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Thursday, May 28, 2015

First they pay, then the delay

Imagine it’s late afternoon on a weekday, let’s say Friday. You decide to start the weekend a little early and head to a local establishment for an adult beverage or two. You’ve planned well and arrived at that magical time, happy hour, when select drinks can be bought at discounted prices. You venture up to the bar and put in your order, eager to enjoy the drink and bask in the glory of being a savvy money-saving consumer. The bartender hands you your cocktail and the bill, which causes you to freeze for a moment. You’ve been charged full price. You frustratingly ask, "what happened to the happy hour discount?" To which the bartender calmly replies, "all the local bars got together and agreed to abolish happy hour. Sorry about that." You wander back to your seat, drink in hand and wallet lighter than you'd like. This situation is not far off from what’s happening with brand-name and generic pharmaceuticals.


Pay the piper


“When patients demand brand, it’s like insisting on paying full price at happy hour,” said Kyle Weiler, a pharmacist from Phoenix, Arizona [Tweet this quote]. A reverse payment settlement agreement, also known as the more catchy ‘pay-for-delay’, is the pharmaceutical version of charging full prices when happy hour prices are available. It is a legal tactic which some branded drug manufacturers use “to stifle competition from lower-cost generic medicines,” according to the US Federal Trade Commission (FTC) website.


“These drug makers have been able to sidestep competition by offering patent settlements that pay generic companies not to bring lower-cost alternatives to market.” -FTC



In situations involving pay-for-delay, especially for blockbuster drugs with the potential for billions of dollars in annual sales, it’s a win-win for the drug companies. The generic firm wins by avoiding a potentially lengthy and costly patent dispute, and makes a significant chunk of change without having to manufacture a thing. The brand firm wins by keeping any generic competitors out of the market until after the brand patent expires, creating a monopoly where prices stay high and profits more than cover the costs of settling.


The big losers in delayed entry of cheaper generics are those who have to pay up for the more expensive brands. For example, it would be like if the generic versions of Advil, which have the same effectiveness but are half the cost as the brand-name, suddenly weren't available. The resulting universal high price would create a transfer of wealth from consumers to drug manufacturers, with both brand-name and generic firms sharing in the spoils. Altogether, these settlements cost US consumers and taxpayers $3.5 billion in elevated drug prices every year, according to an FTC study.


All for one, and one for all


1984 was a big year for pharmaceuticals. This was the year when the Hatch-Waxman bill, officially the Drug Price Competition and Patent Term Restoration Act, brought landmark changes which made it easier for generic drugs to enter the market. Generics are important because they make medicine affordable for millions of people and help keep down the cost of healthcare.


Before 1984, only about one third of brand name drugs faced competition from generics. Since then, nearly every branded drug has at least one generic competitor which, in certain instances, can account for more than half of the market share, significantly reducing the cost to consumers.


1984 was also the beginning of a pattern typical for the release of major drugs: launch, challenge, sue. This process spawned the pay-for-delay tactic within a decade. Here’s how it goes: a brand-name firm launches a new patented drug on the market; one, or a few, generic firms challenge the brand drug by marketing a competing product; the brand-name firm sues for patent infringement; rinse and repeat.


In an article examining the frequency and evolution of brand-generic settlements, author C. Scott Hemphill brings to light details of nearly all the significant pay-for-delay settlements between 1984 and 2009. By analysing archived press releases, trade publications, financial analyst reports, analyst calls with management, court filings of patent and antitrust litigation, SEC filings, FDA dockets, and FTC reports, Hemphill was able to uncover the terms of these settlements.




According to the aggregated data, there is an upward trend for the sum of the annual sales of the drugs involved in brand-generic settlements, and a transition from purely monetary agreements to more involving terms which include retained exclusivity. Retained exclusivity is also a byproduct of the Hatch-Waxman Act, whereby if several generic firms want to launch competing versions of a brand-drug, the first to submit what is called an Abbreviated New Drug Application (ANDA) may be granted a 180-day exclusive right to market its generic formulation directly against the brand-name. If this ‘first filer’ gets paid upfront to delay and gets to keep its half-a-year head start over other generics when it does finally enter the market, that’s pretty good reason to accept a pay-to-delay settlement.


Of the nine blockbuster (over $1 billion annual sales) drugs identified, eight involved retained exclusivity for first filers. These included Lipitor ($7.2 billion), Nexium ($3.4 billion) and Plavix ($3.4 billion) for which a 180-day market with only two competing firms would be worth hundreds of millions of dollars.


-Walter Savage Landor [Tweet this quote]


On June 17, 2013, four years and four and a half months after the FTC first filed a complaint in the US District Court for the Central District of California, the Supreme Court ruled five to three that profit-sharing deals between drug companies which delay the manufacturing of generic drugs can be challenged as anticompetitive.


In a statement regarding the decision in FTC v. Actavis, Inc., FTC Chairwoman Edith Ramirez said: “The Supreme Court’s decision is a significant victory for American consumers, American taxpayers, and free markets. The Court has made it clear that pay-for-delay agreements between brand and generic drug companies are subject to antitrust scrutiny, and it has rejected the attempt by branded and generic companies to effectively immunize these agreements from the antitrust laws.”



The judicial floodgates may have finally been opened. On April 20, Teva Pharmaceutical agreed to pay $512 million in the first resolution of a pay-for-delay allegation. This resolves nearly a decade of litigation against Cephalon Inc., which Teva acquired in 2011, of allegedly paying $136 million in cash to delay sales of generic versions of its narcolepsy pill Provigil.


Teva was in the headlines again on May 7, when a California appeals court ruled that a $398.1 million payment between Bayer and Barr Pharmaceuticals (now owned by Teva) was antitrust. The 1997 agreement allegedly delayed the release of the generic to Bayer’s Cipro antibiotic until 2003, a period in which Bayer made profits of about $6 billion according to court documents.


Despite the FTC’s prioritisation of going after anticompetitive pharmaceutical agreements and the recent court victories in antitrust settlements, the complex nature of the current pharmaceutical-patent system makes one thing clear: the pattern of drug launch, challenge, and sue isn’t going away anytime soon. And neither is pay-for-delay.



Thursday, May 7, 2015

♫ These are a few of my favourite data-things... ♫

This is the era of data, and journalism is evolving with the times. There are so many tools and resources available for data journalists (especially science data journalists) with more being added every other day it seems. It can get a bit overwhelming (and downright impossible) to keep up with all the latest developments, but I've put together a list of some of my favourite sources to help get you started.

Sources: 

World Health Organization (WHO) - Global Health Observatory Data Repository
Provides data (for viewing &/or downloading) pertaining to health-related topics such as Health systems, Infectious diseases, and Public health and environment.

World Bank - Open Data
Free and open access to data about development in countries around the world.

NASA - Data Portal
Growing catalog of publicly available datasets relating to both Space and Earth Science.

ClinicalTrials.gov - Registry & Results Database
Database of publicly and privately supported clinical studies of human participants conducted around the world. A service of the US National Institutes of Health (NIH).

Data.gov - US Government's Open Data
Over 130,000 datasets on topics such as Agriculture, Education, Public Safety, and Science & Research.
(see also: Data.gov.uk - UK Transparency and Open Data team)

Scrapers:

kimono - A wonderful web browser plugin that allows you to easily (no coding required) turn websites into APIs to extract only the data you want. It's infinite scroll and pagination functions are extremely useful for websites where the contents of the page expand as you scroll to the bottom or continue on more pages. A chat window that connects you with a helping hand and the kimono blog are also excellent features for problem-solving any issues and being involved in the wider kimmunity.

import.io - Another great online tool to turn web pages into data with no coding required. This also comes with a blog showcasing how the community is using import.io. A new feature allows you to send your extracted data straight to Plotly for streamlining the visualization of your just-scraped data.

Cleaner:

Google/Open Refine - My favourite tool for cleaning and transforming messy data (see previous blogpost). The best feature is that every action or operation on the data is recorded and stored in the order performed. This allows mistakes to be corrected with a simple undo, and the ability to copy the sequence of operations and quickly repeat the process for another (similar?) dataset.

*I've shared tools for scraping and cleaning that don't require coding, but can be modified and optimized with some coding knowledge. A great (free) online resource for learning pretty much everything online-coding related is W3Schools.

Visualizations:

tableau public - By far my favourite tool for building interactive charts. It also has a feature called dashboard which allows for combining multiple charts and/or maps to build more complex visualizations that can accentuate a particular point or angle and help weave together a narrative (see my CO2 emissions example, health spending and life expectancy example, and my other CO2 emissions example).

cartoDB - A mapmaking tool, for anything from the more localized city level, to countries on the global scale. Torque is a new-ish feature which allows for the map to change over time in an automatic and dynamic way (see my earthquake example). CartoDB uses CSS, which is a fairly straightforward computer language, but the interface is designed so as not to require any coding. Just in case you do want to modify your maps in a way requiring CSS code, or just to get an idea of the basics and special tricks for making interactive maps using CartoDB, they offer free webinars.

plotly - An easy-to-use and very useful tool for graphing data and finding the best chart-type to maximize the soul of the data (see earthquake depth example). The Plotly Blog is also a great resource for tips on choosing the right type of chart, seeing what other people have created, and maybe even showcasing a bit of your own work.

Datawrapper - Chart/map-making tool with the tagline: "create charts and maps in just four steps." Like Plotly it's very easy to use, and has a simple interface for customizing your visualization. A chart gallery shows the more than 100,000 charts that have been created using Datawrapper.

Websites:

The Upshot - online news and data visualization site for the New York Times.

FiveThirtyEight - Started by Nate Silver as a politics data blog for the New York Times until bought by ESPN. In addition to covering politics, FiveThirtyEight also touches on economics, sports, and SCIENCE!

theguardian datablog - data journalism courtesy of The Guardian.

Science data journalists:

Peter Aldhous - Is currently a science and health reporter for BuzzFeedNews and has previously worked at Nature and The New Scientist.

David Herzog - A veteran investigative reporter and data journalist, and the academic adviser to the
National Institute for Computer-Assisted Reporting.

Christie Aschwanden - Lead science writer for FiveThirtyEight.com and health columnist for The Washington Post.


This list is by no means perfect or exhaustive. There are so many different sources of data, a constant progression of the tools to acquire, clean, and visualize data, and so many websites/blogs/journalists/data-nerds with their own unique skills and perspectives. The idea is not to tell you what you should or shouldn't do, but to give you a grounding for what's out there, what I personally use, and to help you find your unique voice and style, and impart a bit of your soul into the data.