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An analysis of the attrition of drug candidates from four major pharmaceutical companies

Key Points

  • This Analysis article describes the compilation and analysis of combined data on the attrition of drug candidates from AstraZeneca, Eli Lilly and Company, GlaxoSmithKline and Pfizer.

  • The analysis reaffirms that control of physicochemical properties during compound optimization is beneficial in identifying compounds of candidate drug quality.

  • Safety and toxicology are the largest sources of failure within the data set.

  • The link between calculated physicochemical properties and frequent causes of attrition (preclinical toxicology, clinical safety and human pharmacokinetics) is assessed.

  • Analysis of this data set shows that none of the physicochemical descriptors we examined correlates with preclinical toxicology outcomes.

  • This work is the first to indicate a link between lipophilicity and clinical failure owing to safety issues. The utility of this finding in a prospective sense is discussed.

  • Although control of physicochemical properties is clearly important, this analysis suggests that further stringency in this respect is unlikely to have a significant effect on attrition in development and that additional work is required to address safety-related failures.

Abstract

The pharmaceutical industry remains under huge pressure to address the high attrition rates in drug development. Attempts to reduce the number of efficacy- and safety-related failures by analysing possible links to the physicochemical properties of small-molecule drug candidates have been inconclusive because of the limited size of data sets from individual companies. Here, we describe the compilation and analysis of combined data on the attrition of drug candidates from AstraZeneca, Eli Lilly and Company, GlaxoSmithKline and Pfizer. The analysis reaffirms that control of physicochemical properties during compound optimization is beneficial in identifying compounds of candidate drug quality and indicates for the first time a link between the physicochemical properties of compounds and clinical failure due to safety issues. The results also suggest that further control of physicochemical properties is unlikely to have a significant effect on attrition rates and that additional work is required to address safety-related failures. Further cross-company collaborations will be crucial to future progress in this area.

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Figure 1: Composition of the data set by phase and progression status.
Figure 2: Reasons for failure.
Figure 3: Distributions of selected calculated properties for the data set.
Figure 4: Comparison of selected physicochemical property distributions for the data set compared with compounds in patent applications and launched drugs.
Figure 5: Distributions of different target classes within the data set.
Figure 6: Analysis of potential links between physicochemical properties and non-clinical toxicology outcomes.
Figure 7: Analysis of potential links between physicochemical properties and non-clinical safety failures.
Figure 8: Analysis of potential links between physicochemical properties and failures due to poor pharmacokinetics.

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Acknowledgements

We thank N. Blomberg (AstraZeneca), A. de Dios (Eli Lilly), M. Beaumont and J. Valentine (GlaxoSmithKline) and S. Louise-May (Pfizer) for their roles in the compilation of the dataset.

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Correspondence to Michael J. Waring.

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Competing interests

The authors are minor stock holders and employees of their respective companies. The research was funded jointly by the four pharmaceutical companies AstraZeneca, Eli Lilly and Company, GlaxoSmithKline and Pfizer. The authors from Thomson Reuters received payment from these four companies to compensate them for their part in this work.

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Supplementary information

Supplementary information S1 (box)

Dataset compilation and statistical analysis (PDF 1541 kb)

Glossary

Rule of five

Lipinski's 'rule of five' was derived from an analysis of small-molecule oral drugs (Phase II and above) and identifies desirable limits for several key physicochemical parameters; specifically, molecular mass <500 Da, number of hydrogen-bond donors <5, number of hydrogen-bond acceptors <10 and calculated octanol–water partition coefficient <5. In the original study 90% of the data set obeyed at least three of these 'rules'.

logP

The logarithm of the octanol–water partition coefficient, which is a measure of a molecule's preference for aqueous or lipophilic environments, and can be used to rationalize the ability of molecules to cross biological membranes. logP is defined as the ratio of un-ionized drug distributed between the octanol and water phases at equilibrium. Larger values imply greater lipophilicity.

Topological polar surface area

(tPSA). A measure of the degree of polarity of a molecule; the PSA is calculated from the sum of surface contributions from polar fragments. PSA has been shown to correlate with the passive permeability of compounds through membranes. The summation method enables much more rapid calculation than other methods while returning practically identical results.

Therapeutic index

In a drug development setting, this is the quantitative ratio of the exposure level at the chosen safety end point divided by the exposure level at the chosen efficacy end point, typically the ratio of the highest exposure to the drug that results in no toxicity over that which produces the desired efficacy.

logD7.4

The logarithm of the octanol–water distribution coefficient, accounting for ionization at pH 7.4. logD7.4 is equal to the logP for un-ionized (neutral) compounds but lower than logP for acids or bases because the majority of the ionized form partitions into the aqueous phase.

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Waring, M., Arrowsmith, J., Leach, A. et al. An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat Rev Drug Discov 14, 475–486 (2015). https://doi.org/10.1038/nrd4609

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