Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2011 Mar;162(6):1239-49.
doi: 10.1111/j.1476-5381.2010.01127.x.

Principles of early drug discovery

J P Hughes  1 , S Rees, S B Kalindjian, K L Philpott
Affiliations
Review

Principles of early drug discovery

J P Hughes et al. Br J Pharmacol. 2011 Mar.

Abstract

Developing a new drug from original idea to the launch of a finished product is a complex process which can take 12-15 years and cost in excess of $1 billion. The idea for a target can come from a variety of sources including academic and clinical research and from the commercial sector. It may take many years to build up a body of supporting evidence before selecting a target for a costly drug discovery programme. Once a target has been chosen, the pharmaceutical industry and more recently some academic centres have streamlined a number of early processes to identify molecules which possess suitable characteristics to make acceptable drugs. This review will look at key preclinical stages of the drug discovery process, from initial target identification and validation, through assay development, high throughput screening, hit identification, lead optimization and finally the selection of a candidate molecule for clinical development.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Drug discovery process from target ID and validation through to filing of a compound and the approximate timescale for these processes. FDA, Food and Drug Administration; IND, Investigational New Drug; NDA, New Drug Application.
Figure 2
Figure 2
Overview of drug discovery screening assays.
Figure 3
Figure 3
Target ID and validation is a multifunctional process. IHC, immunohistochemistry.
Figure 4
Figure 4
Aequorin high throughput screening: validation testing GPCR antagonist assay (1536-well). Assay validation of a GPCR drug screening assay for the identification of agonist and antagonist ligands. Cells expressing the histamine H1 receptor and the calcium-sensitive photoprotein aequorin were dispensed into 1536-well microtitre plates. A total of 12 000 compounds were screened in duplicate to detect agonist ligands (left panel) and antagonist ligands (right panel). In the agonist assay (left panel), no drug response is represented in red, the response to a maximal concentration of the ligand histamine in blue and compound data in yellow. As is typically seen in agonist assays, the hit rate is very low due to the absence of false positives. In the antagonist assay (right panel), the response to histamine in the absence of test compound is represented in red (basal response), the response to a maximal concentration of a histamine antagonist in blue (100% inhibition) and compound data in yellow. As is typically seen in a cell-based inhibitor assay, there is significant spread of the compound data due to a combination of assay interference and compound activity. True actives correlate in the range 40% to 100% inhibition. Both assays have excellent Z'. GPCR, G-protein-coupled receptor.
Figure 5
Figure 5
Quality control (QC) in high throughput screening. To ensure the control of screening data in compound screening campaigns each assay plate typically contains a number of pharmacological control compounds. (A) Each 384-well plate contains 16 wells containing a low control and a further 16 wells containing an EC100 concentration of a pharmacological standard which are used to calculate the Z' factor (reference Zhang et al., 1999). Plates that generate a Z' factor below 0.4 are rescreened. (B) Each plate also contains 16 wells of an EC50 concentration of a pharmacological standard to monitor the variance in the assay (diamonds). (C) A heat map is generated for all plates that pass the pharmacological standard QC to monitor the distribution of activity across the assay plate. One would expect to see a random distribution of activity across the screening plate. A plate such as the one presented would be failed and rescreened due to the active wells clustering in the centre of the plate.
Figure 6
Figure 6
Hypothetical screening cascade. Examples of assays along the screening cascade from high throughput screening (HTS) to candidate selection are shown. DMPK, drug metabolism pharmacokinetics.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Abell AN, Rivera-Perez JA, Cuevas BD, Uhlik MT, Sather S, Johnson NL, et al. Ablation of MEKK4 kinase activity causes neurulation and skeletal patterning defects in the mouse embryo. Mol Cell Biol. 2005;25:8948–8959. - PMC - PubMed
    1. Bertram L, Tanzi RE. Thirty years of Alzheimer's disease genetics: the implications of systematic meta-analyses. Nat Rev Neurosci. 2008;9:768–778. - PubMed
    1. Boppana K, Dubey PK, Jagarlapudi SARP, Vadivelan S, Rambabu G. Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models. Eur J Med Chem. 2009;44:3584–3590. - PubMed
    1. Castanotto D, Rossi JJ. The promises and pitfalls of RNA-interference-based therapeutics. Nature. 2009;457:426–433. - PMC - PubMed
    1. Chessell IP, Hatcher JP, Bountra C, Michel AD, Hughes JP, Green P, et al. Disruption of the P2X7 purinoceptor gene abolishes chronic inflammatory and neuropathic pain. Pain. 2005;114:386–396. - PubMed

Publication types