical trials and thereby improve the quality and safety of these life-enhancing therapies and accelerate the pace with which they are brought to market. With these advances, pharmaceutical companies will be better positioned to produce better clinical outcomes by identifying more target candidates through prospect matching, improved enrollment, and greater patient retention.

IntelliClinical is a comprehensive cloud-based clinical trial analytics solution that provides faster actionable insight into clinical trial programs to make more – informed business decision and improve your bottom line with timely and fact-based help. IntelliClinical platform adds agility to clinical trial management that lowers risk while improving quality and compliance.

AI Enhances Clinical Trial Enrollment