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.
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.
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.
Constructing accurate drug and competitive market forecasts is a vital function of pharmaceutical commercial teams. A model that combines patient-based and event-based assumptions provides for a stronger understanding of the drug’s market, and accounts for potential scenarios that could affect what patient populations are treated. A lot of data need to be synthesized to create the best forecast possible. Evidence aggregation platforms are well suited to this task.
Let’s examine the case of a new drug entering a market which is claiming superior safety and efficacy vs. standard of care. While it is expected to quickly take market share, there are concerns that the advantages may only be seen in certain patient demographics. If true this would significantly alter patient-based forecasts and market penetration models.
Pharmaceutical Competitive Intelligence (CI) teams within pharma have always been early adopters of data driven insight. Individual data points aggregated into an interconnected dataset allow pharma CI professionals to access, manipulate, and keep up with constant change.
As such, it’s come as no surprise that evidence aggregation platforms have found strong use cases in this area of pharma, helping manufacturers generate new insight on market dynamics which aids them in fully understanding the competitive landscape.
A case study of how an evidence aggregation platform has been used should be a helpful example.
An evidence aggregation platform is a web based software-as-a-service (SaaS) application that takes multiple, disparate sources of data, or evidence, and combines those data together using analytics to create new insight.
For example, an evidence aggregation platform can read adverse event data points from multiple clinical trial results and perform on-demand meta-analyses to better understand side effect rates for drugs. The evidence aggregation platform can then compare side effect rates from clinical trial results to side effect rates found in real world data such as pharmacy claims data or electronic health records (EHR).
On August 1, 2016, Dan Leonard, the President of the National Pharmaceutical Council published an opinion piece for Morning Consult, laying out his reasons for FDA to provide guidance on how biopharmaceutical companies can utilize and share real-world evidence with healthcare decision makers. He argues that due to shortcomings and ambiguities in existing laws, the exchange of information is limited, and stakeholders are making decisions without access to all of the pertinent information. His solution is more regulation and guidance from FDA.