Detecting drug-induced liver injury with JMP Clinical 4.1
In my previous post, I highlighted several of the new features in our latest JMP Clinical release for clinical findings analysis (with a little help from Dr. Seuss). I didn’t use one of my favorite quotes from Oh the Places You’ll Go; so just to get it out of my system, here you go!
“And will you succeed? Yes! You will, indeed! (98 and ¾ percent guaranteed.)”
I must say Dr. Seuss lived in an optimistic world. If only we could have such high probability of success in clinical trials! So often, clinical trials end in failure, with safety and efficacy being the top offenders. Worse is when a drug has to be withdrawn from the market due to safety-related issues. The leading cause of withdrawal continues to be drug-induced liver injury (DILI), largely because of the complexity of detection and diagnosis and the rare occurrence (as little as 1/10,000) of such events.
While true DILI is often not observed until post-market, you can (and should) assess safety signals for potential hepatoxicity concerns. Hy Zimmerman has become famous for coining a set of rules (Hy’s Law) based on time-relevant liver laboratory measurements tied with the comprehensive patient profile to enable early detection of potentially fatal (10-50% mortality) hepatocellular injury and liver damage (Zimmerman 1978,1999). The Hy’s Law Screening process in JMP Clinical has become a state-of-the-art tool just for this purpose, especially with the many new features in our latest release.
The analyses, based heavily on the FDA DILI Guidance and domain experts, highlight the JMP Clinical mantra to flag interesting/potential signals through analytically driven visualization and drill-down into comprehensive patient profiles/narratives and cross-domain safety information.
New tools that enhance the algorithms to flag potential Hy’s Law cases include a simplified screening plot of Total Bilirubin and Alanine Aminotransferase (mimicking the FDA eDISH tool), histogram distributions of liver tests and demography, interactive tables that are a standard in medical review, and liver test peaks plotted against Study Day. With new drill-down options to plot exposure-annotated time course profiles and liver laboratory shift plots and tables, it is now easier than ever to apply a standardized workflow to detect potential DILI:
Visualize peak liver lab values for all patients, flagged by time-relevant algorithm to detect Hy’s Law relevant cases.
Evaluate differences in incidence of transaminase tests between treatment arms.
Report tables of flagged counts and severity of liver elevations.
Drill down to individual time course and shift plots.
Drill down to comprehensive patient profiles, medical history, narratives and further cross-domain clustering and data trends.
See screenshots below of some of these new features in JMP Clinical 4.1.