FOLLOW

FOLLOW

SHARE

The Importance Of Data In Pharma Pricing

The pharmaceutical industry has had some issues with pricing, can big data help?

13Feb

We have seen a huge number of different factors impacting on the purchase of drugs across the world over the past few years and we are likely to see a considerable change in the future too. One of the main issues has been the huge scandals that have revolved around the pricing of drugs, with some massive price hikes causing considerable problems for patients and healthcare providers.

The Telegraph in the UK found that the NHS was paying considerably more for drugs such as ‘Tamoxifen - one of the most common treatments for breast cancer - saw its price rise from 10 pence per tablet to £1.21 - a rise of 1,100 per cent’ and ‘Busulfan, used to treat leukaemia, rose from 21 pence per pill to £2.61 - a 1,142 per cent rise.’ There have been court cases surrounding these increases with Pfizer and Flynn being fined £90 million for their pricing.

It is impacting the UK especially hard, due to the National Health Service being publicly funded. It means that it firstly represents one of the largest single buyers of drugs in the world, but it is also one that needs to justify its expenditure and work within an incredibly tight budget. This budget is also being stretched as the UK population is ageing and budget increases are not sufficient for keeping up with demand, with an IFS report showing that the average yearly budget increase has been just over 1% compared to an average of over 4% since 1955. Sir Andrew Dillon, CEO of NICE (National Institute of Health and Care Excellence who approve drugs for use in the NHS) said of the situation ‘It’s concerning that we’re seeing such sharp rises in the price of cancer drugs. We need large-scale changes to the whole ecosystem of drug discovery and development to ensure new medicines are created more cheaply and priced more fairly.’

These price changes are seeing the NHS buying fewer drugs, or at least fewer drugs per person, with some patients being pushed away from the more expensive options. It isn’t just an issue for the healthcare providers and patients, but also for the pharmaceutical companies. After all, if they are selling fewer drugs at a higher price then it not only prices a large section of the market out of buying them, but also gives a huge opportunity for rivals to create a similar drug that undercuts their pricing.

There are huge differences in the costs of drugs throughout the world, with the previously mentioned Telegraph coverage claiming that Tamoxifen (£1.21 per pill in the UK) was available for 2p in India whilst Busalfan (£2.61 per pill in the UK) was available for 3p. There are clearly going to be differences in infrastructure and circumstances that increase the price, although it’s difficult to see how that represents a 8,600% increase in the case of Busulfan.

There are huge challenges facing pharmaceutical companies in these conditions, combined with the huge public backlash against Martin Shkreli, the face of price gouging, who GQ referred to as ‘the worst person of 2015’ and who Seth Myers labelled ‘a real slappable prick’, after his price gouging of Daraprim. However, there are ways around this and big data may well be the best.

Using data to effectively set pricing strategy is becoming more popular as companies in all industries realize that using traditional methods is no longer optimal. Mckinsey have done some research on the subject and found that ’on average, a 1% price increase translates into an 8.7% increase in operating profits’ but it is clear that a 5000% rise did not see a 43,500% increase in operating profit for Shkreli’s company, who had $14.6 million net loss in the preceding quarter after the price hike. They also had a rival release an alternative drug for $1 per pill (compared to $750 for the licensed version) which is naturally going to the choice of the bulk of what was a previously captive market.

Pricing is perhaps more difficult in pharmaceuticals than any other industry because the tiny pill that sits in your hand is likely to cost almost nothing to produce, yet to get it to patients is incredibly expensive. There are R&D costs, licensing, multiple levels of trialling, distribution, constant quality control and also factoring in the hundreds of other drugs who never made it past the first step which need to be paid for by the successful drugs created. It is for this reason that big data needs to be heavily implemented to help with price setting.

Firstly, there are thousands of different variables that need to be input and weighed up, not only the competitiveness of the drug against alternatives, but in location and factoring in the failed projects that have led to an eventual finished drug. Then there is planning likely usage numbers, with a huge price increase it is likely that a large proportion of the projected users will simply look elsewhere. We have already seen patients in the NHS being steered away from the more expensive treatments because it is not financially viable. If other large healthcare providers take the same approach the numbers will become incredibly difficult to calculate as the loss of audience will be increasingly unpredictable.

Data also allows for better long-term planning, giving pharma companies the opportunity to plan pricing based on making a modest profit across the entire time a license is held, rather than needing to create huge price increases to recuperate their costs in the shortest time possible. Instead, feeding as much relevant information into the system as possible (and even working out what that relevant information is) is one of the most powerful uses for huge and disparate data sources.

There are clearly many pharmaceutical companies who are already using data in this way and they should be commended, but the outliers, especially when they are household names, need to get with the program. They need to look at their pricing not as a way of creating as much profit in as short a time as possible, but instead keeping people on-side and keeping prices at a manageable level. 

Comments

comments powered byDisqus
Turkeyss

Read next:

What’s On Data Analysts’ Plates This Thanksgiving

i