the evolving role of biomarkers - and cross-industry issues. ... trials process for cardiology,...

The evolving role of biomarkers Focusing on patients from research to clinical practice

Life Sciences and Pharmaceuticals

IBM Institute for Business Value

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industry-specific and cross-industry issues. This executive brief is based on an

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IntroductionThe use of biomarkers in BioPharma R&D and diagnostics will enable more precise, predictive and preventive clinical care. Biomarker-enabled R&D is evolving into a new discipline with a strong patient focus. Many organizations that believe in biomarker-enabled R&D are investing in biomarker technology, establishing new departments and even dedicating executive positions to leverage biomarkers. They are also devel-oping methods to validate biomarkers. Many leading companies, such as Novartis, Eli Lilly, Bristol-Myers Squibb, Pfizer and Bayer, have developed new R&D processes based on the use of biomarkers throughout the clinical trials process for cardiology, oncology and neurology.1

In the imaging field, biomarkers are increas-ingly being used non-invasively to assess patients’ localized disease progression and response to drug candidates. Biomarkers can help determine whether the drug reaches the target, whether it affects biological activity and, if it does, whether that effect leads to the desired clinical outcome.

With these trends in mind, this paper reflects insights and discussions from the IBM (Imaging) Biomarker Summit III held in January 2007. This is the third in a series of summits that began in 2005, but for the first time, participants explored a full spectrum of biomarkers, including imaging, genomics and proteomics. They discussed ways in which biomarkers can play a more vital role in clinical development decisions and the work

Patients expect approved drugs that work, are safe and are “right” for them. Biomarkers can help drug development focus more on defined subgroups of patients, thereby potentially increasing treatment efficacy and safety. Biomarker-enabled R&D is maturing into a new discipline that is addressing these goals with more precision. However, the science is outpacing widespread acceptance. The path toward acceptance by regulators and the medical community is through discovery and consistent validation of genomic, proteomic, in vitro and imaging biomarkers. Further collaborative efforts and powerful technology approaches can increase public confidence.

The evolving role of biomarkers

The evolving role of biomarkersFocusing on patients from research to clinical practiceBy Terry McCormick, Kathleen Martin and Michael Hehenberger

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that still needs to be done. They also debated data sharing – specifically, where to draw the line between openness and protection of proprietary intellectual property (IP). They also explored the critical role that information technology (IT) plays in enabling the success of applying imaging as a biomarker. These summits are catalysts for change; we have seen stakeholders across related industries and disciplines make tremendous progress in turning vision into action.

To achieve the ultimate vision of addressing unmet medical needs and reducing the costs of disease to society, full stakeholder cooperation is needed. This means the involvement of the BioPharma and healthcare industries as well as software partners, diag-nostic and device manufacturers, academic researchers, and U.S. and EU government agencies. Achieving this vision also requires a developmental model that thrives on more precise data that takes patient differences into account.

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Medical practitioners already use a patient-focused approach, but one based on treatment and diagnostic tools that were developed based on disease mechanisms rather than patient differences. As biomarkers become part of the entire developmental process, they can be used to help increase patient-focused precision in medical practice, leading to better risk assessment, diagnosis and treatment. Figure 1 shows how biomarkers can impact both clinical development and medical practice.

This paper describes the scientific trends related to biomarker use, barriers to biomarker acceptance and steps that can be taken to help improve acceptance across all stake-holders. These steps include:

• Enabling collaboration

• Increasing biomarker utility

• Shifting toward information-based medicine2

• Creating an interoperable environment.

If successful, these actions will transform both R&D as well as healthcare by enabling more predictive, precise and preventive patient care.

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FIGURE 1. Focusing on patients from research through clinical care.

Source: IBM Institute for Business Value.

• Shifts blockbuster model to more patient-focused development model

• Supports more efficient R&D methods

• Identifies risk groups and candidates of responders

• Identifies risk for toxicity • Addresses expensive, slow-

progressing diseases

Common value• Predicts safety• Identifies risk

and candidates of responders

• Monitors therapy

• Addresses diseases of aging population

• Assesses disease risk• Helps diagnose patients

early in disease process to reduce healthcare costs

• Provides prognostic tools

Biomarkers in clinical development help Biopharma create more effective therapies

Biomarkers in medical practice help improve outcomes and reduce cost to society

� The evolving role of biomarkers

The evolving role of biomarkersFocusing on patients from research to clinical practice

These common biomarkers have historically taken decades to become part of medical practice. For example, PSA is a biomarker for diagnosing and monitoring prostate disease, the most prevalent cancer in men. Figure 2 reflects the 30-year evolution of PSA, illus-trating how it took decades for PSA to evolve into an accepted biomarker and finally be used to help develop new therapies. PSA’s evolution and use reveals some common themes in a biomarker’s lifecycle.

Biomarker science progressing faster than acceptanceBiomarkers are already embedded into our language and medical care today. Cardiovascular risk can be assessed through blood pressure and cholesterol checks; Diabetic patients can test their glucose levels using one test – hemoglobin A1c (HbA1c) – that provides glucose levels from the most recent two weeks. Liver function tests (LFT) assess liver toxicity and prostate-specific antigen (PSA) assesses prostate cancer risk and disease status.

Preclinical exploratory

Prospective screening

Cancer control

FIGURE 2. Lifecycle of the prostate cancer biomarker, PSA.

Sources: Bartsch, G., F. Frauscher, and W. Horninger, Dept. of Urology, University of Innsbruck, Austria, “New efforts in the diagnosis of prostate cancer,” IBM (Imaging) Biomarker Summit III, January 2007, (PSA evolution and development themes); Hara, M, et al., The Japanese Journal of Legal Medicine, Volume 25, page 322, 1971, (PSA discovery); Watanube, H, et al., “Development and application of new equipment for transrectal ultrasonography,” Journal of Clinical Ultrasound, Volume 2, page 91, 1974, (studied through imaging); IBM Institute for Business Value analysis.

Theme #1: Early stages of development, PSA was informative• PSA discovered �97�• �974: prostate cancer studied

through imaging• Focus on understanding underlying

disease

Theme #2: Conundrum – What is the value of diagnostics for which there is no therapy?• �990’s debate on PSA’s usefulness

in identifying disease with no drug therapy

• PSA use grew despite up to 75 percent false positives

• Biopsies continued on patients without cancer

• Used as a predictive marker to diagnose early enough to assess effectiveness

Theme #3: Perseverance can prevail, but innovation and collaboration must shorten timelines• Reduce mortality in prostate cancer

– long term Tyrol screening reduced mortality by 54 percent compared to Austria average

• Combine biomarker indicators• Partner with other experts to improve

clinical outcomes• PSA velocity (rate of increasing

concentration) is a better risk indicator than original PSA

Clinical assay and validation

Retrospective longitudinal

1977: Food and Drug Administration (FDA) approves PSA for patients already

diagnosed

2007: “220 therapeutics emerging;” 100 in

Phase II; 20 on market

1994: PSA approved as predictive

indicator

1996-1997: Four new chemical entity

therapeutics approved for prostate cancer

2002-2004: Period and retrospective analyses

on survival

Biomarker development

PSA evolution

Industry stakeholders must work together to shorten the time between biomarker

discovery and assimilation into

everyday medical practice.

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These and related efforts produced great insights, which have resulted in 220 emerging therapies for prostate cancer.3 This progress came from 30 years of one biomarker’s evolution. The benefit of the PSA biomarker to society is clear. Let us hope the lessons learned can be applied to compress the evolutionary lifecycle of other needed biomarkers to far fewer years.4

Promising progress helps address unmet medical needs in neuroscience, cardiovascular disease and oncologyBiobanks are a rich source for identifying biomarkers across a wide range of diseases and treatments. Renowned medical centers across the world, such as the Karolinska Institute in Sweden and the University of British Columbia, have set up biobanks that provide information and resources for biomedical research in genetics, functional genetics and epidemiology.5 The biomarker boom has already benefited therapeutic areas like neuro-science, cardiovascular disease and oncology. Let us look at examples of the tremendous progress that is gaining acceptance and the promising work being done today that can help address unmet medical needs.

NeuroscienceNeuroscience requires minimally invasive procedures to see deep into the brain to understand both function and disease. Positron emission tomography (PET) now plays a vital role in measuring drug concentrations in target organs and tracking how and where drugs bind to a target that might serve as a biomarker. It is also important in visualizing targets, such as amyloid plaques hypoth-esized in triggering Alzheimer’s disease (AD).This is the most common form of dementia that affects over 12 million people and their

families.6 Genetic, neuropsychological and neuroimaging probes might predict AD devel-opment long before behavioral tests diagnose diminished function, which may reflect irrevers-ible damage. This is crucial since clinical trials otherwise would depend on enrolling patients with symptoms that may take decades to develop. Early diagnosis and treatment could forestall or even prevent disease progres-sion. Imaging biomarkers, including functional magnetic resonance imaging (fMRI), are addressing similar research challenges in schizophrenia, bipolar disorders/psychosis, Tourette’s syndrome, temporal lobe epilepsy psychosis, addictions to cocaine and alcohol, and restless legs syndrome.7

Cardiovascular (CV) There are promising biomarkers that address various types of vascular diseases, such as strokes and coronary heart diseases. In the past, stroke diagnosis involved measuring red blood cell leakage into the spinal fluid. This was invasive and mostly measurable after major strokes. Imaging biomarkers promise a more timely, less invasive approach to help diagnose and treat strokes caused by ischemic or hemorrhagic events in the early stages of disease to reduce the likeli-hood of damage and death. One proteomic program on cardio-vascular diseases identified 95 potential biomarkers out of 731 proteins using Matrix Assisted Laser Desorption Ionization/ Mass Spectrometry (MALDI/MS) and Electrospray Ionization Mass Spectrometry (ESI-MS). Another proteomic study of spinal fluid and plasma revealed new blood stroke biomarkers. Similar work is underway to address hemorrhagic versus ischemic condi-tions as well.8

5 The evolving role of biomarkers

Coronary heart disease is another area of great progress for biomarkers. Presenters at the IBM (Imaging) Biomarker Summit III noted various approaches including ultrasound probes to help study drugs for stopping or reversing plaque growth and reducing damage to surrounding vessel tissue. Proteomics is aiding in understanding the implications of related proteins associated with natural defenses, inflammation, growth and coagulation.9

OncologyOncology researchers are investigating a wealth of biomarkers to address risk, drug resistance and treatment effectiveness for many tumor types. Other biomarkers like human epidermal growth factor receptor 2 (HER2) help predict response and resistance in breast cancer. DNA resistance arrays are being used to predict drug resistance and guide patient treatments. That assessment is helping to predict the right therapy for patients with 85 percent accuracy for certain traditional chemotherapy treatments.10 New imaging tools are being used to assess anti-tumor activity across a wide range of tumors. These tools include: PET scan, MRI, dynamic contrast-enhanced MRI (DCE-MRI), DCE-computed tomography (DCE-CT) and fluorodeoxyglucose-PET (FDG-PET). All these biomarkers have made progress across a wide range of functional targets. Despite advances, more work is needed to validate these biomarkers as reliable tools, develop consistent international data standards and enable the co-development of better diagnos-tics and drugs.11

The power of many: The value of combining biomarker technologiesSingle modes of imaging are making signifi-cant progress, but another level of insight comes from combining different types of biomarkers or correlating results with tradi-tional clinical data. This approach can increase both the value of any single biomarker as well as the associated confidence level in using it. In one case study (see sidebar, Dual-purpose instruments), researchers used multimodal imaging to help prove a stronger link between animal findings and human experience in Huntington’s disease.

Dual-purpose instruments: Multimodal image reconstruction in neuroscienceThe Molecular Imaging Research Center (MIRC) along with two other imaging centers took on a project to address the difficulty that single-mode imaging has in defining activity in the central nervous system. They applied multimodal imaging approaches to better understand neurodegenerative diseases including Huntington’s disease.12

By merging imaging data with post-mortem information in preclinical and clinical studies, researchers were able to perform three-dimensional (�D) reconstruction. It allowed them to investigate the underlying biological pathways occurring in Huntington’s disease. These broken pathways contribute to patients’ eventual decline observed six years after cell transplantation. By overlaying functional (PET) and anatomical (MRI) imaging with anatomical (histology) and functional (autotrophy) data, they were able to improve the quantitative assessment of various brain structures, confirm the animal model and apply it to humans.13

Biomarkers are already benefiting many

therapeutic areas, but even greater value may

be realized as the industry begins to combine

multiple biomarker technologies.


Computational biology for analyzing large volumes of dataBiomarker data is complex and puts a tremen-dous burden on traditional analysis methods. Computational biology can guide math-ematical modeling and simulation techniques to study biological systems, but still needs to become more user-friendly and accessible.

Advanced computing harnesses large volumes of diverse sources and types of information. It also increases visibility across databases to seamlessly combine experi-mental, research and simulated data.

As part of IBM’s computational biology research, IBM Blue Gene® is also advancing analysis of new areas of biology, including proteins folding into their final 3D structures, drug candidates docking to target proteins, receptor function, imaging data reconstruction, and analysis processing (aligning imaging studies from the same or different modalities). Blue Gene’s speed and performance along with optimized software algorithms allow us to simulate tens of microseconds of these biological events.14

Another impressive breakthrough in multi-modal analysis of complex data is occurring in the biolibrary-enabled project in biomarker discovery supported by the Genome Canada Initiative in Applied Human Health Genomics at the University of British Columbia (see sidebar, Biomarkers in Transplantation Project). Stakeholders can build on these and other advances to strengthen biomarker discovery and validation, thereby, more powerfully supporting the development of new preven-tives and treatment and providing a deeper understanding of disease mechanisms.

Biomarkers in Transplantation Project: Stratified analyses of complex data to gain knowledge from multimodal biomarker data and biolibrary resources The Genome Canada Initiative in Applied Human Health Genomics at the University of British Columbia is capitalizing on a multidisciplinary, multinational team of clinicians, life scientists, computational scientists, ethicists and economists linked to the James Hogg iCAPTURE Centre (Imaging, Cell Analysis, and Phenotyping Toward Understanding Responsive, Reparative, Remodeling, and Recombinant Events). The biomarker project is dependent upon experienced biobankers and the project’s ethics-framed, SOP-enabled biolibrary. This project is identifying effective, minimally invasive biomarkers to predict and diagnose acute and chronic organ rejection in heart, kidney and liver transplant recipients, and predict their responsiveness to various therapeutic regimens. Researchers are examining the relation-ships among genomic, proteomic, metabolomic, phenotypic and environmental data and the presence of heart, kidney and liver rejection or other pathologies. To do this, they developed a common, semantic data model to link and analyze diverse types of data from transplantation databases, case report forms and other biomarker and clinical data sources. This work identified many early potential candidate biomarkers from thousands of mRNAs, peptides, proteins and metabolites. They have created a rather complete profile of genetic and translational information to gain new insights into organ rejection and treatment. Soon it is anticipated that the biomarker clusters of emerging predictive and diagnostic value will be broadly validated in large-scale clinical trials and then used to drive decisions and organ transplant management and policy.15


Resistance to using biomarkersWhile there is widespread recognition of biomarker value, scientific progress continues to outpace acceptance. Over the years, biomarkers have sometimes been the center of excessive “hype,” prompting excessive expectations. Also, biomarkers as surrogate endpoints have had some public failures when they were felt to be falsely reassuring or too alarming, creating general skepticism among some scientists. Resistance still hindering biomarker acceptance includes:

• Resistance to sharing data across inde-pendent efforts – Organizations may work on similar research or discover keystone advances yet resist sharing knowledge because they feel that doing so will jeopar-dize their competitive advantage. However, sharing information could help companies achieve greater overall progress or reduce costs by not having to work on efforts inde-pendently.

• Limited biomarker validation – Validation is critical for establishing biomarkers as reliable tools to support develop-ment, medical care, health policy such as the FDA’s critical path, and BioPharma investment decisions.16 The biomarker development and validation process is necessary but costly for one company to do in isolation. Innovation takes place in many organizations, and so stakeholders work redundantly on the same effort. Many collaborative forums exist, but these usually involve sharing “safe” information that really does not hasten overall progress.

• Need for new R&D models with greater precision and flexibility – The industry needs an R&D model with greater precision to improve pipelines, leveraging active clinical knowledge to offset the declining success in new drug development.17 Some R&D leaders are concerned that using an approach that targets treatment for limited patient groups decreases profits and increases research costs. Others recognize that this direction has already created value beyond costs and are building these capabilities into their new R&D models and tactics. For example, Herceptin is considered an effective targeted treatment for breast cancer.18 Targeted treatments could actually increase both the medical and economic success of a therapeutic.19

• Insufficient interoperability – Traditional data resides in disparate places that often do not easily connect. Factor in imaging biomarkers constituted by terabytes of data and you have a complex mix of data from which it is difficult to extract new insights. The path forward – interoperability – is a design and intent to have systems share information that relies on data standards and, more impor-tantly, semantics. Semantics use common vocabularies and business rules to relate clinical terms reported across different sources to find common meaning.

Despite scientific progress, biomarker

acceptance is lagging due to a general

reluctance to share data, limited biomarker

validation, outdated R&D model and insufficient interoperability among

collaborators’ IT systems and databases.


The path forward: Promoting biomarkers for a patient-focused marketBiomarkers can help translate patient-focused research into medical care with valuable precision. Figure 3 shows the steps that can be taken to achieve this goal.

Enable collaboration across stakeholdersMany participants at the IBM (Imaging) Biomarker Summit III agreed that biomarker collaboration has accelerated scientific advances, distributed cost of validation and increased confidence in using biomarkers. For biomarkers to be validated and accepted by the scientific community, companies must work together to support the research needed. We are already seeing BioPharma, vendors, government and academia working together, recognizing the need to share information.

Industry is expanding its view of IP to include unique knowledge of disease mechanisms, of which biomarkers play a part. In that respect,

biomarker research could represent a form of IP, and the inclination of for-profit organizations is to protect it. At the same time, there is a continuing debate on what IP could be shared so the benefits could more quickly address many of society’s unmet medical needs. Many existing forums share “safe” informa-tion, like insights on science, data standards and trends. New philosophies suggest that competitors can share more sensitive informa-tion within private, safeguarded discussions. Figure 4 describes the range of approaches discussed at the IBM (Imaging) Biomarker Summit III.

What would motivate a BioPharma company to share information more openly? Collaboration often makes biomarker validation more economically feasible than working indepen-dently. The risk of violating IP agreements should not be an issue because biomarker validation is not patentable. Collaboration helps decision making as researchers rely on validated biomarkers that can slash devel-opment time and costs in many diseases.

FIGURE 3. Creating patient focus through biomarkers.


Challenges

• Resistance to sharing data across independent efforts

• Limited biomarker validation

• Need for new R&D models with greater precision and flexibility

• Insufficient interoperability

Actions to promote biomarkers

• Enable collaboration across stakeholders: New philosophies accelerate new approaches for biomarker validation, innovation, development and sharing costs.

• Purposefully increase biomarker utility: Agree on validation framework for biomarkers to be part of pivotal decisions within development, medical care and health policy.

• Shift toward information-based medicine: Increase predictability of safety and efficacy to help target treatment based on more informative cohort data and other clinical information.

• Create an interoperable environment: Combine biomarkers with other clinical data. Agree and implement data standards and semantics (i.e., ontologies and rules).


Sharing information pre-competitively is becoming recognized as a way to feed the amount of published shared knowledge and improve productivity in developing new medical treatments (see Figure 5).

Two information-sharing approaches were debated at the IBM (Imaging) Biomarker Summit III: a Biomarker Consortium and a Radiotracer Clearinghouse (see sidebars, Biomarker Consortium and Broker for imaging biomarkers). 20

FIGURE 4.Different approaches that foster collaboration among competitors.

Proprietary view: What’s mine is mine


• Guard IP and share only with partners protected through contractual agreements

• BioPharma and Contract Research Organization (CRO) partnerships

• BioPharma to BioPharma co-development or co-marketing

• Third-party brokers help manage sensitive data and resolve security, privacy and data access for authorized parties

• Radiotracer Clearinghouse

• Pre-competitive arrangements that provide an open sharing environment are gaining interest

• The Foundation for the National Institutes of Health sponsors private/public partnerships (PPPs):- Biomarker Consortium- Genetic Association

Information Network (GAIN)

Data broker approachPre-competitive

arrangement

Desc

riptio

nEx

ampl

es

FIGURE 5.Pre-competitive collaboration can help expand published shared knowledge.


Today

Develop medical treatments

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Improved productivity in development of new medical treatments

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Published shared knowledge

Tomorrow

Pre-competitive space

Expandedpublished shared

knowledge

The pace of biomarker acceptance

is expected to increase with more

collaboration among industry stakeholders.

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Biomarker Consortium: A pre-competitive approach to collaborationThe Biomarker Consortium is a program sponsored by the Foundation for the National Institutes of Health (FNIH) to bring private and public partners together for open and fair discussions and to support the NIH vision.21 Its strategy is to create “harmonized approaches” to speed up biomarker value and formal use to promote research, regulatory approval, public health and more informed decisions. A governance committee upholds its mission and goals. The Consortium carefully develops policies to address IP concerns, data sharing, antitrust issues, grantee/contractor selection, confidentiality and conflicts of interest. The Consortium involves project-based collaborations that clearly define what each partner can contribute.

Currently, the Biomarker Consortium is focusing on three projects:

• Oncology: FDG-PET for lung cancer and lymphoma

• Neuroscience: Major Depressive Disorder – identifying its genomic biomarkers

• Metabolic diseases: Such as diabetes.

FNIH is also sponsoring the Genetic Association Identification Network (GAIN) and other initiatives in Alzheimer’s disease, osteoarthritis, imaging database and translational research.22

Broker for imaging biomarkers: The Radiotracer Clearinghouse (RCH) Stakeholders pursue biomarker development independently because current collaborations are not set up to protect highly valued IP. But advancing imaging biomarkers, such as radiotracers, at a faster rate is essential in therapeutic areas. This is particularly important where such biomarkers are rare or where only a small body of evidence exists to prove their value. Substantial evidence is seen in the central nervous system areas within Pharma and is growing in cardiovascular and oncology, where Pharma is establishing major collaborations with academic imaging centers and even establishing its own animal PET centers.

The RCH is a non-profit organization providing a solution to help fast-track drug discovery and development processes. The RCH was conceived with the aid of members of the American College of Neuropsychopharmacology (ACNP) and the Society for Non-Invasive Imaging in Drug Development (SNIDD) as a vehicle to enable Pharma and academia to share information on radiotracers for PET or Single Photon Emission Tomography (SPECT) imaging within an environment designed to protect all parties’ intellectual property.

Interactions within the RCH can vary between two extremes of privacy and public disclosure. At one end, members can choose to share information under strict confidence with disclosure among parties and no public disclosure. Participants can remain anonymous or reveal who they are if and when they feel comfortable. On the other end of the spectrum, they can share information with all parties involved, with the intent to publicly disclose information related to the biomarker, target or specific imaging study in a timely manner. The latter scenario may be covered under the activities of the RCH in its role as a Project with the Biomarker Consortium. (The Biomarker Consortium executive committee recently recommended RCH as a formal Project.) Prior to any interaction among parties, the rules of engagement will be established by the RCH facilitator and the pharma-ceutical companies or academic centers involved. They will determine the scope and timing of information shared throughout the process.23

Supporters believe that such a Clearinghouse could reduce duplication of radiotracer development globally, accelerate validation, reduce research costs and set a model for enhancing the use of non-diagnostic radio-tracers in general. This approach could also make radiotracers more available to academic institutions for governmentally funded research.24

�� The evolving role of biomarkers

These resources provide BioPharma companies with alternatives to consider that can help facilitate their drug development programs. In addition, they can foster new discussions to speed up the progress and acceptance of promising biomarkers.

Purposefully increase biomarker utilityAmong the participants, one thing was clear: having a validation framework was absolutely critical for widespread use of biomarkers. According to the FDA’s draft guidance for phar-macogenomic data submissions, a validated biomarker is one that is “measured in an analytical test system with well-established performance characteristics with an estab-lished scientific framework or body of evidence that elucidates the physiologic, pharmacologic, toxicologic, or clinical significance of the test results.”25 But the path there has not, as yet, been clearly defined.

Other stakeholders are using other defini-tions, but many are expecting the FDA to take the lead for the use of biomarkers in drug, discovery and disease management. Imaging and diagnostic measures will need

to be validated against certain standards and metrics for use in internal BioPharma decision making, clinical practice, clinical diagnostic claims and payer considerations (whether government or insurance) as well as for regu-latory purposes.

Biomarkers are becoming a foundation for information-based medicine in determining who should be treated, how and with what. For biomarkers to reach their full potential, alone or in combination, they must undergo their own development process. Biomarker development has lagged significantly behind therapeutic development because of scientific, economic and regulatory factors.26 It is important to accelerate biomarker development and to help biomarkers advance in parallel with thera-peutics, but, as noted in the conference, they must be tested with established therapies.27

As the confidence in a biomarker increases, BioPharma or doctors can apply it to weightier decisions that impact financial investment and patient care (see Figure 6). Early “infor-mational” biomarkers involve decisions in applying animal findings to human subjects,

FIGURE 6. Increasing role with increasing confidence.

Source: Adapted from Dr. H. Young, AstraZeneca, “Role of Imaging in Oncology Drug Development,” IBM (Imaging) Biomarker Summit III, January 2007.

DiscoverySurrogate evaluationCharacterizationDevelopment Demonstration Affirmation

Biomarker development

Biomarker qualification Surrogate validation

R&D discovery R&D development Post approval trials

R&D value chain

Sample biomarker progress Structural imaging - Response Evaluation Criteria in Solid Tumors (RECIST)

objective response and progression-free survival endpointsGlucose metabolism, PET

Hypoxia MRI, PET

InformativePredictive Validated

A widely accepted validation framework

is an essential element in building industry confidence

in biomarkers.

�� IBM Global Business Services

pharmacology and safety; later development involves decisions about dose-response for safety and efficacy and differences in metabolism. These later decisions also affect hundreds to thousands of trial participants and involve large investments, hence the importance of high confidence levels in a biomarker. The ultimate stage is when a biomarker is accepted by regulators as a surrogate for a clinical endpoint, and directly supports a drug filing.

New and validated biomarkers help develop more targeted therapy to transition develop-ment away from a treatment-based research model that some describe as trial-and-error. Biomarkers provide increasing value as companies move along the path from drug discovery to product launch because:

• Costs go up at each progressive stage.

• More knowledge is needed to reduce risks at progressive stages.

• Regulatory “proof” requires more rigor as one approaches approval “stage-gates.”

• Technique and technology must be “locked down” through the multiyear clinical phases.

As biomarker evidence increases, payers (whether government or insurance) may consider them for reimbursement. Adoption of new technology and innovation typically follows a certain sequence: Discovery Medical practice Development Health insurance.

Development and health insurance companies tend to adopt scientific advances more slowly because of the financial impact of investing millions of dollars for development and large-scale reimbursement for health insurance. Medical practice often begins using new

technologies sooner based on personal expe-rience in a tool or backing from respected groups or medical publications. Government or companies that pay for healthcare remain the primary gatekeepers for innovative medical products.28

Shift toward information-based medicineApplying biomarkers to the traditional block-buster model may have its benefits, but biomarkers offer a new level of precision and value in a transformed R&D model. They can make trials more economically feasible by improving patient selection and not including patients that have more known risk of toxicity or lack of efficacy. This is already being done in many pediatric studies and HIV trials.29 Figure 7 shows the role that biomarkers play in intro-ducing additional information from discovery and translating it into clinical care. Knowledge gained in clinical research and clinical practice can be fed back into earlier stages to better guide new product development.

Adaptive trials are also important to the new vision for drug development. These are clinical trials that are modified based on data analysis while the study is ongoing. Adaptive trials allow researchers to redirect participants to modify protocols, omit study treatments that appear ineffective or add more study participants who may respond to study treatment. Some believe this approach can reduce the duration, cost and size of trials by up to 30 percent.30 Biomarkers can help identify appropriate patient cohorts and help reduce the likeli-hood that participants will receive ineffective treatments. Support for this is growing among industry leaders, and adoption is likely to expand when the FDA develops more formal guidelines.31

�� The evolving role of biomarkers

Create an interoperable environmentAn interoperable environment accelerates connections across the internal organiza-tion and potentially with an organization’s partners and collaborators. To achieve this, companies need cohesive data standards to create a continuous flow of information for

timely decision making (see Figure 8). Global data standards, such as those developed by the Clinical Data Interchange Standards Consortium (CDISC), can help provide a consistent, universal foundation for sharing knowledge within their organization, with other organizations and across industries.32

FIGURE 8.Data standards and semantics enable continuous information flow across industries.


FIGURE 7. Biomarkers connect bench to bedside and create a continuous feedback loop for innovation.

Discovery and preclinical phases Clinical research phases Clinical research

“Omics” (e.g., proteomics, genomics, etc.) screening

based on cellular, physiologic models, driven by target

population analysis

Preclinical animal testing

• Better qualified compounds

• Patient enrichment strategies

Diagnostic tests

Biomarkers

Compounds

Patient samples Apply results to new trials

Source: Carini, C., “Biomarkers: Predictive Tools to Enable Translational Research,” IBM (Imaging) Biomarker Summit III, January 2007.

BioPharma

Research Development Healthcare

Healthcare

• HUPO PSI: Human Proteome Organization’s Proteomic Standards Initiative to define community standards for data representation in proteomics

• MAGE – MicroArray and Gene Expression standard developed by the Microarray Gene Expression Data Society to facilitate the exchange of microarray information among different data systems

• Life Sciences Grid standards developed by OGF (Open Grid Forum)

• HL7: Health Level Seven, hospital/clinical data standards

• CDISC standards: Clinical Data Interchange Standards Consortium develops the industry standards that support the electronic acquisition, exchange, submission and archiving of clinical trial data

• Pharmacogenomics standards: Joint initiative between CDISC and HL7, based on FDA guidance

• eCTD: Electronic Common Technical Document developed by ICH (International Conference for Harmonization) for electronic submissions

• HL7: Health Level Seven, hospital/clinical data standards

• DICOM: Digital Imaging and Communications in Medicine standards for medical imaging

• Standardized dictionaries – Snomed CT: (Systematized Nomenclature of Medicine Clinical Terms) and UMLS (Unified Medical Language System)

Biomarkers offer greater value when they are

part of a transformed R&D model – one that

is more adaptable, better integrated and

less dependent on creating mainstream

blockbusters.


IT architectures supporting biomarker-based R&D rely heavily on open data standards, such as the Study Data Tabulation Model (SDTM) and extensions of the JANUS data model, which was developed jointly by the FDA and IBM.33 Nascent, semantic data models will become important in providing common vocabulary and business logic for similar terms and meaning. These approaches along with middleware products provide the backbone for scalable IT architectures to support interoperability.

Companies can provide central views for their businesses by linking their existing systems with data that can be synthesized more easily.34 Data syntax is relatively easy to set up, but delivering semantically-rich, real knowledge is more difficult to achieve. Today we can integrate “omics” (e.g., proteomics, genomics, etc.) and imaging data, but combining semantics with approaches like service-oriented archi-tecture (SOA) can help industry participants access the volumes of data needed to bring new insights into disease mechanisms and treatment. Using SOA to assimilate biomarker data can also support growing ecosystems of partnerships with CROs and academic medical research centers.

CROs are responding to these challenges and adding imaging data management to their internal capabilities as they assist the BioPharma industry in leveraging needed data types for proving a medical hypoth-esis. However, significant IT challenges need to be addressed before such applications can become routine and accepted by both BioPharma and the FDA.

How to contribute to future biomarker useThere are several things that companies can do to contribute toward biomarker accep-tance. Consider these questions to guide your involvement:

• Are you involved in any private/public part-nership arrangements?

• How has your organization invested in biomarker development, validation or collab-oration?

• If your organization is involved in R&D, is it prepared to deal with the complexity of data, such as genomics and proteomics?

• Is your organization beginning to adopt data standards and data-driven semantic approaches?

The answers to these questions can help organizations begin planning how they can contribute to biomarker progress in the future.

Standards provide the foundation for

increased integration and collaboration,

and thus play a major role in accelerating

development and validation of biomarkers.

�5 The evolving role of biomarkers

ConclusionInnovation and adoption of biomarkers of all types have increased at an astonishing rate, and biomarker-enabled R&D has become a recognized discipline in itself. BioPharma is investing in the discovery and development of biomarkers while providing collaboration and leadership to guide this progress.

Biobanks and associated epidemiology studies are playing an important role in the discovery of new biomarkers and the understanding of disease mechanisms. In turn, biomarkers are being applied in an expanding range of clinical and therapeutic areas. Combining information from diverse biomarker sources is increasing its useful-ness and importance in making critical patient and investment decisions. Full utilization of biomarkers, however, is still lagging in drug development.

The realization of information-based medicine will depend on the ability of stakeholders to address complex data integration, commu-nication and collaboration issues. IT and service leaders are working on IT standards, architectures and solutions supporting this biomarker-driven transformation, with particular emphasis on the management and analysis of clinical data that includes genomic and imaging data. In addition, modeling and simulation are playing emerging roles

whose full impact is yet to be seen. To provide answers to disease-specific questions, both in drug development and at the point of care, it will become essential to rationalize the data through semantic data modeling and high-performance computing.

Achieving these goals requires new kinds of collaborative efforts, such as private/public partnerships that encourage pre-competitive discussions, and the Radiotracer Clearinghouse approach that involves sharing sensitive infor-mation in a protected environment. These collaborative efforts can help biomarkers become more ingrained in drug development as well as patient diagnosis and treatment. This will help stakeholders address today’s unmet medical needs with safer and more precise medical treatments that benefit both individual patients and society as a whole.

To learn more about the IBM (Imaging) Biomarker Summit III and the IBM Institute for Business Value, please contact us at [email protected]. For a full catalog of our research, visit:

ibm.com/iibv


About the authorsTerry McCormick is an Associate Partner in the Life Science Practice of IBM Global Business Services, which is responsible for providing project management, integration services and e-business solutions for clients in the Pharmaceutical, Biotech and Medical Device industries. Terry has been both a phar-maceutical and consulting executive, and is experienced across multiple aspects of drug development and launch, including R&D, regu-latory, manufacturing and commercialization. After working more than 20 years in R&D and operations within the pharmaceutical industry, Terry has been consulting in that arena since 1998. He has worked in discovery, develop-ment and the manufacturing operations areas, with a continuing focus on the development and commercialization of new drugs. He can be contacted at [email protected].

Kathleen Martin is a Managing Consultant in the IBM Institute for Business Value, Life Sciences/Pharmaceuticals team. She has ten years’ experience in business consulting and five years’ experience in clinical consulting. She has also worked in the pharmaceu-tical and healthcare industries, where she specialized in oncology and women’s health. Kathleen’s consulting expertise includes project management, business strategy, change management and process improve-ment. She has extensive experience in addressing the business aspects of technical implementations with pharmaceutical clients and the U.S. government. Kathleen has an MPH in Epidemiology and has published in the areas of medical malpractice, corporate learning and clinical development. She can be reached at [email protected].

Michael Hehenberger is the Global Solutions Leader for the Life Sciences/Pharma segment of the IBM Global Healthcare and Life Sciences organization. He is responsible for the development and implementation of innovative new IT solutions that support the ongoing transformation of Healthcare and Life Sciences. He manages a portfolio of initiatives that leverage capabilities across IBM Research and IBM product and service lines. During his years in academic and industrial research, Dr. Hehenberger has developed an understanding of the deep computing and information needs in various scientific domains. He has worked on data and knowledge manage-ment solutions, including the integration and analysis of information related to chemical, biological and clinical (patient) databases. More recently, he was involved in the develop-ment of solutions for Clinical Genomics and Biobanking, Pharmacogenomics, Clinical Decision Intelligence, Bio-Medical and Molecular Imaging. Dr. Hehenberger holds a Dipl.Ing. in physics from Vienna University of Technology, and Ph.D. and Dr.Sc. degrees in quantum chemistry from Uppsala University, Sweden. He can be reached at [email protected].

ContributorsWe wish to thank the members of the Biomarker Summit Advisory Council, as well as the speakers, for their valuable insights. Thanks are also due to workshop facilitators for providing summaries of the IBS III workshops that were used to develop this paper.


About IBM Global Business Services With business experts in more than 160 coun-tries, IBM Global Business Services provides clients with deep business process and industry expertise across 17 industries, using innovation to identify, create and deliver value faster. We draw on the full breadth of IBM capabilities, standing behind our advice to help clients implement solutions designed to deliver business outcomes with far-reaching impact and sustainable results.


References1 “Vital Signs – Biomarkers in Clinical Trials – A

Significant Competitive Advantage?” Frost and Sullivan. October 2006.

2 IBM defines “information-based medicine” as the process of transforming existing medical and pharmaceutical practices with knowledge generated from the integration and analysis of diverse clinical and biomedical data, including genomic, proteomic and imaging data types.

3 “There Are Currently No Less Than 220 Emerging Therapeutics Targeting Prostate Cancer, from Early Preclinical to Marketed Drugs.” Business Wire. January 15, 2007. http://www.micromedex.com/pressroom/news_feeds/?story_ID=111532&category=13 (accessed June 15, 2007).

4 Bartsch, G., and H. P. Rohr. “Möglichkeiten der quantitativen Bildanalyse an Prostatabiopsien/Quantitative analysis of prostate biopsy.” Bulletin of Swiss Academy of Medical Science, Vol. 33, pages 99-109, 1977; Bartsch, G. “Imaging and new developments for markers for prostate cancer.” IBM (Imaging) Biomarker Summit III, January 2007.

5 “The Biobank at Karolinska Insitutet.” http://ki.se/ki/jsp/polopoly.jsp?d=866&a=1306&l=en (accessed June 15, 2007); McManus, B., MD, PhD, FRSC. “Biomarkers of Acute and Chronic Allograft Rejection in Heart, Kidney and Liver Recipients.” IBM (Imaging) Biomarker Summit III, January 2007.

6 “Alzheimer’s Disease Drug Development Program.” U.S. Department of Health and Human Services. http://grants.nih.gov/grants/guide/pa-files/PAR-05-148.html (accessed June 15, 2007).

7 Wong, D. “Progress in PET Biomarkers for CNS Research.” IBM (Imaging) Biomarker Summit III, January 2007.

8 Hochstrasser, D. “Clinical Proteomic & Biomarker Discovery in Cerebral, CV & Renal Diseases.” IBM (Imaging) Biomarker Summit III, January 2007.

9 Donahue M.P., K. Rose, D. Hochstrasser, J. Vonderscher, P. Grass, S.D. Chibout, C.L. Nelson, P. Sinnaeve, P.J. Goldschmidt-Clermont and C.B. Granger. “Discovery of proteins related to coronary artery disease using industrial-scale proteomics analysis of pooled plasma.” American Heart Journal, Vol. 152, Issue 3, pages 478-485, 2006.

10 Dietel, M. “Predictive Tissue-Biomarker for Cancer.” IBM (Imaging) Biomarker Summit III, January 2007.

11 Ibid; Young, H. “Role of Imaging in Oncology Drug Development.” IBM (Imaging) Biomarker Summit III, January 2007.

12 Deglon, N. “Multimodal image reconstruction in neurosciences.” IBM (Imaging) Biomarker Summit III, January 2007.

13 Ibid.14 Royyuru, Ajay. “Deep computing in biology:

challenges and progress.” IBM (Imaging) Biomarker Summit III, January 2007.

15 McManus, Bruce, MD, PhD, FRSC. “Biomarkers of Acute and Chronic Allograft Rejection in Heart, Kidney and Liver Recipients.” IBM (Imaging) Biomarker Summit III, January 2007.


16 “Innovation or Stagnation: Challenge and Opportunity on the critical path to new medical products.” U.S. Department of Health and Human Services. March 2004. http://www.fda.gov/oc/initiatives/criticalpath/ (accessed June 15, 2007).

17 Martin, Kathleen, Dr. Mark Hammond and Stuart Henderson. “The eClinical equation: Part 2 – Bridging connections for innovation.” IBM Institute for Business Value. October 2006. http://www-935.ibm.com/services/us/index.wss/ibvstudy/gbs/a1025940?cntxt=a1000060 (accessed June 15, 2007).

18 Burstein, H. J. “The distinctive nature of HER2-positive breast cancer.” New England Journal of Medicine, Volume 353, No. 16, pages 1652–1654, 2005.

19 Trusheim, M.R., E.R. Berndt and F.L. Douglas. “Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers.” Nature Reviews/Drug Discovery, Vol. 6, April 2007, pages 287-293.

20 “The Biomarkers Consortium: Advancing Medical Science.” Foundation for the National Institutes of Health. http://www.fnih.org/Biomarkers%20Consortium/Biomarkers_home.shtml (accessed June 15, 2007).

21 Mittleman, B. “Public-Private Partnerships at the NIH.” IBM (Imaging) Biomarker Summit III, January 2007. NIH approval to cite this material should not be considered an endorsement of IBM or its products and services.

22 Genetic Association Information Network (GAIN). Foundation for the National Institutes of Health. http://www.fnih.org/GAIN2/home_new.shtml (accessed June 15, 2007).

23 Wong, D. “The Radiotracer Clearinghouse: A New Approach for Sharing Biomarkers.” IBM (Imaging) Biomarker Summit III, January 2007.

24 Ibid.25 “Guidance for Industry: Pharmacogenomic

Data Submissions.” U.S. Department of Health and Human Services. March 2005. http://www.fda.gov/cber/gdlns/pharmdtasub.pdf (accessed June 15, 2007).

26 Woodcock, J., Deputy Commissioner for Operations, FDA. “Biomarkers: Physiological & Laboratory Markers of Drug Effect.” National Institutes of Health Clinical Center. February 1, 2007 http://clinicalcenter.nih.gov/researchers/ training/principles/ppt/woodcock_2006-2007.ppt (accessed June 15, 2007).

27 Mills, G. “FDA Update.” IBM (Imaging) Biomarker Summit III, January 2007.

28 Garber, A. M. “Cost-effectiveness and evidence evaluation as criteria for coverage policy.” Medical Management. May 19, 2004.

29 Greener, Mark. “SNPs: Driving Variablity and Tailoring Treatments.” Drug Discovery & Development. 2006. http://www.dddmag.com/ShowPR_Print.aspx?PUBCODE=016&ACCT=1600000100&ISSUE=0407&RELTYPE=PR&ORIGRELTYPE=GPF&PRODCODE=00000000&PRODLETT=Y&CALLFROM=RELPGM (accessed June 15, 2007).

30 “FDA to Develop Regulatory Guidelines for Trials That Change Midcourse to Accommodate Early Results.” kaisernetwork.org Daily Health Policy Report. July 10, 2006. http://www.kaisernetwork.org/daily_reports/rep_index.cfm?hint=3&DR_ID=38390 (accessed June 15, 2007).


31 Martin, Kathleen, Dr. Mark Hammond and Stuart Henderson. “The eClinical equation: Part 2 – Bridging connections for innovation.” IBM Institute for Business Value. October 2006. http://www-935.ibm.com/services/us/index.wss/ibvstudy/gbs/a1025940?cntxt=a1000060 (accessed June 15, 2007).

32 Fraser, Heather, Ed Mounib and Sarah Payne. “In the interest of the patient: Convergence across the pharmaceutical and health-care industries.” IBM Institute for Business Value. December 2006. http://www-935.ibm.com/services/us/index.wss/ibvstudy/gbs/a1026259?cntxt=a1000401 (accessed June 15, 2007).

33 “FDA Data Standards Council.” http://www.fda.gov/oc/datacouncil/ (accessed June 15, 2007); “JANUS.” National Cancer Institute. http://crix.nci.nih.gov/projects/janus/ (accessed June 15, 2007).

34 Martin, Kathleen, Dr. Mark Hammond and Stuart Henderson. “The eClinical equation: Part 2 – Bridging connections for innovation.” IBM Institute for Business Value. October 2006.http://www-935.ibm.com/services/us/index.wss/ibvstudy/gbs/a1025940?cntxt=a1000060 (accessed June 15, 2007).

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