Specialty drugs have been one of the bright spots in the Pharmaceutical industry, accounting for nearly 30 percent of total pharmacy spend on the commercial side in 2013, despite accounting for less than 1 percent of all US prescriptions. Spending on specialty drugs increased 14.1 percent that year, and is expected to increase another 63 percent by 2016. At the same time, spending on six of the top 10 traditional therapy classes dropped, primarily because of lower unit costs.
Yet state systems and commercial insurers globally are pushing back against these high-cost drugs. Plans are designing special formularies for specialty drugs, implementing Oncology pathways to reign in costs, and shifting coverage from the medical benefit to the pharmacy benefit, which may put greater financial responsibility on patients. Indeed, 61 percent of commercial plans (75 percent of covered lives), and 87 percent of Medicare Advantage and prescription drug plans, charged a co-insurance rather than co-pay for specialty drugs in 2013. In late 2014, state Medicaid directors sent an eight-page letter to Congress urging “an immediate federal solution” to the cost of specialty drugs.
Providers are also pushing back. In April 2013, an international coalition of cancer experts released a call to action decrying the “astronomical” cost of certain drugs. The letter followed the actions of Oncologists at New York’s Memorial Sloan-Kettering Cancer Center in 2012 who publically refused to prescribe the drug Zaltrap (ziv-aflibercept) for Colon Cancer because it was twice as expensive as similar therapies. Their outcry eventually led the drug’s manufacturer to slash the price in half.
To combat the risk of significant revenue loss from these drugs, manufacturers need to determine pricing and marketing based on more than just recouping research investment and hitting profit goals. Analytics must include the effect of pricing on increasingly cost-conscious private and public payers, as well as the true value of the product.
Applying AI to Pricing
Pricing can be done far more intelligently than Pharma pricing agencies and Pharma internal teams appear to be doing. Eularis are now applying Artificial Intelligence to pricing based on simulated clinical trials in real world populations and real payer costs. This means we can use Artificial Intelligence to price for both high value for payer and maximum acceptable price for Pharma.
If you want to know more, contact us at Eularis https://www.eularis.com/contact.