Reducing attrition in drug discovery: The role of biomarkers
8
SHARES
Posted: 20 June 2011 |
The development of most diseases is often attributed to the dysfunction of the activities of key proteins involved in biological processes and their modulation by a therapeutic agent is considered to offer the potential to alleviate the disease state.
The development of most diseases is often attributed to the dysfunction of the activities of key proteins involved in biological processes and their modulation by a therapeutic agent is considered to offer the potential to alleviate the disease state. However, prior to discovering a therapeutic agent, it is usually necessary to identify and validate that a particular protein is the underlying cause of the disease. It is often the case that a single target is implicated as being the cause of more than one disease. This suggests that particular focus needs to be paid to validating these targets for drug discovery purposes as many experimental drugs that are designed to modulate the activity of a specific protein often fail to exhibit efficacy during clinical trials. The role that biomarkers can play in reducing attrition observed in drug discovery will be discussed in this article.
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The discovery of therapeutic agents in drug discovery is a time consuming, expensive and risk averse process. A recent analysis that can be generally applied to the drug discovery process suggested that more than 24 target-to-hit projects are required in order to deliver a single marketed therapeutic agent1. Further analysis was made by categorising the attrition in relation to each of the well known milestones of the drug discovery process. Approximately half of the experimental drugs failed to progress from Phase I to Phase II suggesting that despite the rigorous evaluation of the experimental drug in the pre-clinical stages, safety related issues were a major contributor to their attrition. Of those that did not have any safety related issues, two-thirds of the experimental drugs still failed to progress from Phase II to Phase III, suggesting that they did not demonstrate efficacy in the primary disease indication. Likely reasons for this attrition include the possibility that the experimental drug undergoes metabolism, its mechanism of action may vary, use of sub-optimal experimental drug dosage, and in some cases the presence of slow and/or non-responding patients. Even if the experimental drug is shown to act upon the intended target in patients but does not lead to efficacy, it is also possible that the target is not a valid one for therapeutic intervention2. Thus, a large number of experimental drugs have been developed to modulate the activities of their respective targets and progressed to the clinical stages of drug discovery, fail to demonstrate efficacy.
A major reason for this lack of efficacy is that the targets against which the experimental drugs were developed were inappropriate and poorly validated with respect to being the root cause of the disease. The best validated targets are likely to be identified as the result of extensive studies of disease biology that may have taken many years to accomplish and the best assessment for validating a particular target from a drug discovery perspective would come from the existence of a therapeutic agent that has successfully been shown to yield clinical benefit. Many of the experimental drugs that enter the clinical trials result from high throughput screening campaigns that make use of assays in which the activity of the target of interest is measured in isolation or in a cellular context, both of which tend not to resemble the target’s physiological environment. Those hits that are optimised and eventually progressed to the clinical trials often fail to yield efficacy or translate their activities in vivo and are a cause of significant attrition in drug discovery3.
One approach that is being explored with the aim to reduce this attrition is to make more use of biomarkers in pre-clinical drug discovery4-10. This is becoming possible in a large part due to the advances in technologies such as genomics, transcriptomics and proteomics which allow the rapid profiling of patient derived samples11-14, in addition to already implemented ADME profiling in drug discovery15. There are major trans-national initiatives investigating this and a notable example is the Innovative Medicines Initiative (IMI) which is Europe’s largest public-private initiative that has funded projects focusing on safety and efficacy with biomarkers being a key element of the projects16. Examples of projects that focus on biomarkers for a variety of disease indications are shown in Table 1.
Table 1 Examples of biomarker and translation research focused projects within the First Call of the Innovative Medicines Initiative
Project focus
Biomarker content
Non-genotoxic carcinogenesis
Identification of early biomarkers for more reliably prediction of compounds that have a potential for late cancer development thus allowing early prediction of potential for non-genotoxic carcinogenesis.
Qualification of translational safety biomarkers
Qualification of safety biomarkers for clinical use to help understand and translate preclinical data into clinic. Focus is placed on three target organs (kidney, liver and vascular system) for which new translational and clinical safety biomarkers will be developed.
Islet cell research
Diagnostic biomarkers for diabetes to improve the diagnosis and prognosis of beta-cell failure and for monitoring diabetes progression and treatment.
Biomarkers for vascular endpoints
Identification and validation of biomarkers that can provide information to make drug development studies more efficient and shorten clinical trials.
Pain research
Identification of biomarkers and elucidating different nervous system changes contributing to pain with a view to increase confidence in what are relevant and predictive measurements of pain.
Novel therapies in psychiatric
disorders
Validation of MRI-based paradigms and PET approaches as early and surrogate biomarkers for efficacy. Provide guidance for drug development and identify pharmacogenetic and proteomic biomarkers that can be used to stratify patients.
Understanding severe asthma
Identifying biomarkers from patient cohorts and biobanks for various patient populations in order to improve drug development.
The use of protein based biomarkers in pre-clinical drug discovery is becoming more commonplace using samples such as blood17 as it is already extensively profiled from patients undergoing experimental drug treatment. Thus, a wealth of information is already available from clinical trials that need to be exploited.
Biomarkers have, for a long time, been used for clinical diagnostic purposes, for example to measure the concentrations of sugar and cholesterol in blood samples and thus determining which treatment to prescribe to patients. However, their use in pre-clinical drug discovery is becoming more commonplace and this, to a large extent, is being driven by the advances in technologies which allow the rapid profiling of samples. As the origins of diseases are elucidated, the role of biomarkers will increase in the pre-clinical stages of drug discovery with the aim that these will aid the discovery of drugs that will produce the predicted benefits when transitioning them to a clinical setting.
References
Paul, S.M., Mytelka, D.S., Dunwiddie, C.T., Persinger, C.C., Munos, B.H., Lindborg, S.R. and Schacht, A.L. How to improve R&D productivity: the pharmaceutical industry’s grand challenge. Nature Reviews Drug Discovery, 9, 203-214, 2010
Overington, J.P., Al-Lazikani, B. and Hopkins, A.L. How many drug targets are there? Nature Reviews Drug Discovery, 5, 993-996, 2006
Kola, I. and Landis, J. Opinion: Can the pharmaceutical industry reduce attrition rates? Nature Reviews Drug Discovery, 3, 711-716, 2004
Colburn, W.A. Biomarkers in drug discovery and development: from target identification through drug marketing. Journal of Clinical Pharmacology, 43, 329- 341, 2003
Bassa, A.S., Cartwright, M.A., Mahona, C., Morrison, R., Snyder, R., McNamara, P., Bradley, P., Zhou, Y. and Hunterg, J. Exploratory drug safety: a discovery strategy to reduce attrition in development. Journal of Pharmacological and Toxicological Methods, 60, 69-78, 2009
Frank, R. and Hargreaves, R. Clinical biomarkers in drug discovery and development. Nature Reviews Drug Discovery, 2, 566-580, 2003
Peck, R.W. Driving earlier clinical attrition: if you want to find the needle, burn down the haystack. Considerations for biomarker development. Drug Discovery Today, 12, 289-294, 2007
Lewin, D.A. and Weiner, M.P. Molecular biomarkers in drug development. Drug Discovery Today, 9, 976-983, 2004
Ross, J.S., Symmans, W.F., Pusztai, L. and Hortobagyi, G.N. Pharmacogenomics and clinical biomarkers in drug discovery and development, American Journal of Clinical Patholology, 124, S29-S41, 2005
Chau, C.H., Rixe, O., McLeod, H. and Figg, W.D. Validation of analytic methods for biomarkers used in drug development. Clinical cancer research, 14, 5967- 5976, 2008
Obach, R.S. Baxter, J.G., Liston, T.E., Silber, B.M., Jones, B.C., Macintyre, F., Rance, D.J. and Wastall, P. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. The Journal of Pharmacology and Experimental Therapeutics, 283, 46-58, 1997
Zolg, J.W. and Langen, H. How industry is approaching the search for new diagnostic markers and biomarkers. Molecular and Cellular Proteomics, 3, 345-354, 2004
Kell, D.B. Systems biology, metabolic modelling and metabolomics in drug discovery and development. Drug Discovery Today, 11, 1085-1092, 2006
Bodovitz, S. and Joos, T. The proteomics bottleneck: strategies for preliminary validation of potential biomarkers and drug targets. Trends in Biotechnology, 22, 4-7, 2004
Wang, J. and Urban, L. The impact of early ADME profiling on drug discovery and development strategy. Drug Discovery World, 73-86, 2004
Li, J., Zhang, Z., Rosenzweig, J., Wang, Y.Y. and Chana, D.W. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clinical Chemistry, 48, 1296-1304, 2002
About the Author
Sheraz Gul is Vice President and Head of Biology at European ScreeningPort, Hamburg, Germany. He is responsible for the management and development of Medium and High Throughput Screening activities for academic partners across Europe. He has 12 years research and development experience in both academia (University of London) and industry (GlaxoSmithKline Pharmaceuticals). This has ranged from the detailed study of catalysis by biological catalysts (enzymes and catalytic antibodies) to the design and development of assays for High Throughput Screening for the major biological target classes. He is the co-author of numerous papers, chapters and the Enzyme Assays: Essential Data handbook.
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