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Phil Thomas

Price changes, market opportunities

As Pharma Footpath develops its databases, we're able to quickly drill down into the commercial opportunities. Where I think this is most interesting currently is in looking at renegotiated prices in different markets, and taking advantage of these before others do.

Examples of this include:

- 50% reduction in price for Australian Xolair PFS, bringing this below EU market. Valuable for the 54 clinical trials globally, and for the wider number of trading opportunities that come from these English language packs

- The centrally authorised product Pradaxa has had over 300 parallel trade licenses granted, and is listed in 65 clinical trials globally. A recent price reduction of over 20% in Hungary makes this an import area to review

It's clear from the data that when price changes occur, they don't happen in a synchronized fashion. That creates opportunities for finding the markets that have the earliest price movement, but also acts as a warning to companies about committing to purchasing product that may be about to undergo significant market changes (Revlimid is a prime example in Europe!)

If you'd like to talk more about these points, please get in touch! I'm always keen to talk more about the insights we're finding, and what we can build from it to make your business win more.

Phil

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Dutch data now added

The Netherlands has been the biggest trading market in Europe that PharmaFootpath had yet to include. I'm pleased to share we've now included the centralised product pricing, national product registrations will follow in the near future.

Adding a new country to our data takes some time as we have a number of steps to go through to ensure we have data integrity:

  • Agree data source for country (for example, we have an agreement with government in Germany to transfer data every 2 weeks)
  • Review data, isolating the data required for our database and identify any gaps
  • Translate the various APIs, presentations, routes, weights, and other data
  • Restructure data to match our schema
  • Run quality checks to ensure compliance with our standards, investigate each failure and resolve
  • Import data

This process is time consuming, and filled with complex edge cases, and often the origin data itself has mistakes included that we need to investigate. However, when we finish this, the end result is a well structured database that provides us with a valuable dataset that we can quickly interrogate and find new information.

I'm delighted we're continuing to add to this, and getting closer to our goals!

Phil

(If you've any questions about this, please feel free to message me to learn more!)

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