Skip to main content

Lead Optimization, Preclinical Toxicology

  • Chapter
  • First Online:

Part of the book series: AAPS Advances in the Pharmaceutical Sciences Series ((AAPS,volume 25))

Abstract

Nonclinical Toxicology During “Lead Optimization”.

The major deliverable from a “lead optimization” (LO) tox package will be a high-quality candidate compound, suitably characterized to enable judgment-based selection of clinical candidates destined for further development and preparation for initial clinical investigation. For small molecules, the LO phase of development typically represents the first opportunity to characterize the novel chemistry using an integrated approach that collectively scrutinizes a molecule’s overall “druggability,” with a focus on characterization of all the physical chemistry properties that may influence drug disposition, safety and tolerability, and dose prediction (with the underlying assumption that the hypothetical biological mechanism of action remains intact).

In keeping with the 3R principles, modern safety assessment continues to explore the potential risks and liabilities associated with the chemical structure via various predictive in silico screens that tackle both intrinsic toxicophore identification, in addition to structural similarity assessment of chemical moieties appearing in other structures with known adverse event profiles, and a battery of cell-based profiling assays that enable characterization of tolerability based on chemical properties, in addition to bespoke cell models that afford characterization of functional risk (e.g., induced pluripotent cell lines for different target organ systems). Collectively, these data are used to better inform investigators on the potential in vivo risks which may manifest in the preliminary multidose studies, which are designed to not only corroborate the in vitro predictive assessments but also identify the degree of monitorability (and subsequently, manageability) of on- and/or off-target toxicities associated with different drug exposures, in the context of a developable clinical dosing range.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Blomme EA, Will Y. Toxicology strategies for drug discovery: present and future. Chem Res Toxicol. 2016;29(4):473–504.

    Article  CAS  PubMed  Google Scholar 

  2. Roberts RA, Kavanagh SL, Mellor HR, et al. Reducing attrition in drug development: smart loading preclinical safety assessment. Drug Discov Today. 2014;19(3):341–7.

    Article  CAS  PubMed  Google Scholar 

  3. Tannenbaum J, Bennett BT. Russell and Burch’s 3Rs then and now: the need for clarity in definition and purpose. J Am Assoc Lab Anim Sci. 2015;54(2):120–32.

    PubMed  PubMed Central  Google Scholar 

  4. Stark C, Steger-Hartmann T. Nonclinical safety and toxicology. Handb Exp Pharmacol. 2016;232:261–83.

    Article  PubMed  Google Scholar 

  5. Morton DM. Importance of species selection in drug toxicity testing. Toxicol Lett. 1998;102–103:545–50.

    Article  PubMed  Google Scholar 

  6. Gaudy JH, Sicard JF, Lhoste F, et al. The effects of cremophor EL in the anaesthetized dog. Can J Anaesth. 1987;34(2):122–9.

    Article  CAS  PubMed  Google Scholar 

  7. Luijten M, Olthof ED, Hakkert BC, et al. An integrative test strategy for cancer hazard identification. Crit Rev Toxicol. 2016;46(7):615–39.

    Article  CAS  PubMed  Google Scholar 

  8. Mestres J, Gregori-Puigjane E, Valverde S, et al. Data completeness—the Achilles heel of drug-target networks. Nat Biotechnol. 2008;26(9):983–4.

    Article  CAS  PubMed  Google Scholar 

  9. Hu Y, Jasial S, Bajorath J. Promiscuity progression of bioactive compounds over time. F1000Res. 2015;4(Chem Inf Sci):118.

    Google Scholar 

  10. Dessertenne F. Note on a certain type of spontaneous repetitive auricular electrical activity. Arch Mal Coeur Vaiss. 1965;58:553–7.

    CAS  PubMed  Google Scholar 

  11. Li X, Zhang R, Zhao B, et al. Cardiotoxicity screening: a review of rapid-throughput in vitro approaches. Arch Toxicol. 2015;90(8):1803–16.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marcus H. Andrews Ph.D. .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 American Association of Pharmaceutical Scientists

About this chapter

Cite this chapter

Andrews, M.H., Reynolds, V.L. (2017). Lead Optimization, Preclinical Toxicology. In: Bhattachar, S., Morrison, J., Mudra, D., Bender, D. (eds) Translating Molecules into Medicines. AAPS Advances in the Pharmaceutical Sciences Series, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-50042-3_8

Download citation

Publish with us

Policies and ethics