The Viekira Pak effect – Will it change P&T practices for good?

Jim Davis, Executive Vice President, Advera Health Analytics -

I had the opportunity this week to attend the New England Comparative Effectiveness Public Advisory Council (CEPAC) meeting in which they discussed and voted on the evidence the Institute for Comparative Effectiveness Research (ICER) recently generated on the new PCSK-9 inhibitors, Repatha and Praluent.

The report concluded that while the novel medications clearly demonstrated impressive results in clinical trials, the lack of current evidence around harms and outcomes led to a net health benefit assessment of "Promising but Inconclusive." Prior to an expected "No" vote as to whether the medications were cost effective, the panelists reacted to the ICER evidence with a clear majority voting "No" to the question of net health benefit in the majority of patients eligible for PCSK-9 therapy.

This result was a surprise, but an even more surprising were the reasons the panelists provided the thumbs down: unknown harms. A direct quote from the ICER team was although they only gave the PCSK-9's a 10% chance of a negative net health benefit and no adverse events seemed concerning, "...we said the same thing with Abbvie's hepatitis C drug." Several panelists said they needed to see the "adverse events from public monitoring" and the outcomes trials that are due in 2017 before being able to make a net health benefit decision.

For those unaware, FDA recently made warning and label change to Abbvie's Viekira Pak around liver injury, and as demonstrated by the PCSK-9 decision, FDA's announcement is weighing heavy on the minds of formulary decisions-makers. It also demonstrates a clear need for P&T committees to have access to post-marketing data to allow them to get powerful insight into what is going on in the real world when mass groups of individuals start regularly taking newly approved drugs.

It is clear now the FDA warning will have a lasting impact on P&T committees in two major ways:

First, in an era in which acquisition cost is the major concern, the Viekira Pak Effect will force decision makers to re-focus on drug safety. Immediate cost savings have long been trumping long term patient outcomes and economic impact. But now the realization that adverse events and other unexpected harms have direct costs associated with them will force decision makers to identify ways to incorporate additional aspects of drug safety, including the downstream costs of drug adverse events, into their standard decision making workflow.

Second, the Viekira Pak Effect will instigate decision makers to continuously monitor for early safety indicators from real world post marketing data. One panelist in the CEPAC policy discussion brought up the fact that the first decision made on a drug, isn't the last. That formulary policy can and should be altered as more information is gleaned.

This is an extremely important point.

Although decisions can be adjusted as new information comes to light, most decision makers currently are not actively monitoring the data that are available to them, and are instead waiting for FDA communications to make any changes (this can often be a multi-year wait). We believe this will change as the onus of responsibility becomes more evenly weighted between the drug manufacturer and the prescribing entity – whether a hospital, insurer or doctor. The access to data will force a change in the conversation to – why a prescription decision was made when post marketing safety data suggested an alternative option was wiser.

Data tells a story. When the data reveals that large groups of individuals are experiencing unexpected outcomes as a result of taking a particular prescription, action must be taken. The private sector has a responsibility to the public. And the private sector is no longer just the drug manufacturer; with the advent of access to big data, the private sector now includes managed care organizations. Those who are innovative and look outside the box and embrace the story being told by big data will be able to express early indications of concern and set in motion policy changes, such as prior authorizations and formulary alternatives.

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