Erooms_law

Goal

In this notebook, I'll combine data from the yearly PhRMA report and the FDA's databases to check if the trajectory of Eroom's law has been affected by the introduction of machine learning to the biopharmaceutical ecosystem.

Final Plot

If you want to skip the code and see the results:

The trend certainly hasn't reversed but after the introduction of ML and especially DL, the trend seems to be decreasingly less stably.

Citations

Data Sources

• PhRMA Data

  • Yearly report of biopharmaceutical industry showing amount of R&D spending and sales.

• FDA Drug Approval Data

  • Table of drugs approved in a specific month.

References

1. https://blogs.sciencemag.org/pipeline/archives/2012/03/08/erooms_law

2. Hongming Chen, Ola Engkvist, Yinhai Wang, Marcus Olivecrona, Thomas Blaschke, The rise of deep learning in drug discovery, Drug Discovery Today, Volume 23, Issue 6, 2018, Pages 1241-1250, ISSN 1359-6446, https://doi.org/10.1016/j.drudis.2018.01.039. (http://www.sciencedirect.com/science/article/pii/S1359644617303598)

3. https://en.wikipedia.org/wiki/Moore%27s_law

4. https://en.wikipedia.org/wiki/Eroom%27s_law

5. http://wavefunction.fieldofscience.com/2012/03/unstoppable-moore-hits-immovable-eroom.html

6. APA 5th Edition: Journal article (Scannell, Blanckley, Boldon, & Warrington, 2012, p. ) Scannell, J. W., Blanckley, A., Boldon, H., & Warrington, B. (2012). Diagnosing the decline in pharmaceutical R&D efficiency. Nature Reviews Drug Discovery 64(2), p. 10-12.