Product liability insurers protect pharmaceutical companies from legal actions associated with their drugs. They have a significant economic incentive to scientifically assess and understand the scope of litigation risk. Experienced underwriters use an evidence aggregation platform to better understand if a manufacturer’s drug is causing severe side effects that could lead to potential litigation. They also use an evidence aggregation platform to adopt and employ a simplified and unified process of assessing side effect risk with proven statistical measures via a simple interface that deploys in minutes.
Managed Care Organizations are reviewing drugs well before a product is approved. According to a survey conducted by Dymaxium (the company behind the AMCP eDossier System) and presented in a recent webinar, two out of three healthcare decision makers begin to evaluate a drug at least six months prior to approval. The survey also indicates that the primary source of information that payers are using for these pre-approval evaluations is clinicaltrials.gov (CT.gov), and that manufacturers are not always responsive to requests for information pre-approval.
In these blog posts we’re often guilty of highlighting the worst in healthcare (see, for example, here, here, and here). That attitude shouldn’t be totally surprising when we started Advera Health Analytics with a mission to correct a glaring problem in the healthcare system – the lack of transparent drug safety and efficacy data. That said, it seems only fair to give credit where it’s due when things go exactly right. This is one of those stories.
In the Q3 2014 FDA Adverse Event Reporting System (FAERS) data file, FDA quietly added a new field that links a patient and case report to a literature reference. Or in other words, there is additional information on the adverse event (AE) report that previously was not available. These literature references can provide beneficial context to the patient case report, validate or refute a causal relationship to an adverse event, and often times bring to the surface data that is otherwise undiscoverable.
Drug safety is often equated with post-marketing pharmacovigilance, something that is required by manufacturers only after their drug is approved. But when drug safety data are presented in an evidence aggregation platform there are very strong use cases in pharmaceutical competitive intelligence, health economics and outcomes (HEOR), and R&D. An evidence aggregation platform takes multiple sources of information and boils it down into actionable insight. That insight often has use cases that span all departments and can meet the demands of various priorities.
Seventy two hours after 2016 Q2 FDA Adverse Event Reporting System (FAERS) data were publicly released by FDA, our RxFilter® process had it standardized and loaded into the Evidex platform. Based on the volume of data in Q2, it looks like we’re well on the way to yet another record year of adverse events reported into FAERS.
Here is a chart of new case reports (including our estimate for full year 2016). Note that these numbers are based on a clean dataset; de-duplicated, primary suspect cases only).
Clinical data transparency has been under fire for years. There are documented cases of negative clinical trial results not being reported, leading to organizations like AllTrials.net. Trial end-points are often a moving target, being changed mid-trial, leading to organizations like Compare-Trials.org. And it’s not only manufacturer sponsored research either. As STAT pointed out, most research institutions routinely fail to meet reporting requirements as well.
Furthermore, negative data and important safety issues are often “hidden” in publications, outside of the requirements of reporting laws and standard practices. The lack of full transparency leads to evidence based medicine without all of the evidence, and makes pharma CI's job of fully understanding competitors’ data especially difficult.
One form of hidden data points are adverse events that are not listed as “serious” in clinical trials because they do not lead to death, hospitalization, or life-threatening situations.
Health Economics and Outcomes Research (HEOR) teams are using evidence aggregation platforms to conduct observational and retrospective studies using both clinical trial results and real world data. Whether a single database is being used for analysis or a combination of multiple datasets are combined, the best evidence aggregation platforms will incorporate standardized analytics that allow for efficient and effective insight generation. One of the key resources a HEOR team needs is the ability to standardize the downstream medical costs of drug adverse events.
In August 2016, CVS Healthcare announced its 2017 formulary exclusion list. The formulary exclusion list is a list of drugs that pharmacy benefits managers (PBM) like CVS Healthcare have decided to stop paying for in favor of a different, preferred drug. While preferred drugs may be chosen for safety or efficacy reasons, oftentimes economics plays a strong role.
One of those exclusions sent shockwaves throughout the pharmaceutical drug industry—the exclusion of Lantus (insulin glargine recombinant) in favor of its biosimilar Basaglar. That exclusion by CVS is expected to significantly impact Lantus’ sales. EvaluatePharma shows revenue for Lantus dropping from $7 billion in 2015 to $2.9 billion in 2022.
To prepare for more exclusions and continued pressure by payers that favor biosimilars, pharma CI, Medical teams, HEOR, and other commercial and R&D teams within drug manufacturers need to be prepared to fully understand any potential differences the biosimilar may show compared to the reference product. The data will be used for competitive insight as well as evidence generation to position the reference product as a safer choice, as soon as any potential differences are seen.
Last December, Stat News wrote a scathing report on the chronic under reporting of clinical trial results. We followed that up in July with our own blog post, highlighting specific under reporting rates we’ve found in just a handful of indications.