Useful references:

• How to improve R&D productivity: the pharmaceutical Industry’s grand challenge
  Nature Reviews Drug Discovery 9:203, 2010
  [DOI] [PDF]
  A classic review on the drug discovery pipeline and idealized costs, success rates, and durations for various stages of the discovery pipeline.
  A bit too idealized, however, and now a bit out of date.

• Estimation of clinical trial success rates and related parameters
  Biostatistics 20:273, 2019
  [DOI] [PDF]
  A very detailed analysis of clinical trial data for over 21,143 compounds, producing the most accurate estimate of success rates to date

• Financing correlated drug development projects
  Journal of Structured Finance 27:17, 2021
  [DOI] [PDF]
  A simulation model (complete with Python code!) that uses accurate clinical cost, duration, and success statistics of the preclinical through clinical development stages that addresses how financing small portfolios of drug discovery companies often leads to bankruptcy

• What are the odds of finding a COVID-19 drug from a lab repurposing screen?
  Journal of Chemical Informatics and Modeling
  [DOI] [PDF]
  An excellent review from Aled Edwards that points out there have been no (none, zero) successful examples of a new therapeutic hypothesis derived from lab screening of existing drugs leading to approval for a new indication.

• An oral SARS-CoV-2 Mpro inhibitor clinical candidate for the treatment of COVID-19
  [DOI] [PDF]
  The article reporting the discovery of paxlovid (nirmatrelvir), one of the most import medicines in the history of humankind, with 107 pages of supplementary material, describing how they did so in record time and highlighting some of the key considerations, including process manufacturing considerations.

• Biotin’s lessons in drug design
  [DOI] [PDF]
  A detailed look at the strongest noncovalent protein-ligand interaction known (fM to pM) provides lessons for designing potent small molecule ligands.

• Entropy-enthalpy compensation: Role and ramifications in biomolecular ligand recognition and design
  [DOI] [PDF]
  Don’t believe people who try to tell you that entropy-enthalpy compensation is important in drug discovery

• The maximal affinity of ligands
  [DOI] [PDF]
  A classic examination of the maximal affinity achievable by small molecule ligands, and why bigger is not always better.

• A Turing test for molecular generators
  [DOI] [PDF]
  How close are generative models to human medicinal chemists? This paper attempts to find out by determining whether humans can discriminate compound designs from human medicinal chemists from state-of-the-art computational approaches.

• Assessing the impact of generative AI on medicinal chemistry
  [DOI] [PDF]
  A brief, sober look at the real impact of generative AI models on current medicinal chemistry by seasoned drug hunters.

• Alpha Shock
  [DOI] [PDF]
  A refreshing look at what the future of drug discovery might look like, told via a speculative sci-fi short story published as a Journal of Computer Aided Molecular Design perspective.

• The Billion Dollar Molecule and its sequel, The Antidote (books)
  An incredibly detailed look insight drug discovery and development, from an author embedded with Vertex Pharmaceuticals for multiple years.

Slides

• Presentation slides: [PDF]

Other resources of interest:

• In the Pipeline - Derek Lowe’s blog about medicinal chemistry and drug discovery

• From the Analyst’s Couch - Nature Reviews Drug Discovery column on drug discovery successes and failures