Hypothesis for changing models: current pharmaceutical paradigms, trends and approaches in drug discovery
- Subject Areas
- Bioinformatics, Public Health, Translational Medicine, Science Policy, Statistics
- Medicinal - Biological Chemistry, New Chemical Entities, Big Pharma, New Approval Drug, Big Data
- © 2015 Fuoco
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Hypothesis for changing models: current pharmaceutical paradigms, trends and approaches in drug discovery. PeerJ PrePrints 3:e813v1 https://doi.org/10.7287/peerj.preprints.813v1
Despite the increasing availability of chemicals, the number of New Drug Approvals (NDA) from the Food and Drug Administration (FDA) remains unchanged. The number of chemical structures available online via web-based open source applications will reach the symbolic 1 billion in the 10 next years. However, for no apparent reasons, the number of NDA accepted yearly has not changed in the past 25 years. One of the emerging paradigms of Big Pharma is that the more we know about molecular mechanisms and cell signaling pathways, the less we understand how to use this knowledge to make New Chemical Entities (NCE). Moreover, the annual number of pharmaceutical patents collected in the OCSE database has virtually not increased. Unexpectedly, the number of patents originating in the USA is decreasing significantly, while Asia is doing very well. The comparison between the number of NCEs and the American investment in Research and Development (R&D) in the last 35 years shows that to obtain a new drug blockbuster, the total investment is quasi 4 USD billion. One of the peculiarities is the inverse relationship between the investment in R&D and the continued shortfall in productivity. A main reason for this decline is that the quality of scientific reasoning done by experienced chemists is too often replaced by Big Data . It is time to change the role of chemistry in Big Pharma and to re-position it as the central science to progress and to lead to much needed innovation.
This is a review of current paradigms in drug discovery.