Traditionally, safety related meta-analyses have been costly, taken significant time to produce and can often miss relevant studies. Further, there has been no efficient way to test the outcome of those studies prior to initiation. This has led to a lot of unnecessarily wasted resources.
Luckily, Advera Health with the help of machine learning, artificial intelligence, and data science is solving this problem for drug safety, epidemiology, and medical affairs departments of all sizes.
Last week we announced the launch of Clinical Meta-Analysis in Evidex capability and we have provided a walkthrough with screen shots is below. This new analytical tool provides the capability to perform meta-analyses of safety issues using a cloud-based software-as-a-service platform.
Powered by the Advera Clinical Evidence Database containing the safety results of 14,000+ clinical trials, the new analytic creates on-demand meta-analyses to determine AE rates across any combination of drugs, classes, or indications.
This allows users to:
- Characterize and determine expectedness of adverse events
- Better understand the safety market landscape
- Quickly hypothesize potential safety differentiators
In addition to "simply" replicating meta-analysis studies, signal detection, validation, and assessment procedures become more efficient by combining the outputs with data from spontaneous reporting databases like the FDA Adverse Event Reporting System (FAERS), the Uppsala Monitoring Centre's VigiBase, or a client's internal global safety database in a single platform. This further frees up time and resources for insight driven pharmacovigilance analytics.
In order to showcase the capabilities, let's walk through as simple example of finding a benchmark rate of ketoacidosis in type 2 diabetes patients taking a SGLT-2 inhibitor. First, let's bring up Clinical Meta-Analysis tool in Evidex and make our first selection. Here you can see we can start with any drug, class, indication, or mechanism of action.
And then we can add MedDRA preferred terms (PTs), standardized medical queries (SMQs) or SOCs. I've used 'AND' Boolean connectors in this simple search, but I could also utilize 'OR' and 'NOT' strings as well.
Also, in this case I'm not choosing a specific drug to compare the SGLT-2s with, but I also have that option. After running my search (which takes only a few seconds), I can see my results. Across all of the SGLT-2's there have been 13 cases of serious ketoacidosis in clinical trials for type 2 diabetes patients, providing for a pooled rate of 0.0290%, which is in line with comparator arms at 0.0244%.
I can then compare all of the drugs in the SGLT-2 class.
And then look at all the individual trials that have contributed to the meta-analysis.
From here I can click on any of the individual trials to get more details.
And then further explore how the outputs from the Clinical Meta-Analysis compare with other datasets for a specific drug-event combination (DEC), further stratify the data with custom groupings and visualizations, and see if the DEC is being tracked in my organizations signal management process.
We are very excited about the launch of Clinical Meta-Analysis in Evidex and I hope you are too after reading this blog post. Click the button below to watch an overview video or to request a demonstration.