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Published on: September 27, 2016
Societal costs versus savings from wild-card patent extension legislation to spur critically needed antibiotic
B Spellberg1, L G Miller, M N Kuo
1Division of Infectious Diseases, Harbor-University of California, Los Angeles Medical Center, and the Los Angeles Biomedical Research Institute, 1124 W. Carson St., Torrance, CA 90502, USA. bspellberg@labiomed.org
Background:
Over the last two decades, an alarming rise in infections caused by antibiotic-resistant microbes has been paralleled by an equally alarming decline in the development of new antibiotics to deal with the threat. In response to this brewing "perfect storm" of infectious diseases, the Infectious Diseases Society of America (IDSA) has released a white paper that proposes incentives to stimulate critically needed antibiotic development by pharmaceutical companies. A cornerstone of the recommendations is establishment of a "wild-card patent extension" program. This program would allow a company receiving United States (US) Food and Drug Administration (FDA) approval for a new anti-infective agent targeting a drug-resistant pathogen to extend the patent on a drug within their active portfolio. However, wild-card patent extension legislation is highly controversial due to concerns regarding its societal cost.
Methods:
We performed a systematic literature review to estimate the societal cost of wild-card patent extension compared to the savings resulting from the availability of one new antibiotic to treat multi-drug-resistant Pseudomonas aeruginosa.
Results:
We conservatively estimate that wild-card patent extension applied to one new antibiotic would cost $7.7 billion over the first 2 years, and $3.9 billion over the next 18 years. Thus, even if the new antibiotic abrogated only 50% of the annual societal cost of multidrug-resistant P. aeruginosa (estimated $2.7 billion), wild-card patent extension would be cost neutral by 10 years after approval of the new antibiotic, and would save society approximately $4.6 billion by 20 years after approval.
Conclusions:
Wild-card patent extension appears to be a cost-effective strategy to spur anti-infective development. Although our analysis is limited by the precision of published data, our model employed conservative assumptions.
Insights
Wild-card patent extension may be a cost-effective strategy to incentivize new antibiotic development. This policy could save society billions by combating drug-resistant infections, despite initial costs.
Area of Science:
- Pharmacoeconomics
- Infectious Diseases
- Intellectual Property Law
Background:
- Rising antibiotic resistance and declining new antibiotic development pose a significant public health threat.
- The Infectious Diseases Society of America (IDSA) proposed incentives, including "wild-card patent extension," to encourage pharmaceutical companies to develop new anti-infectives.
- Wild-card patent extension allows an extended patent for an existing drug upon approval of a new anti-infective targeting resistant pathogens, but faces controversy over societal costs.
Purpose of the Study:
- To estimate the societal cost of the wild-card patent extension program.
- To compare these costs with the potential savings from a new antibiotic effective against multidrug-resistant Pseudomonas aeruginosa.
Main Methods:
- A systematic literature review was conducted.
- A cost-benefit analysis was performed to evaluate the economic impact of the patent extension policy.
Main Results:
- The estimated cost of wild-card patent extension for one new antibiotic is $7.7 billion over the first 2 years and $3.9 billion over the subsequent 18 years.
- Even if the new antibiotic only mitigates 50% of the annual societal cost of multidrug-resistant P. aeruginosa ($2.7 billion), the policy becomes cost-neutral within 10 years.
- The program is projected to save society approximately $4.6 billion by 20 years post-approval.
Conclusions:
- Wild-card patent extension appears to be a cost-effective strategy to stimulate the development of new anti-infective agents.
- The analysis, while limited by data precision, utilized conservative assumptions, suggesting the findings are robust.
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