Overview of Biomarkers in Disease, Drug Discovery and Development

Overview of biomarkers in disease, drug discovery and development

The pharmaceutical industry and the healthcare sector are both confronted with expensive technological innovation, escalating costs and pointed questions about productivity and efficiency.The parallels between the problems of producing new therapeutic agents and treating patients afflicted with poorly understood diseases are compelling. In part this is due to our limited ability to transform large datasets, (eg clinical data in diagnosis of disease) into meaningful information and knowledge. Knowledge of a disease process or impact of a drug in the treatment of disease is imperative for scientists, physicians and managers to make accurate and decisive decisions. One approach to enhance our understanding of such issues has emerged in the form of biomarker discovery, validation and utilisation. In this article an overview perspective of biomarkers is provided in the context of disease treatment and the drug discovery and development (DDD) process.A variety of issues are addressed including the sundry definitions and classifications of biomarkers. Furthermore, the practical matters to consider for biomarker discovery, the tools and technologies required, and what constitutes the optimal biomarker panel, are all discussed.

he Pharmaceutical Research and to regulatory agencies on an annual basis3. By Professor Manufacturers of America reported recent- Furthermore, both DiMasi4 and Bains5 have noted Stephen Naylor Tly that their members had spent $38.8 bil- the continued, rising cost of bringing a drug to lion on R&D in 20041. This reflects a 12% increase market, and their estimates range from ~$800 mil- from 2003 where the total budget was $34.5 billion to ~$1.15 billion respectively. lion, and this is in concordance with the ~13% Bains, in a topical and provocative article, high- annual growth rates expended on biomedical lighted a series of factors to consider for the drug research by both government and industry over the discovery and development (DDD) process to past decade2. However, this trend of ever increasing become more efficient and cost-effective5. He R&D costs does not appear to have halted the con- argued that poor science, technology and medical tinued decline in productivity, as seen in the decade- understanding contribute significantly to the bal- long decrease of new molecular entities (NMEs) looning cost and time constraints of the process. and biologic licence applications (BLAs) submitted However, he also made the salient point that poor

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Figure 1 The role of biomarkers in determining the Wellness Index (WI) of an individual. The WI ranges from 0 (Death) through to 100 (Perfect Homeostatic Control). Individuals as a function of age, environment and health will strive to maintain a biological equilibrium of through homoestatic control.The latter will be viable over some limited WI range as shown in the figure.Various biomarkers can be used to determine the progression from homeostasis into disease onset, progression and outcome

management decisions concerning borderline proj- of the $1.8 trillion healthcare industry in the US7, ects are a major contributing component. He auda- provides a good example. Innovative new tech- ciously announced that “implementing a ruthless nologies have not decreased costs, and disease success or die policy could half the cost and time to treatments in crucial health areas including oncol- get a drug to market”. Scientists are also not ogy, cardiovascular, CNS and immune-mediated spared in his analysis, and Bains suggested that diseases, have not improved dramatically over the another significant way to cut cost and time is for past decade. The same issues of large datasets not scientists to reduce “repeat” experimental steps at being efficiently transformed into knowledge of the any stage in the DDD process5. Overall, he sug- disease, hence inhibiting physicians from accurate- gests that poor decision-making by both scientists ly diagnosing and efficiently treating disease has and managers is at the heart of spiralling costs and not been readily realised (Figure 1). decreasing productivity. A critical question is how to adequately trans- In a subsequent article, Naylor6 contends that form Data ➔ Information ➔ Knowledge and apply both DDD managers and scientists must have high that to both healthcare and DDD decision-making quality, accurate, reproducible and interpretable processes. Many believe that part of the answer lies data in order to make unambiguous and decisive in the discovery, development and utilisation of decisions. Unfortunately, like all of us in the age of biomarkers. The hope is that biomarker data will the global communication village, managers and provide more predictive information and knowl- scientists are inundated each day with polybytes of edge about the changes in the biological processes data and information. They are ill-equipped to induced after perturbation with a therapeutic analyse such content, and efficiently utilise it in key agent. This should allow better predictive capabil- decision making processes. Most of the data and ity and decision-making on the part of scientists information remains unfiltered, unprocessed and and managers in the DDD process6. A similar unused. Our ability to transform argument could also be constructed around the diagnosis, treatment and management of disease8. Data ➔ Information ➔ Knowledge Definition and classification of is particularly limited, since we lack many of the biomarkers appropriate tools. How does one go about inter- This burgeoning field has attracted excitement, preting and utilising such data and information in enthusiasm and confusion as it begins to impact on making informed decisions? A parallel argument the DDD pipeline, as well many aspects of disease can also be made about shortfalls in the healthcare prediction, onset and progression9-13. In an sector and treatment of disease. The escalating cost attempt to bring some order to this diverse field,

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the Biomarkers and Surrogate Endpoint Working (SNPs) are not biomarkers. Finally, a group at Group (under the direction of the Office of the Bayer Corporation has enunciated a pragmatic def- Director, National Institutes of Health), has agreed inition of the term biomarker from the pharma- on both a definition as well as a classification sys- ceutical perspective16. A biomarker is “...a meas- tem for biomarkers14. The definition of a bio- urable property that reflects the mechanism of marker is: “A characteristic that is objectively action of the molecule based on its pharmacology, measured and evaluated as an indicator of normal pathophysiology of the disease, or an interaction biological processes, pathogenic processes or phar- between the two. A biomarker may or may not macological responses to a therapeutic interven- correlate perfectly with clinical efficacy/toxicity tion”. As this definition encompasses many ele- but could be used for internal decision-making ments of the pharmaceutical and biotechnology within a pharmaceutical company”. For the inter- industries as well as much of the biomedical and ested reader there is a website, organised and regu- conventional biological sciences, practitioners may larly updated by Cambridge Healthtech that pro- still be excused from being lost in the morass and vides working definitions for all aspects of bio- size of the biomarker space. marker applications in the DDD process as well as In a further attempt to bring clarity to the bio- disease biology and medicine17. marker arena, a classification system has also been At present the biomarker arena can be divided devised. Type 0 biomarkers purportedly measure the into two broad subsets10. The pharmaceutical and natural history of a disease and should correlate biotechnology industries have adopted them as a over time with known clinical indicators. Type I bio- wide ranging set of tools in monitoring and provid- markers indicate the intervention effect of for exam- ing information feedback in DDD (Type I-like bio- ple a therapeutic drug, whereas Type II biomarkers markers)12. They have impacted on determination are considered Surrogate Endpoint markers. This of clinically relevant targets, high-throughput Working Group has also given much thought to screening chemistries and preclinical ADME and defining Surrogate Endpoint as well as Clinical toxicology, to clinical ‘decision making markers’ at Endpoint. The latter is defined as: “A characteristic Phase I-IV. They are pervasively used throughout the or variable that reflects how a patient feels, func- entire DDD pipeline. However, in most cases the tions or survives. Clinical endpoints are distinct biomarkers of indication are used primarily in pat- measurements or analyses of disease characteristics tern recognition mode, using a set of unidentified observed in a study or clinical trial that reflect the markers, which may be genomic, proteomic, effect of therapeutic intervention”. Clinical end- metabolomic, or a combination dataset. In this points are considered the most reliable indicators of instance it is not necessary a priori to determine disease or therapeutic response, however a bio- biomarker constituent identities, since the pattern or marker can also rise to the status of Surrogate signature alone denotes specific biological activity. Endpoint. This is defined as: “A biomarker that is The second broad area where biomarkers are intended to substitute for a clinical endpoint. A sur- currently finding use is in the disease mechanism, rogate endpoint is expected to predict clinical bene- monitoring and prediction arena13. One area of fit (or harm) based on epidemiologic, therapeutic, focus is the determination of specific biomarkers pathophysiologic or other scientific evidence” and (gene, transcript, protein or metabolite) for either the reader if interested should peruse the original diagnosis of disease, or screening for a disease. discussion by this group14, as well as the excellent Such compounds can be considered as Type II-like review by Frank and Hargreaves9. biomarkers. In these cases it is important that a From a much more practical and focused per- single biomarker has been structurally identified spective the US Food and Drug Administration has and validated. However, a second approach is the proposed that: “A surrogate endpoint or marker is discovery of biomarker panels to indicate specific a laboratory measurement or physical sign [sic] disease states for predictive, early onset, progres- that is used in therapeutic trials as a substitute for sion, regression, treatment efficacy and diagnosis a clinically meaningful endpoint that is a direct of disease (Type 0-like biomarkers). It is interesting measure of how a patient feels, functions or sur- to note that in this latter situation, the expectation vives and is expected to predict the effect of the of a ‘good’ biomarker can range from a molecular therapy”15. In other words a biomarker is an indi- signature of structurally unidentified markers (sim- cator of change, and therefore fluctuates as a func- ilar in perspective to the pattern recognition mind- tion of time and biological influence. Hence as set of the pharmaceutical industry), to a ‘panel of pointed out by Zolg and Langen11, under this identified biomarkers’ specific for the disease strict definition single nucleotide polymorphisms process being evaluated.

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Zolg and Langen11 have recently described in considers what the intended outcome of the bio- some systematic detail, the biomarker discovery, marker discovery experiment is designed to validation and commercialisation process. They achieve. Experimental design is probably one of make the important point that the biomarker vali- the most overlooked, least-understood components dation phase needs to be precise and accurate, and of biomarker discovery. You need to consider the that it is time consuming and expensive. In part this appropriate number of samples to be analysed that is to ensure that statistical analysis is rigorous and will provide statistically significant data outcomes. that a receiver-operator characteristics (ROC) plot Adequate controls are a very necessary element in to determine specificity and sensitivity can be per- the design of such studies. One needs to consider formed. Furthermore, other authors have also whether a global or targeted analysis is appropri- noted the underlying complexity and time-consum- ate, as well as whether tissue or/and body fluid ing nature of validating biomarkers for routine use. should be analysed. This has been discussed in some depth by Frank 2. Sample quality. The old adage of ‘garbage in, and Hargreaves9 as well as by De Meyer and garbage out’ when applied to analysis of biological Shapiro18. As noted by the former authors: “The samples is particularly relevant in biomarker dis- standard concepts of test-retest reliability and valid- covery. The quality of samples analysed will ulti- ity apply with equal force to clinical biomarkers as mately determine the quality of biomarkers pro- they do in any [classical, standard] assay system”. duced. A number of factors must be taken into They also note that rigorous standards and proto- consideration. For example a clear lineage and ade- cols are already in place for the latter and therefore quate care for animals is necessary, whereas in the provide a lattice framework for the former. They case of human samples, history, outcomes and stor- also ruefully and correctly note that: “The work age conditions are all very important. In particular required to establish the reliability and validity of a one must also consider whether to pool samples or new biomarker should not be underestimated… analyse individual samples. Most practitioners and needs planning for each combination of clinical today tend to agree that the intrinsic biological indication and mechanism of action”. For example variability present in individual samples contains Type 0 biomarkers can be validated longitudinally, important information, and provided that you in a well-defined patient population against a “gold have the appropriate informatics and biostatistical standard clinical assessor”. Type I biomarkers tools, pooling is not appropriate. In the case of het- should be validated in parallel with the drug candi- erogeneous tissue (eg brain) one must determine if date, and Type II biomarkers “must be relevant you will analyse the mix of cellular material, or both to the mechanism of action of the drug and to specific cell populations which can be acquired the pathophysiology of the disease”. using laser capture micro-dissection. At a more refined level, do you analyse the content of specif- Practical biomarker discovery ic organelles by using biological sample prepara- and validation tion techniques? All such questions are determined As noted above, biomarker discovery and valida- by the focus of the study, and biological indication tion are active but emerging fields of endeavour. of the biomarkers being sought. Definitions and classification of biomarkers are 3. Technology platforms. There has been tremen- still being discussed and debated. In addition, the dous developments in -omic platform capability constituents of the optimal biomarker or biomark- over the past decade. However there still remain a er panel are still controversial and not clearly number of concerns. Expression profiling has defined. Furthermore, there are numerous practical matured into a stable, commercially available issues and limitations that have to be considered. platform technology. But questions continue to They include experimental design, biological sam- arise about the precision and reproducibility of ple quality and variability, technology platform this approach. In the differential proteomic and capability, paucity of good ranking and predictive metabolomic analyses of complex mixtures, a modelling algorithms, lack of context in disease number of issues still need to be addressed. One of and DDD process, limited use of knowledge assem- the major limitations of current technologies bly tools, lack of consideration of global initiatives (predicated on chromatography and mass spec- in biomarkers of disease, company versus public trometry) is the limited measurable dynamic range databases, cost-benefit of technologies, and ulti- (typically 104). Given that dynamic range can mately a poor understanding of the potential for vary from 106 to 1010 in biological tissue and flu- reimbursement/or analysis of value of biomarkers. ids, this creates significant problems in terms of 1. Experimental design. It is imperative that one breadth of coverage and limited sensitivity.

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Additional problems involve limited throughput world of biomarker ranking/prioritisation an capability and limited automation. Precision, and alphabet soup of different approaches exist includ- reproducibility as well as accurate quantitation ing SNR, SVM, t-test, POOF, Ecombo and step- are also issues that are still being addressed. In the wise LDA. Unfortunately, many of these are cus- case of imaging, the problem of limited through- tomised approaches, and hence there are no unify- put is still an issue. Finally, in systems biology ing standards in the biomarker field. Furthermore approaches developing integrated platforms to global databases are still only being considered and carry out such analyses are still in their infancy20. discussed, but most remain proprietary in the pri- 4. Informatics and databases. The ability to inte- vate sector. Finally, the data visualisation tools grate data from different platforms is not a available today continue to develop at a pace, but straightforward procedure. To date only a limited are also still in their infancy. number of Companies such as Ingenuity Systems 5. Economics. Over the past two years there have (Mountain View, CA, USA), Gene Network been a number of conferences on biomarker dis- Sciences (Ithaca, NY, USA), Entelos (Foster City, covery and validation (see, for example, Cambridge Ca, USA), BG Medicine (Waltham, MA, USA), and Healthtech Institute, www.healthtech.com; or IBC, Icoria (Raleigh-Durham, NC, USA) as well as aca- www.IBCLifeSciences.com) Many focus on the demic Institutions such as the Institute for Systems important -omic platforms used to undertake bio- Biology (Seattle, WA, USA) and Max Planck marker discovery. However, a number of speakers Institute (Heidleberg, Germany) have such capabil- have made the point that “while there is genomics, ity. The algorithms are proprietary and to date transcriptomics, pharmacogenomics, proteomics there is only a limited number of commercially and metabolomics, the only really important -omics available tools (see, for instance, Ingenuity, is ECON-omics”! This comment from a business www.ingenuity.com). In the rapidly developing perspective is most appropriate and timely. The

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Figure 2 The Decision Wheel of Biomarker Discovery.The issue of what constitutes the optimal biomarker(s) is still an area of some strident debate and discussion, in part because biomarkers serve a multitude of purposes. However, one can envisage a relatively simple, compartmentalised series of modules that make up the ‘Decision Wheel of Biomarker Discovery’.At each stage a careful and thoughtful decision has to be made to address the key issues raised within each module.The ‘Decision Wheel’ is designed to systematise the process of determining the optimal biomarker(s) for the scientific question under scrutiny

issue of reimbursement for biomarkers is a quag- -Omics and -ics of biomarker mire, mired in the political debate of escalating technologies healthcare costs in both North America and Disease biology and more specifically the DDD Europe. The conventional diagnostics marketplace process have historically suffered, from a paucity of provides some background for consideration of the information. This has been predicated on the tech- monetary value of biomarkers. However, who will nical difficulties associated with obtaining mean- actually bear the cost of discovery, and how that ingful measurements on biological systems (eg might be reimbursed is not so clear. In part it will be organisms, organs, tissue, cells or organelle) under determined by the role of the biomarker and its use. investigation6. Ultimately, this has resulted in limit- For example, the use of biomarkers in the pharma- ed data output and hence information content. ceutical industry is somewhat more straight for- However, the advent of gene expression arrays pio- ward, since the intrinsic value of biomarkers is to neered by Brown21 in the early 1990s and commer- reduce the approximately $800 million-$1.15 bil- cialised by Affymetrix Inc (Santa Clara, CA, USA) lion needed to bring a drug to market. forged the ‘decade of measurements’ which begat Unfortunately it is not so clear cut as to the value of numerous high throughput analytical tools and biomarkers in monitoring disease processes. technologies. The consequence of this ‘Omics However, in that context of how one might go Revolution’ has been the development of platforms about actually valuing biomarkers has been ele- that now routinely produce copious and substan- gantly discussed by Ferber19 in a recent paper. He tial, genetic, genomic, transcriptomic, proteomic, discusses the use of the Pearson Index (a normalised functional proteomic and metabolomic datasets22. measure of the financial value of a drug develop- In a concomitant timeframe, there was also an ment project) in the context of using biomarkers as explosive growth in the -ic technologies, such as tools in acquiring additional information about the informatics, bioinformatics and biostatistics. These process. He concludes that: “Economy makes us try tools enable the acquisition, manipulation and stor- to obtain the most valuable, albeit still incomplete age of large datasets, as well as mining them for information with a limited investment. It is in this new information and knowledge23,24. context... that biomarkers play their role”. The development of such technologies has enabled

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the emergence of biomarker discovery efforts. The based platform, www.ciphergen.com); diaDexus References platforms (hardware and software) now available (oncology biomarker kits, www.diadexus.com); 1 GenomeWeb Staff Reporter. include the existing -omic technologies, as well as the Genedata (software, www.genedata.com); Icoria Pharma spent $38.8B on R&D in 2004, a 12% jump; integrative analysis of systems (commonly referred to (systems biology platform, www.icoria.com); breakdown on genome as systems biology, pathway or network biology, or Lipomics Technologies (lipid biomarkers, spending soon. GenomeWeb panomics)6,20. Such discovery platforms, which typ- www.lipomics.com); Metabometrix (metabolite (www.genomeweb.com) ically analyse molecular components, commonly patterns, www.metabometrix.com), Molecular 2/18/05. utilise genetic linkage analysis, expression arrays, Staging (DNA amplification, www.molecularstag- 2 Booth, B and Zemmel, R. Prospects for productivity. chromatography coupled with mass spectrometry, ing.com); Rules-Based Medicine (multiplexed Nat. Rev. Drug Dis. 3: 451-456 NMR and other sensitive detection devices such as assays, www.rulesbasedmedicine.com) and (2004). electrochemical and laser-induced fluorescence detec- Surromed (nanobeads and mass spectrometry, 3 FDA Federal Drug tion. However, a wide variety of other approaches www.surromed.com). This is not a comprehensive Administration (FDA), are also used that includes incorporation of conven- list, but does provide some of the major private sec- Department of Human Health and Services. Challenge and tional clinical chemistry measurements, all forms of tor participants in biomarker discovery efforts. opportunity on the critical imaging from immunohistochemical staining to The development of tools and technologies, as path to new medical products. NMRi, to whole cell analysis using flow-cytometry well as innovative new research in biomarker dis- April 2004 (www.fda.gov/oc/ approaches. In order to mine and exploit the data covery is vibrant and active. This is in stark con- initiatives/criticalpath/). acquired on such diverse platforms a panoply of data trast to the actual validation and use of new molec- 4 DiMasi, JA, Hansen, RW and Grabowski, HG.The price of handling tools are required. They include data pre- ular signatures, individual biomarkers or biomark- innovation: New estimates of processing software to subtract out baseline devia- er panels. In part this is simply due to temporal drug development costs. J. tions, as well as align individual data files. A broad events and participant foci. Many of the necessary Health Econ. 22: 151-185 array of biostatistical tools is in use to identify spe- tools and technologies necessary for biomarker dis- (2003). cific cohorts of individual samples from a set of covery have only recently become available, at 5 Bains,W. Failure rates in drug discovery and analyses and include principal component analysis least when used in a concerted manner. development: will we ever get (PCA) and discriminant analysis (PCDA). Prioritising Furthermore the issue is compounded by the any better? Drug Discovery individual biomarkers into panels based on fold- underlying complexity and time-consuming nature World 5: 9-18 (2004). change and significance (Pearson Coefficient) of validating biomarkers for routine use9,11,18. It is 6 Naylor, S. Systems Biology, requires a suite of conventional statistical approach- paradoxical to note that the tools and technologies information, disease and drug discovery. Drug Discovery es including ANOVA, t-test and Kolmogorov- needed to undertake such tasks in the validation World 6: 23-33 (2005). Smirnov as well as more recent developments such as process are for the most part already available. 7 Mattera, MD. Memo from support vector machine analysis. Data visualisation, They include expression arrays, protein arrays, the editor.A way to curb storage and retrieval packages are also critical to high throughput immunoassays and conventional healthcare costs? Medical have in order to carry out such analyses. In addition, statistical and epidemiological analyses. Indeed, Economics December 3rd, 2004, (www.memag.com/ given the plethora of platforms used to acquire data, there is a reasonably well-defined paradigm in memag/article). data integration and correlation (linear and non-lin- place to validate biomarkers, once they exit the dis- 8 Morel, N et al. Introduction ear) capability are essential features to have in the covery phase. The compounding issues are the to Systems Biology-A new biomarker software toolbox. Finally, tools to extract fledgling state of biomarker discovery as well as approach to understanding knowledge from data are required. Such tools “ren- the added complexity of analysing highly variable disease and treatment. Mayo Clin. Proc. 79: 651-658 (2004). ders knowledge derived from both structured and population samples. 9 Frank, R and Hargreaves, R. unstructured sources into a machine-readable for- Clinical biomarkers in drug mat”25. For an excellent overview of the technolo- What is the optimal biomarker? discovery and development. gies employed in biomarker discovery the interested As discussed above, the quality of biomarker discov- Nature Drug Discov. 2: 566- reader should peruse the report written by ery data has the potential to dramatically impact 580 (2003). 10 Naylor, S. Biomarkers: Rubenstein entitled ‘Post-Genomic Biomarkers: both the DDD process as well as disease biology. In Current perspectives and Revolutionising Drug Development and the former case, the pecuniary effect could be signif- future prospects. Expert Rev. Diagnostics’26. icant if it leads to better information, knowledge and Mol. Diagn. 3: 525-529 (2003). A number of companies offer -omic and -ic tech- decision-making on the part of scientists and man- 11 Zolg, JW and Langen, H. nologies and capabilities for biomarker discovery agers. In the latter case decisions affecting patient How industry is approaching the search for new diagnostic and they include Aclara (chemistry and microflu- health and well being could also be improved dra- markers and biomarkers. Mol. idics, www.aclara.com); Affymetrix (expression matically if physicians had the appropriate tools and Cell. Proteomics. 3: 345-354 arrays, www.affymetrix.com); BG Medicine (inte- information on how to treat the complex and subtle (2004). grated omic platform, www.bgmedicine.com); infringement of disease on the patient (see Figure 1). Biosite (phage display platform, www.biosite.com); In both cases, an efficient process flow of Data ➔ Caprion (protein platform and software, Information ➔ Knowledge should afford better deci- www.caprion.com); Ciphergen (mass spectrometry- sion making in both DDD as well as the treatment of Continued on page 29

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disease. All this is predicated on the quality of the the rigour of validation is determined by whether Continued from page 27 data produced in the biomarker discovery phase. this is an internal process (eg toxicity of drug in Hence how does one go about determining what animal), or the biomarkers are used as part of a kit 12 Colburn,W.A. Biomarkers in drug discovery and constitutes the optimal biomarker(s)? (eg disease diagnosis). development. From target The issue of what constitutes the optimal bio- 10. Validation and utilisation – the biomarkers identification through drug marker(s) is an area of considerable debate and dis- are subject to validation predicated on the answer marketing. J. Clin. Pharmacol. cussion. There is no one widely accepted answer to to module9. 43: 329-341 (2003). this question, since biomarkers serve numerous The various component modules of the 13 Trull,AK et al (Eds). Biomarkers of Disease.An purposes. However, one can envisage a relatively ‘Biomarker Discovery Decision Wheel’ (Figure 2) evidence-based approach. simple compartmentalised series of modules that are still a source of vigorous debate. Many practi- Cambridge University Press, make up the ‘Decision Wheel of Biomarker tioners still argue that a molecular signature is per- Cambridge, UK. 2002. Discovery’. This is shown in Figure 2, and consists fectly acceptable, whereas others dismiss such an 14 Biomarker Definitions of the following: opinion as shortsighted. In part the latter group Working Group. Biomarkers and surrogate endpoints: argues that biomarkers are markers (distinguish- Preferred definitions and 1. Scientific question – the biological context should ers) of biological processes, hence it is imperative conceptual framework. Clin. be defined by the scientific question being posed. Also that such markers be identified. Certainly, if bio- Pharmacol.Ther. 69: 89-95 is it a hypothesis or discovery driven endeavour? markers are to be used in a meaningful way to (2002). 2. Define biomarker purpose – within the context facilitate decision-making processes in DDD, as 15 Temple, R.Are surrogate markers adequate to address of the scientific question under consideration, what well as treatment of disease as discussed here, then cardiovascular disease drugs? is the required output from the biomarker dataset? it would appear that identification is of paramount JAMA 282: 790-795 (1998). For example, are the biomarkers being used in a importance to ensure the highest quality data and 16 Lathia, CD. Biomarkers and simple go/no go decision making process, or are information. However, it is certain that such surrogate endpoints: How and they being used to understand a mechanism of bio- debate will continue over the next 1-2 years, as the when they might impact drug development. Disease Markers logical action? field develops. 18: 83-90 (2002). 3. Experimental design – predicated on modules 1 17 Cambridge Healthtech; and 2, issues such as what is the statistically signif- Conclusions www.genomicglossaries.com/c icant number of samples needed, appropriate con- The discovery, validation, commercialisation and ontent/biomarkers.asp trols (both positive and negative). use of biomarkers continues unabated in 2004-5. 18 De Meyer, G and Shapiro, F. Biomarker development:The 4. Organism/tissue/cell or body fluid selection – Active programmes are in place across the DDD road to clinical utility. Current the scientific question and the information needed pipeline driven by pharmaceutical and biotechnol- Drug Discovery May: 23-27 from the biomarker output, will determine the ogy companies. There are an increasing number of (2003). selection of biological system to be studied. For well attended biomarker conferences that provide 19 Ferber, G. Biomarkers and example, a simple prognostic test for pancreatic a forum for stimulating debate and discussion proof of concept. Methods Find. Exp. Clin. Pharmacol. 24 cancer might indicate a blood or urine analysis. about the fundamentals as well as the practical (Supplement C): 35-40 (2002). However, disease mechanism might require either aspects of biomarker discovery and validation. 20 Naylor, S and Cavanagh, J. animal or human biopsy samples. This augers well for the future of this fledgling but Status of systems biology-does 5. -Omic/panomic/imaging/clinical chemistry/ rapidly growing field of endeavour. In particular it have a future? Drug physiology/systems biomarker selection – often- spirited debate over the past 2-3 years has clearly Discovery Today-Biosilico 2: 171-174 (2004). times, given sample size, cost and time factors, one helped to refine working definitions of biomarkers 21 Schena, M et al. must select which molecular class of markers or as well as sub-classifications of various types of Quantitative monitoring of determine if imaging will provide more pertinent biomarkers17. However, at present the future of gene expression patterns with information about the process under investigation. biomarkers appears to be tinged with a mixture of a complementary DNA 6. Single biomarker or panel – does a single bio- excitement and uncertainty. In part that uncertain- microarray. Science 270: 467- 470 (1995). marker or a combination of biomarkers provide ty is predicated upon the fact that numerous disci- 22 Hood, L.A personal view of the most accurate and useful information about the plines and practitioners contribute to the biomark- molecular technology and how biological system? er effort. In order to provide direction, clarity of it has changed biology. J. 7. If panel: optimum number – what is the optimal goals and continued fortification of the biomarker Protome Res. 1: 399-409 number of biomarkers in the panel? Is it less than 10 foundation, more organisation needs to be brought (2002). 23 Ilyin, SE, Belkowski, SM and (economics) or more than 100 (information rich)? to bear. Such a diverse group of people and skill Plata-Salaman, CR. Biomarker 8. ID or molecular signature – does a simple molec- sets needs a variety of tools to hone and fashion discovery and validation: ular signature suffice, where none of the biomark- this industry. Several initiatives need to be consid- technologies and integrative ers have been identified, or does a well charac- ered. For example, in order to build on the excel- approaches.Trends Biotechnol. terised and identified panel afford more informa- lent progress of the Biomarkers and Surrogate 22: 411- 416 (2004). tion-rich content? Endpoint Working Group, a grass roots type 9. Validation question: commercial or internal – organisation needs to be formed. This can take the Continued on page 30

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Continued from page 29 form of a formal professional Society, or a more time-consuming but well defined validation steps. loose-knit structure, eg HUPO-like (organisation Finally, the regulatory bodies in North America, 24 Ilyin, SE et al. Functional focused on proteomics). This structure can provide Europe and Japan/SE Asia will play a significant informatics: convergence and integration of automation and a forum for broad based discussions on definitions, role in how the biomarker space continues to bioinformatics. as well as defining key elements of new tools and develop. At present the value of biomarkers in the Pharmacogenomics 5: 721-730. technologies required to advance the field. An DDD pipeline, as well as indicators of disease is the 25 Neumann, E and Thomas, J. annual meeting or meetings need to be scheduled subject of debate and scrutiny by such regulatory Knowledge assembly for the that augment the current meetings organised by authorities. It is important for the biomarker com- life sciences. Drug Discov. Today (Supplement) 7: S160- professional conference companies such as CHI or munity to continue to educate and debate the S162 (2002). IBC. Consideration of consortia formation is also authorities, since the latter’s decisions will impact 26 Rubenstein, K. Post- something that needs to be discussed, particularly significantly on the economics of value of bio- Genomic Biomarkers: in regard to biomarker databases, nomenclature markers in the future. It is an exciting future, that Revolutionizing Drug and data visualisation. needs help in defining where biomarkers go and Development and Diagnostics. (2003) DM&D Publications, The development of new tools and technologies the importance of them in the future. The potential Westborough, MA, USA. that impact on the biomarker space will for the role of biomarkers in helping the decision-making (http://www.drugandmarket. most part be developed in the respective -omic are- process in patient treatment, as well as DDD is a com). nas. For example the issue of reproducibility, quan- very real possibility. However, at present there are titation, sensitivity enhancement and high through- few concrete examples and there are still some put capability in both proteomic and metabolomic questions as to their true value! DDW analyses will be addressed by those respective scientific communities. However, a key area that does need to be addressed by the biomarker practitioners is how to rapidly and reliably integrate data from different platforms. The value of a biomark- Professor Stephen Naylor is currently Adjunct er panel containing genes/transcripts, proteins and Professor of Genetics and Genomics at Boston metabolites is at present unknown. We need to University of Medicine (Boston, MA, USA), as well address and understand if and why a composite as a Visiting Faculty Member in the Division of panel is more valuable (scientifically, information- Biological Engineering at MIT (Cambridge, MA, content and economically) than individual panels USA) and a Faculty Member of the Computational of genes or proteins or metabolites alone. Systems Biology Initiative (CSBi) also at MIT. He Furthermore there will be significant debate in the is the former Chief Technology Officer, and Senior future as to the advantages of genes versus proteins Vice-President for Research at Beyond Genomics versus metabolite panels. Which type of con- where, in conjunction with his colleagues, he built stituent component will provide the most informa- the world’s first integrated systems biology plat- tion about the process being investigated? Finally form, consisting of both analytical, bioinformatic and more near term, the issue of whether a molec- and knowledge assembly capability. Previously he ular signature, an individual biomarker (diagnos- was the founding Director of the Biomedical Mass tic) or panel of identified biomarkers is the best Spectrometry and Functional Proteomics Centre at approach as a final product clearly needs to be the Mayo Clinic. In addition he was Professor of debated. The answer to this conundrum is at pres- Biochemistry and Molecular Biology and Professor ent not clear, since who you ask will dictate the of Molecular Pharmacology and Experimental expediency of the response, and clearly the regula- Therapeutics. He was also Adjunct Professor of tory agencies such as the FDA will certainly (and Clinical Pharmacology, as well as Biomedical correctly) weigh in on this discussion. Engineering (Molecular Biophysics) at the Mayo As the field continues to develop one will see Foundation. Stephen received his PhD from continued concerted efforts from individuals from Cambridge University (UK) in biological mass very different disciplines. For example, as the bio- spectrometry, completed post doctoral work at marker discovery engine becomes more refined and MIT (USA) and served as Associate Director of capable, integration with the knowledge assembly Mass Spectrometry at the MRC Toxicology team to put the biomarkers into biological context Institute in London. Professor Naylor also serves will be essential. This latter event is in effect a pre- as a consultant to a number of analytical, pharma- validation step, since it places the biomarker com- ceutical and biotechnology companies, has pub- ponents in the biology of the system under study. lished more than 225 research papers, has filed a The pre-validation step should then provide a qual- number of patents and made more than 600 pre- ifier prior to sending on the biomarkers for the sentations at seminars worldwide.

30 Drug Discovery World Spring 2005