Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-pjpqr Total loading time: 0 Render date: 2024-06-28T08:31:16.577Z Has data issue: false hasContentIssue false

10 - Integrated approaches to lead optimization: improving the therapeutic index

from II - INTEGRATED APPROACHES OF PREDICTIVE TOXICOLOGY

Published online by Cambridge University Press:  06 December 2010

Jinghai J. Xu
Affiliation:
Merck Research Laboratory, New Jersey
Laszlo Urban
Affiliation:
Novartis Institutes for Biomedical Research, Massachusetts
Get access

Summary

INTRODUCTION: RISK AWARENESS, A MAJOR ELEMENT OF MODERN DRUG DISCOVERY

Since the introduction of simple, in silico, and in vitro tools for the assessment of physicochemical properties in the 1990s. drug discovery has come a long way. The impact of these tools was based on their acceptable predictive value for in vivo pharmacokinetic performance and their cost effectiveness for large-scale profiling. During the past decade, we have seen a rapid improvement in the throughput and quality of these assays, accompanied by an impressive development of in silico tools based on accumulating experimental knowledge. Today, most if not all, pharmaceutical companies use an arsenal of these assays to fine-tune compound properties prior to clinical testing. This “revolution” has resulted in diminished attrition rate due to ADME-related liabilities.

The significant improvement in ADME (absorption-distribution-metabolism-elimination) properties in the early phases of drug discovery indeed shifted the challenges in lead optimization and candidate selection toward safety and toxicology aspects. This is partly due to the complexity of safety assessment, which is difficult to translate into high-throughput, cost-effective in vitro assays with significant predictive value and partly due to the mandatory use of fixed assays required by regulatory authorities. In addition, some toxicities such as reactive metabolite-related hepatotoxicity remain difficult to predict in vitro. To date, most safety-related assays have been performed in vivo with limited insight into the underlying mechanisms that would define the link between a particular target molecule and the observed toxic or adverse drug reaction (ADR).

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Lipinski, CA. Drug-like properties and the causes of poor solubility and poor permeability. J Pharm Toxicol Methods. 2000;44:235–249.CrossRefGoogle ScholarPubMed
Kola, I, Landis, J. Can the pharmaceutical industry reduce attrition rates?Nat Rev Drug Discov. 2004;3:711–716.CrossRefGoogle ScholarPubMed
,Cardiac Arrhythmia Suppression Trial II Investigators. Effect of the antiarrhythmic agent moricizine on survival after myocardial infarction. New Engl J Med. 1992;327:227–233.CrossRefGoogle Scholar
Keating, MT, Sanguinetti, MC . Molecular and cellular mechanisms of cardiac arrhythmias. Cell. 2001;104:569–580.CrossRefGoogle ScholarPubMed
Jamieson, C, Moir, EM, Rankovic, Z, et al. Medicinal chemistry of hERG optimizations: Highlights and hang-ups. J Med Chem. 2006;49:5029–5046.CrossRefGoogle ScholarPubMed
Pearlstein R Vaz, R, Rampe, D. Understanding the structure-activity relationship of the human ether-a-go-go-related gene cardiac K+ channel. A model for bad behavior. J Med Chem. 2003;46:2017–2022.CrossRefGoogle Scholar
Redfern, WS, Carlsson, L, Davis, AS, et al. Relationships between preclinical cardiac electrophysiology, clinical QT interval prolongation and torsade de pointes for a broad range of drugs: Evidence for a provisional safety margin in drug development. Cardiovasc Res. 2003;58:32–45.CrossRefGoogle ScholarPubMed
Kramer, JA, Sagartz, JE, Morris, DL. The application of discovery toxicology and pathology towards the design of safer pharmaceutical lead candidates. Nat Rev Drug Discov. 2007;6:636–649.CrossRefGoogle ScholarPubMed
Leeson, PD, Springthorpe, B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov. 2007;6:881–890.CrossRefGoogle ScholarPubMed
Bender, A, Jenkins, JL, Glick, M, et al. Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effect from chemical structure. Chem Med Chem. 2007;2:1–14.Google ScholarPubMed
Wang, J, Urban, L, Bojanic, D. Maximising use of in vitro ADMET tools to predict in vivo bioavailability and safety. Expert Opin Drug Metab Toxicol. 2007;3:641–665.CrossRefGoogle ScholarPubMed
Wang, J. Comprehensive assessment of ADMET risks in drug discovery. Curr Pharm Design, 2009;5(19):2195–2219.CrossRefGoogle Scholar
Kerns, EH, Di, L. Physicochemical profiling: Overview of the screens. Drug Discov Today Technol. 2004;1:343–348.CrossRefGoogle ScholarPubMed
Thomas, VH, Bhattachar, S, Hitchingham, L, et al. The road map to oral bioavailability: An industrial perspective. Expert Opin Drug Metab Toxicol. 2006; 2:591–608.CrossRefGoogle Scholar
Li, AP. Building predictive ADMET models for early decisions in drug discovery. Drug Discov Today. 2001;6:357–366.CrossRefGoogle Scholar
Ramot, Y, Nyska, A. Drug-induced thrombosis – Experimental, clinical, and mechanistic considerations. Toxicol Pathol. 2007;35:208–225.CrossRefGoogle ScholarPubMed
Meyer, CH, Schmidt, JC, Rodrigues, EB, et al. Risk of retinal vein occlusions in patients treated with rofecoxib (Vioxx). Ophthalmologica. 2005;219:243–247.CrossRefGoogle Scholar
Zhu, W, Zeng, X, Zheng, M, et al. The enigma of β2 adrenergic receptor Gi signaling in the heart. The good, the bad, and the ugly. Circ Res. 2005;97:507–509.CrossRefGoogle ScholarPubMed
Shamovsky, I, Connolly, S, David, L, et al. Overcoming undesirable HERG potency of chemokine receptor antagonists using baseline lipophilicity relationships. J Med Chem. 2008;51:1162–1178.CrossRefGoogle ScholarPubMed
Obradovic, T, Dobson, G, Shingaki, T, et al. Assessment of the first and second generation antihistamines brain penetration and role of P-glycoprotein. Pharm Res. 2007;24:318–327.CrossRefGoogle ScholarPubMed
Faller, B, Wang, J, Zimmerlin, A, et al. High-throughput in-vitro profiling assays: How useful for decision making?Exp Opin Drug Metab Toxicol. 2006;2:823–833.CrossRefGoogle Scholar
Rubinstein, AL. Zebrafish assays for drug toxicity screening. Expert Opin Drug Metab Toxicol. 2006;2:231–240.CrossRefGoogle ScholarPubMed
Peterson, RT, Nass, R, Boyd, WA, et al. Use of non-mammalian alternative models for neurotoxicological study. Neurotoxicology. 2008;29:546–555.CrossRefGoogle ScholarPubMed
Whitebread, S, Hamon, J, Bojanic, D, et al. In vitro safety pharmacology profiling: An essential tool for drug development. Drug Discov Today. 2005;10:1421–1433.CrossRefGoogle ScholarPubMed
Vaz, RJ, Klabunde, T eds. Antitargets: Prediction and Prevention of Drug Side Effects. Wiley-VCH, Weinheim; 2008.CrossRefGoogle Scholar
Krejsa, CM, et al. Predicting ADME properties and side effects: The BioPrint approach. Curr Opin Drug Discov Dev. 2003;6:470–480.Google ScholarPubMed
Zhang, S, Zhou, Z, Gong, Q, et al. Mechanism of block and identification of the verapamil binding domain to HERG potassium channels. Circ Res. 1999;84:989–998.CrossRefGoogle ScholarPubMed
Giuliano, KA, Johnston, PA, Gough, A, et al. Systems cell biology based on high- content screening. Methods Enzymol. 2006;414:601–619.CrossRefGoogle ScholarPubMed
Cellumen, . Cell Ciphr Toxicity Profiling. http://www.cellumen.com/solutions/cytotoxicity-csb.php., accessed date: 07. 05. 2010.
Morelli, JK, Buehrle, M, Pognan, F, et al. Validation of an in vitro screen for phospholipidosis using a high-content biology platform. Cell Biol Toxicol. 2006;22(1):15–27.CrossRefGoogle Scholar
Hamon, J, Whitebread, S, Techer-Etienne, V, et al. In vitro safety pharmacology profiling: What else beyond hERG? 2009;1(4):645–665.
,Ambit Biosciences. http://www.ambitbio.com. Accessed date: 07. 05. 2010.
Goldstein, DM, Gray, GS, Zarrinkar, PP . High-throughput kinase profiling as a platform for drug discovery. Nat Rev Drug Discov. 2008;7:391–397.CrossRefGoogle ScholarPubMed
Lu, LY, Wood, JL, Ye, L, et al. Aurora A is essential for early embryonic development and tumor suppression. J Biol Chem. 2008;283:31785–31790.CrossRefGoogle ScholarPubMed
Robless, P, Mikhailidis, DP, Stansby, GP. Cilostazol for peripheral arterial disease. Hoboken, NJ: John Wiley & Sons, 2008.
Elangbam, CS, Job, , Zadrozny, LM, et al. 5-hydroxytryptamine (5HT)-induced valvulopathy: Compositional valvular alterations are associated with 5HT2B receptor and 5HT transporter transcript changes in Sprague-Dawley rats. Exp Toxicol Pathol. 2008;60(4–5):253–262.CrossRefGoogle ScholarPubMed
,Pharmapendium. https://www.pharmapendium.com.
,GVK Biosciences. http://www.gvkbio.com. Accessed 08. 05. 2010.
,Lhasa Ltd, DEREK. https://www.lhasalimited.org/index.php/derek/ Accessed 08. 05. 2010.
Cheng, A. In silico prediction of hepatotoxicity. Curr Computer-Aided Drug Design. 2009;5:122–127.CrossRefGoogle Scholar
,Multicase Inc. Bioactive software. http://www.multicase.com. Accessed 09. 05. 2010.
Ekins, S, ed. Computational Toxicology. Wiley-VCH, Hoboken NJ: 2007.CrossRef
Ekins, S . Predicting undesirable drug interactions with promiscuous proteins in silico. Drug Discov Today. 2004;9:276–285.CrossRefGoogle ScholarPubMed
Azzaoui, K, Hamon, J, Faller, B, et al. Modeling promiscuity based on in vitro safety pharmacology profiling dataChem Med Chem. 2007; 2:874–880.CrossRefGoogle ScholarPubMed
Whitebread, S, Hamon, J, Scheiber, J, et al. Broad-scale in vitro pharmacology profiling to predict clinical adverse effects. Am. Drug Discov. 2008;1(7):1–5.Google Scholar
Mitchell, JA, Warner, TD. COX isoforms in the cardiovascular system: Understanding the activities of non-steroidal anti-inflammatory drugs. Nat Rev Drug Discov. 2006;5:75–86.CrossRefGoogle ScholarPubMed
Dieterle, F, Marrer, E, Suzuki, E, et al. Monitoring kidney safety in drug development: Emerging technologies and their implications. Curr Opin Drug Discov Devel. 2008;11:60–71.Google ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×