Accelerating Clinical Trial Success

Have you ever had to find a clinical trial for a loved one? Do your friends outside of the life science sector know the process for receiving a drug approval? If you answered "yes" to the first question then you realize how difficult it is to find the right trial. As for the second scenario, it has afforded me the opportunity to be: 1) quite boring at parties, and 2) leave my neighbors with more questions than answers. How can we make the process better?

Today’s patient recruitment process is outdated. The promotion methods of clinical trials are archaic to say the least. Perhaps a flyer at an investigator’s office or an ad (print or online) directed at the intended demographic. Social Media has helped with the recruitment process, but it is still a non-personalized approach. These unsophisticated methods hope to attract a patient that meets the initial study criteria and is willing to participate. In business development we call it "spray and pray". An unflattering way of defining an approach that was effective thirty years ago. For advanced as our industry is with regard to discovering and developing new therapies, we are reluctant to adapt new procedures related to clinical operations.

I blogged in August that according to a study published by Bio in May 2016 (Clinical Development Success Rates 2005-2016) only 10% of eligible products in Phase 1 trials will receive FDA approval. The study covered 14 disease areas and the likelihood of approval (LOA) varies depending upon the disease state. This success rate is not very good when the improved quality of a loved one's life is the goal.

The objective of that article was to raise awareness of the technological advancements used to improve the success of clinical trials. Using AI and Machine Learning to mine large data sets of eligible patients will significantly improve the chances of recruiting the right patient at the right site for the right trial. One company successfully contributing to this advancement is TriNetX (www.trinetx.com). Their easy to use platform and deep database of 84 million patients allows for real-time modeling of protocol feasibility. In addition, their platform performs predictive analytics to project rates at which new patients will match certain criteria. Two very important steps to obtaining successful trial results. As technology and data continue to come together in platforms like TriNetX, the predictive model will transition to a prescriptive model contributing to even greater clinical trial success in the near future.

Designing an effective protocol that results in a successful trial and FDA approval is just the beginning. Post-marketing surveillance has intensified as payers (private and government) demand real world evidence (RWE) to support formulary and pricing requests throughout the patent life of the product. A trial that utilized the correct patient population will improve the chances of collecting RWE post-approval that further substantiates the product's efficacy.

The technology is available now to improve the lives of many. Let’s hope we are quick to adapt and not be laggards.  

Please feel free to connect with me if Public Health Policy is of interest to you. I am always willing to engage in a discussion of how to favorably impact society with technological advancements.