Cardiac safety is, without a doubt, a very critical issue for the pharmaceutical industry. It is well known that some drugs may increase the risk of arrhythmias or other critical cardiac events. Therefore, industry spends a significant amount of effort in the early stages of drug development to ensure cardiac safety. 

However, there are no perfect biomarkers for cardiac safety, and the risk is high for killing drugs before their benefits are clearly evaluated. 

Some years ago, the U.S. FDA and European Medicines Agency published their recommendations for ECG QT/QTc studies (Thorough QT studies, or TQT) to evaluate the proarrhythmic potential of non-antiarrhythmic drugs.

  The basic assumption behind these recommendations is that the QT-interval is a sufficient biomarker for the arrhythmogenic potential of drugs. 

The QT interval represents the ventricular depolarization and the following repolarization of the heart cycle. The QT-interval is commonly measured from the beginning of the QRS complex (Q-Point) to the end of the T-wave. But the threshold level of regulatory concern is around five milliseconds, as evidenced by an upper bound of the 95% confidence interval around the mean effect on QTc of 10 milliseconds.

This requires very accurate acquisition and analysis of the 12-lead surface ECG. 

Measuring small effects of drugs on cardiac polarization and repolarization in the surface ECG with the necessary statistical relevance is not easy. All TQT studies, therefore, have to prove that the applied procedure is capable of detecting the small drug-induced effect on the QT interval. 

TQT studies typically run a positive control group and placebo group in combination with the group treated with the drug under evaluation. Currently, each ECG is evaluated manually by experienced staff, which requires a significant budget for QT studies. Although humans are very good at pattern recognition, a manual analysis of ECGs introduces statistical errors due to inter-reader and intra-reader variability. 

This problem has been well known since the mid-1980s, when a systematic evaluation of cardiologist in comparison to computer algorithms was done in the CSE study.

  Today, most ECG core labs are automatically tracking the variability introduced by their staff to ensure sufficient quality of the ECG analysis. Together with the positive and placebo control in TQT studies, this works well and with the necessary accuracy. 

There have been several attempts to do the ECG analysis automatically, especially the QT measurement.

  But so far, no one seems to have proven well enough the accuracy of fully automatic procedures in TQT studies to persuade the pharmaceutical industry to take the risk of submitting a fully automated analysis to the FDA. 

The reason for this lack of proof is that before new methods can be applied in real cases, they must be proven with existing data to be capable of delivering the same accuracy compared with the reference of a fully manual approach. 

To date, however, these data have not been available for academic or commercial research institutions. Only recently, the THEW initiative,

  a public/private partnership under the leadership of the University of Rochester and FDA, has made an attempt to fill this gap by publishing data and conducting further research on automatic analysis methods. 

The THEW project is a very promising start, but to date it is not sufficient to compare fully automatic procedures against a real gold standard. A real gold standard would mean to have ECG data sets—free of any commercial conflict of interest—made available to the public, where the reference (the key to the results) is nonpublic and held by an independent organization, such as the FDA. 

These data sets should contain at least three TQT studies (with placebo and positive control) analyzed by different core labs and a nonprofit organization to ensure high data quality. Public and private organizations could then run the data sets with their automatic measurement methods and send their analysis to the organization holding the key (i.e., the expected results). The methods would then be proven independently and free of commercial interest. 

This general procedure was already established for standard ECG measurement and interpretation algorithms in the 1980s (CSE project) and today is part of the required norms for ECG machines such as the IEC 60601-2-25.

We have run our own ECG algorithms against several data sets and can prove that QT measurements are as accurate as manual measurements with less variability. 

However, without a general, widely accepted reference against which all core labs and manufacturers have to prove their accuracy, industry will not take the potential risk to move forward with innovative, automatic procedures, despite offering tremendous efficiency gain and cost savings. 

Besides validating automatic analysis of TQT studies, there is a fundamental question about the quality of QT as a biomarker. The association of long QT and the arrhythmogenic risk is well proven, but there is no one-on-one, direct relationship. QT is an indicator, but the predictivity is limited. This may lead to drugs killed in the early development stage, although their benefit would easily justify the risk (to date only estimated with a nonperfect biomarker). 

The problem is well known, and several public and private organizations, including ours, are working on new ECG-based biomarkers—with very promising ideas. 

  have focused on T-wave morphology analysis and, not surprisingly, it seems there is significantly more information in the T-wave than just within the QT-Interval. However, most of the work is being done on very small data sets; the majority of critical arrhythmias, such as TdP (Torsade de Pointe), occur very rarely and are difficult to collect in larger data sets. 

To prove and validate new biomarkers, the whole industry—ECG core labs, pharma, and public research organizations—will have to work together and contribute meaningful data to share among the different parties, as recently stated in the THEW project.

Besides TQT studies, many drug safety and efficacy trials apply ECGs to monitor patients. While a systematic QT evaluation is usually not part of these studies, the ECG is still used to ensure safety by applying a defined set of evaluations. These are commonly provided by the sponsor. In these trials, the number of ECGs to be evaluated is usually significantly higher than in standard TQT studies.  

The intention of these trials is to detect any changes in the ECG during the trial relative to a baseline ECG. The current state-of-the-art is a central, digital ECG collection with manual over-read by experienced core lab staff. Again, this procedure is costly and consumes a lot of resources. In a Phase III trial, there can easily be 20,000 to 50,000 ECGs. 

The interpretation of ECGs after the recording in central core labs takes typically between 12 and 48 hours, depending on the requirements of the sponsor. Usually, the shorter the time, the higher the charge by the ECG core lab. However, a critical change against the baseline ECG means there will be quite a long time before a patient is reevaluated at the trial site and is withdrawn from the study, if necessary. 

We have recently developed a new procedure to overcome these shortcomings. The intention is to increase cardiac safety of patients in a clinical trial by reducing the response time in the core lab. A secondary effect is that the cost of large ECG trials can be reduced significantly. 

The basic idea behind this new procedure is that all incoming 12-lead resting ECGs are immediately, and in real-time, analyzed with our automatic measurement and interpretation algorithm HES

In the first step, the algorithm classifies the ECGs into normal and abnormal. As classification criteria, we apply approximately 150 parameters of the ECG, including measurements, a detailed rhythm analysis, and a QRST evaluation. The 150 parameters were derived from approximately 1.200 parameters, the algorithm calculates for each 12 lead, 10 second resting ECG. 

The algorithm was specifically trained to sponsor-defined thresholds, such as QTcB > 450 ms, HR > 100 (tachycardia), and HR < 58 = bradycardia, among others. The algorithm itself is trained so that its sensitivity to detect abnormal ECGs is extremely high—near 100%. This sounds difficult, but if any abnormality, when not even critical, is already classified as abnormal, it's possible to achieve the necessary sensitivity. 

In the second step, the ECG is compared to the baseline ECG of the patient under evaluation (if present already) and analyzed for any change, for example, in the PQ, QRS or QT interval (serial ECG comparison). If the sponsor defines a change in QTc of more than 10 milliseconds as a clinically significant change, and 11 milliseconds are measured, the ECG is immediately classified as abnormal, even if the absolute value of QTc is still in the normal range. 

Any ECG classified as abnormal is then, in the third step, prioritized according to clinical significance of measured changes. We define up to five levels of clinical significance. The highest level of significance is over-read by core lab staff immediately and sent back to the trial site, say within 20 minutes. The lowest level, which means abnormal but not clinically significant, may take up to 48 hours, depending on the requirement of the sponsor. 

In conclusion, ECGs are not, as is common practice, always analyzed within a certain time frame—regardless of the clinical severance—but in the clinically appropriate time frame. This leads to significantly increased patient safety. In the event of a critical ECG, it is analyzed immediately to make sure that the patient and doctor do not have to wait 12 to 48 hours for feedback. 

We have tested the new procedure with retrospective ECG data (more than 10,000 ECGs) from a Phase III trial analyzed in our core lab, and were able to detect all abnormal ECGs. Since the algorithm was trained to a high sensitivity, it classified many ECGs as false positive—that is, ECGs were classified as abnormal, although the lab classified them as normal. But since all abnormal ECGs were detected, this led us to conclude that in the future we could even analyze all ECGs classified by the algorithm as abnormal only and trust that if the algorithm classifies ECGs as normal, we don't have to send them for manual over-read. 

In our example Phase III trial, we could have saved more than 50% of the manual over-read without any loss of patient safety. This would have saved the sponsor a lot of money. [Detailed results of our study will soon be published.] 

Although the cardiac safety industry has talked for some time about a fully automatic ECG analysis approach to TQT, to date no methods have been proven well enough to persuade the pharmaceutical industry to apply them in a real trial. We need a concerted effort, across the whole industry and within academic institutions, to generate large enough data sets to validate fully automatic procedures. 

To improve cardiac safety, we also need further private/public partnerships to foster research and development of new biomarkers besides QT, which is good but by far not a perfect risk-stratification marker. In non-TQT ECG trials we have reached a level of accuracy in automatic analysis to apply it, after a few more validation trials, in real trials. 

 is head scientist, cardiac technology, Cardinal Health Research Services and general manager, BIOSIGNA, Lindwurmstrasse 109, 80337 Munich, Germany, email: 

1. ICH E14, EMEA, European Medicines Agency, 2005.  

2. J.L. Willems, P. Arnaud, J.H. van Bemmel, P.J. Bourdillon et al., "Development of a Reference Library for Multi-lead ECG Measurement Programs," 

3. R. Handzel, C. Garnett, M. Li, S. McNitt et al., "Computers in Cardiology," IEEE Computer Society Press, 35, 693-696 (2008). 

4. Computers in Cardiology Conference, QT Challenge 2006, 

Articles

Feature Article

With industry facing technological change, partnering may offer safety solutions.

Partnerships for Cardiac Safety

Over the past 10 years, the industry has seen the emergence and advancement of technologies in the clinical trial process, including electronic data capture (EDC), electronic Patient Reported Outcomes (ePRO), and the electronic Common Technical Document (eCTD). 

Such advances have had a tangible impact on streamlining the delivery of clinical trials. However, despite the fact that up to 80% of all trials are outsourced to third parties, the selection of a suitable CRO partner still involves a labor intensive procurement process that is often costly-in time and money-to both sponsor and CRO alike, and can involve a significant paper trail. 

A global electronic procurement (eProcurement) report released by SPG Media Research in 2007 indicated that approximately 90% of businesses worldwide are now involved in some form of eProcurement, and highlighted that key decision makers are incorporating them into overall organizational cost reduction strategies. 

It's estimated that the U.S. business sector is now saving $700 billion dollars per annum by employing an eProcurement approach. 

In the life sciences, eProcurement solutions are well-established and have proven to reduce costs through streamlining the purchasing of lab products, IT equipment, and office supplies. Such platforms can also integrate with internal financial systems offering significant time savings. 

In 2007, SciQuest and Invitrogen Corporation embarked on an eProcurement partnership-the first of its kind within the life sciences industry-to deliver a multivendor platform to targeted sponsors that allowed them to recognize efficiencies and have more control over their purchasing practices, which delivered significant savings in their organizations. 

Within the pharmaceutical industry, many eProcurement-based processes have begun to govern outsourcing practices. 

eProcurement platforms and electronic document management systems such as the Ariba B2B Commerce Platform and Microsoft's SharePoint are being employed in the tendering process, with contract service providers progressively more incorporated in the eProcurement infrastructure developed by sponsors. 

Commercially available platforms such as these can reduce the tasks of distribution, receipt, and tracking of tender submissions to help streamline and manage the entire procurement process. 

Electronic tendering has recognized business benefits in reducing the tender cycle time and paper trails, accompanied by a reduction in costs to both buyers and suppliers. The systems enable faster response times to questions and clarification points during the Request for Proposal (RFP) process and provide robust electronic audit trails for sponsors. From a CRO perspective, however, the time to complete responses can be increased, as there is a tendency from sponsors to request additional information to supplement the proposal. 

Online electronic auctions have enabled sponsors to create interactive and real-time bidding environments as part of preferred-provider selection initiatives. 

Although this technology is increasingly employed by a number of pharmaceutical companies, the approach offers limited interactivity and still represents a detached and transactional shopping-cart approach to CRO-sponsor interactions, with limited opportunity to develop the relationship outside of a formal-bid defense process. 

A further limitation of current eProcurement solutions is the continued reliance on "traditional" proposal and pricing documents that are uploaded onto an eSourcing platform. 

However, the current evolution of more long-term strategic relationships, exemplified by the established association between Wyeth Research and Accenture, the Functional Service Provider (FSP) initiative pioneered by Pfizer in 2003, and more recently Lilly's contract with Covance for clinical and preclinical research services over the next 10 years, highlights a desire to develop more collaborative partnerships and greater transparency within the industry. 

If a more interactive approach to the tendering process were adopted, it could engender greater transparency at the earliest stages of the CRO-sponsor relationship. This would help establish a more collaborative and trusting environment to maximize the chance of successful study delivery. 

Such a strategy has clear advantages to both CRO and sponsor. In such an aggressive and highly fragmented marketplace-there are currently around 1100 CROs worldwide-CROs need to differentiate themselves from competitors at the earliest stage of the sales cycle. The proposal often provides the first opportunity for sponsors to assess the capabilities and expertise of an organization, and can be indicative of a CRO's ability to deliver a quality product whilst working to a tight deadline. 

From a sponsor's perspective, the quality of the proposal document is clearly a differentiator and provides insight into whether potential vendors understand the requirements of a particular study and the expectations of the sponsor. 

Further, sponsors need to compare the capabilities, resources, experience, and pricing models of a range of CROs through a document that is often prepared within a short time frame. Does this approach really allow sponsors to adequately assess vendors that they will entrust to successfully deliver their clinical projects? 

A well-presented proposal should clearly demonstrate a CRO's depth of relevant expertise and offer an operational strategy that will provide a clear and well-defined solution to a sponsor's clinical trial requirements. 

"Although a few [proposals] are outstanding, most aren't. Many offend with 'cut-and-paste' boilerplate, miss important opportunities to provide value, suffer from poor logic and organization, and focus more on you than on me and my organization. Although some do a few things well, some don't do much well at all." 

According to Harold E. Glass and Daniel P. Beaudry,

  sponsor companies use five general dimensions in evaluating and selecting a CRO: Processes for Issue Identification and Resolution; Specifics of Project Execution; Team Chemistry; CRO Experience; and CRO Capabilities. 

Current procurement processes and traditional proposal responses provide minimal opportunity to address these key selection criteria appropriately. Proposals often struggle to convey the expertise of the CRO effectively and fail to highlight sponsor hot-buttons for a successful partnership. 

If an eProcurement environment was provided by the CRO instead of the sponsor, this would redefine the interaction and collaboration between CRO and sponsor at the earliest stages of the relationship. 

Implemented using commercially available platforms, such as eRoom, Ariba or SharePoint, or through solutions combining database servers (e.g., MS SQL Server 2007) to store the data with Web servers to host the Web pages, sponsors would access the system via a desktop Web browser through a secure internet link. 

Levels of secure access-assigned by the CRO-would permit sponsors to navigate through an electronic proposal (eProposal) area to evaluate a CRO's portfolio of experience and capabilities, including general company information and relevant study-specific expertise. 

The eProposal would hyperlink to an interactive pricing tool, library of relevant case studies, operational strategy and project plans, and resource-planning software to enable sponsors to view resource allocation and even pre-book project teams to specific studies. Additional access would be provided to a secure sponsor-specific vault area containing bespoke templates and legacy documents, including previous proposals, quotes, and contracts. For ease of sponsor review, selected documents would be available for download as required (see Figure 1). 

The implementation of such a solution provides instant access for sponsors to assess CRO core competencies and requires only a minimum paradigm shift within industry. However, the provision of accessible resource-planning software and the concept of an interactive pricing tool may require a bigger leap of faith. 

Interactive approaches to resource planning and tracking are already in place. For example, in our organization we have implemented a Web-based project portfolio management system offering secure access to users via Web browser. 

This platform is used to collect and forecast resource requirements over varying time frames to provide a single view of resource capacity, work demand, and skills profile. Through this secure Web portal, sponsors will have global visibility to resource capabilities and can not only identify and select a project team through screening core competencies at the eProposal stage, but can also track the progress of their existing studies on an on-going basis. 

This technology solution not only facilitates resource planning and modeling, but also scope management, risk management, issue management and escalation, and project status reporting, enabling sponsors access to critical information to drive the CRO selection process. 

There is continued discussion within the industry for a standardized approach to the bid template. Current sponsor-specific bid-grids go some way to facilitate cost comparisons between vendors, but mapping budgets to these tools can be time consuming for CROs and often result in more questions than answers, as CROs shoehorn their own pricing models into a sponsor-specific format. 

Allowing access to an interactive pricing tool allows sponsors to modify key budget drivers, such as number of sites, patients, monitoring visits or CRF pages to assess the impact on the overall price of a study. By interacting with the budgets, sponsors will have a greater understanding of the CRO pricing structure. This improved transparency should reduce the requirement for bid-grids, saving CROs time preparing budgets while minimizing risk of pricing misunderstandings by both parties at the outset. 

The current proposal process is time consuming, and there are limitations with the format that restrict how information is presented. A CRO hosted eProcurement solution enables CROs to deliver a flexible and interactive response to sponsors that will address the five key evaluation and selection criteria highlighted and maximize proposal hit-rate. 

Further, by providing restricted access to key company and study-specific information, the CRO can retain control of the documents and process, while addressing specific RFP requirements with greater detail and clarity within a much reduced time frame and with a minimal paper trail. 

CRO proposal responses vary in quality and relevance, with sponsors often wading through large documents to identify salient points. The eProposal allows sponsors to review information in bite-sized chunks, focusing on key areas of interest and with a greater level of transparency. 

Relevant documents can be downloaded and distributed as required and the appropriate levels of access can be predefined with the CRO to enable a thorough assessment of CRO capabilities at the RFP stage. 

Transition from a traditional paper-based approach to an electronic interactive platform is just a small step from currently available eProcurement solutions. Embracing a constantly evolving technology environment at the earliest stage of the clinical trial process offers clear advantages for all stakeholders, not just in time, but in harmonizing CRO and sponsor teams at the outset of the relationship. 

, PhD, is head of contracts & proposals at Quanticate, Bancroft Court, Hitchin, Hertfordshire SG5 1LH, United Kingdom, email: 

A more transparent solution to vendor selection in an evolving technology environment.

eProposals: An Interactive Approach to eProcurement

Over the past 30 years the cost of taking a drug from conception to FDA approval has increased from $138 million to $1 billion. R&D spending in the United States rose from $4 billion in 1985 to $55 billion in 2006.

  This increase has been caused by many factors, including increasing regulatory requirements, more technically demanding science and manufacturing procedures, and the introduction of innovative new drugs and molecular entities for complex disease targets. 

The number of successful product approvals for new drugs has decreased in the last three years, with a high rate of attrition. Current estimates suggest that only one in 10 Investigational Medicinal Products (IMPs) entering Phase I clinical trials actually makes it through to the end of the drug development process and obtains marketing approval.

  Since the cost to develop and market is so high and constantly increasing, it would be advantageous to reduce the number of unsuccessful drugs at an early stage of development before embarking on expensive trials. 

A potential solution to the high number of failures in clinical trials could be the use of biomarkers. The U.S. National Institutes of Health defines a biomarker as "a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes or pharmacologic responses to a therapeutic agent." 

Identifying, studying, and quantifying biomarkers can increase our understanding of drug action, its metabolism in the body, efficacy, and safety. All of which can collectively act as key decision making tools when evaluating the performance of an IMP in the clinical environment. 

The scope of what constitutes a biomarker is in itself wide ranging. The nomenclature of biomarker can be applied both at the gene level or post-gene expression as well as analytes, which are indicative of a physiological change post drug administration. Therefore, with such a wide range it is easy to understand the impact that biomarker discovery, identification, and subsequent monitoring could play in the life cycle of a potential therapeutic agent. 

Novel biomarkers can be used as research tools during early drug development to select candidates with therapeutic potential. Patients can be screened at both the genetic and/or protein level to indicate or predict their response (therapeutic or not) to administration of an IMP and to monitor any potential toxicity caused by a drug, which could lead to an adverse drug reaction. 

Qualifying a biomarker—that is linking it to a clinical endpoint—is essential if the biomarker is to be used to measure a clinical outcome. And by linking biomarkers at the different levels, an increasing and ultimately enhanced understanding of the receptiveness of the patient to respond either well or adversely can more rapidly be qualified. Genetic and/or metabolic expression biomarkers can classify patient responses to treatments, but these must be correlated with phenotypic endpoints or surrogate endpoints. 

Biomarkers have become more important in clinical practice because the tools and technologies available to researchers have facilitated better understanding of: 					

The link between genetic/genomic and protein markers

Their association with disease and metabolic pathways

It is the continual advancement of new technologies that can measure these markers that is resulting in the ability to make go/no-go decisions earlier in the development process. This article will describe some of these technologies and the methods used to measure biomarkers. 

With the completion of the Human Genome Project, the ability to generate genome-wide association data, next generation sequencing, and gene expression profiles has helped researchers in the study, understanding, and explanation of disease mechanisms and epidemiology. By looking at the data available through these technologies, biomarkers in monogenic and polygenic diseases have been identified. 

In the study of human genetics and pharmacogenomics, it was historically thought that there would be one "wild-type" and one "defective allele." With the passage of time, this has changed to a position whereby most researchers think that there will be multiple Single Nucleotide Polymorphisms (SNPs) in one or a few genes that will be associated with any complex disease or drug response. 

Technology has advanced to such a level that these SNPs can now be identified, and the downstream consequences of them in relation to both disease epidemiology and reactions to drugs can be assessed and measured. 

Within the clinical trial arena the extraction and purification of DNA from patients is currently being undertaken. This provides clinical researchers the potential for subsequent genotyping experiments on multiplexed arrays such as the Illumina IScan. These genome-wide association studies form the initial point of biomarker discovery and identification, providing a high-throughput solution for screening up to over 1 million potential markers across the trial population. Complex bioinformatics can then be used to narrow down specific SNPs of interest right down to a singleplex approach, looking specifically at SNPs within candidate genes.  

The launch of the DETPlus panel by Affymetrix provides a high-throughput screen that captures more than 90% of the current ADME Core markers as defined by the PharmaADME group. This panel provides coverage of a wide range of genetic variations, including common and rare SNPs, which enables the identification of significant, new biomarker associations. 

As an example, warfarin, a well-known drug prescribed to prevent heart attacks and strokes, is also known to be one of the top drugs for causing severe adverse events. In a recent warfarin study using the DMET Panel, researchers discovered a new variant in CYP4F2 (a drug metabolizing enzyme) that explained 8% of dosing variability in select patient populations.

  This new biomarker has subsequently gone on to being tested in a Phase III prospective trial. 

Using this information in conjunction with the raft of other clinical data available provides a level of information that could determine the efficacy and safety of a drug during a trial or that could be used as a screening diagnostic to prevent the administration of products to recipients who will have an adverse effect or demonstrate no therapeutic value. 

In either case, the decision pathway required to get a drug to market is greatly enhanced as potentially toxic products could be quickly identified and dropped, or conversely, more precise clinical data could be accrued to support authorization of a product for a very specific genotype. 

Proteomics is the scientific discipline that studies proteins and their association with diseases by means of their altered levels of expression and/or post-translational modification between control and disease states. It enables correlations to be drawn between the range of proteins produced by a cell or tissue and the initiation or progression of a disease state and the effect of therapy. Proteomics can be used for the discovery of novel drug targets and in the discovery and validation of diagnostic and prognostic disease biomarkers. 

An example of a disease where proteomic research of biomarkers is being used is the diagnosis of ovarian cancer. Researchers collected serum from 50 ovarian cancer patients and 50 controls and used a computer algorithm to search for the protein patterns that distinguished cancer from noncancer. When they tested this pattern with a set of blinded serum samples, the test pattern correctly identified all 50 patients with cancer, and was able to discriminate them from 63 out of 66 patients who were unaffected or had benign disease.

Some of the analytical methods used in Proteomic research are gel electrophoresis and mass-spectrometry. 

Enzyme Linked Immunosorbent Assay (ELISA) is probably the most well-established quantitative and/or qualitative biomarker testing method. There are many test kits on the market designed to measure markers specifically associated with diseases (e.g., cardiovascular, oncology, inflammatory). Other biomarkers may be indicators of infection, such as skeletal, muscle and acute phase proteins, and toxicity (e.g., liver toxicity) or immunotoxicity. They usually have a "sandwich" format where biomarker-specific antibodies are coated on a microtitre plate, the sample is added, then after wash steps another specific labeled antibody is added and the bound complex detected by color/fluorescence development. 

Multiplex platforms where several markers can be measured in one sample are becoming more popular due to the reduction in cost, time, and sample volume required. They often use fluorescent beads to which antibodies are attached. For example, several cytokines can be measured using the Luminex xMAP (multi-analyte profiling) platform by covalently linking each capture antibody to Luminex beads, enabling measurement of each cytokine level in plasma. 

Flow cytometry is also used in biomarker detection by employing specific fluorescence-tagged antibodies that bind to antigens expressed on the target cells, which can then be detected in the cytometer. The fundamental mechanism of biomarker detection is the same as ELISA (antigen–antibody affinity), however, the flow cytometry platform can be used to examine the proteins that are expressed by the different populations of cells. 

Metabolic profiling involves the characterization of the metabolites (usually small molecules) found in an organism, which are the end products of gene expression—it is therefore closely linked with genomics and proteomics. Methods of metabolite analysis usually involve: 					

Extraction of metabolites from biological tissues

Separation by chromatography or electrophoresis, particularly capillary electrophoresis

Detection for example by mass spectrometry

Identification and quantification of the analytes.

Radioimmunoassay (RIA) is a well-established method that can be used to measure metabolites (e.g., hormones such as insulin in biological samples). 

It is based on the antigen–antibody reaction in which tracer amounts of the radio-labeled antigen competes with the endogenous antigen for limited binding sites of the specific antibody against the same antigen. Another example of the application of RIA in biomarker research has been its use to quantitate biomarkers of breast cancer.

The study of biomarkers, whether genomic, proteomic or metabolomic, has the potential to revolutionize clinical research. The complexity of the systems and advanced technologies mean that data are being collected at a fast pace. 

Efforts to qualify/validate, interpret, and integrate biomarker data with clinical endpoints will ultimately provide a better understanding of biomarkers in disease processes and will benefit clinical diagnosis and prognosis. 

is manager, biopharmaceutical laboratory, for Tepnel Research Products & Services, Appleton Place, Appleton Parkway, Livingston, West Lothian EH54 7EZ, United Kingdom, 

A look at the different testing methods and how the results impact drug development.

Biomarker Boom

China is in the midst of a transformation from one of the world's top producers of generic medications to a leader in novel drug discovery. Companies like Eli Lilly, Novartis, and Bayer are investing heavily in R&D infrastructure. 

Novartis alone-which said its 2008 sales rose 29%, boosted by its patent drugs-has so far invested 2.26 billion Yuan on infrastructure, marketing, and R&D facilities. This year Novartis is on track for the release of six new drugs in China, and by 2010 China is expected to be the fourth largest pharmaceutical market. 

Add to this growth substantial new government investment into expanding health care access. According to 

  the State Council has approved a long awaited draft plan of government investments in health care reform that will see the Chinese government commit $124.26 billion (850 billion Yuan) in the next three years to cover 90% of the population. The aim of the reform is to have the government bear the bulk of medical expenses for its people by 2011. 

Global economics will only add to this double digit growth. Contrary to the rest of the world's credit condition, China banks are sitting on the highest amount of liquidity currently available. According to 

  Chinese bank lending surged by 21% in the last year. 

For small biotech and externally funded drug developers thirsting for cash and an inexpensive path to approval, Shanghai may be the path of least resistance. 

  the pharma outsourcing industry in China has experienced over 35% year-to-year growth in the past few years. While the market growth and financial resources are very attractive, there are many challenges to face in this still emerging landscape. 

Despite recent changes, pharmaceutical regulations in China are still burdensome and among the slowest to permit clinical trials. On average, it takes up to nine months from application for a trial to receive approval [

http://www.cfs.gov.cn/cmsweb/webportal/W45649089/A64002920.html

Therefore, a partner with extensive Chinese experience can be invaluable, offering advice as well as insight on the risks of a particular program. 

The prolonged approval cycle coupled with the large number of less experienced investigator populations cause studies in China to lag behind parallel trials in more traditional markets. However, rapid project start up, as well as recruitment, more than make up for the initial delays. 

These delays can also be overcome with proper investigator training and trial material distribution. Despite the mentioned issues, there are instances where trials in China catch up or outpace parallel research in the United States and Europe, where the recruitment cycles are slower. 

Strict regulations on the export of specimens and complete restriction of the export of genetic samples can impact the utilization of out-of-country support resources and increase the cost of technology transfers to multiple providers in the region. These complexities of exporting specimens restrict the ability to leverage labs outside of China during study sample peaks. 

To overcome these limitations many local labs must outsource their biomarker and esoteric testing to specialty labs that do not have equivalent accreditation, certification or harmonization processes. It is therefore critical to evaluate any subcontractor arrangements to ensure the local specialty labs have the ability to support your development program. 

As a byproduct of fast startup and recruitment, an onslaught of screening visits in a relatively short time causes a tidal wave of data, specimens, and screening samples potentially inundating available resources. These tsunamis of investigator data and laboratory samples can quickly overwhelm resources not accustomed to the environment. 

Without well-established processes and a robust central lab protocol management system designed to handle these issues, the sheer volume could cause increases in scope, costs, and delays and impact study results. 

To support the boom in drug development and help manage the complexities of clinical trials, service companies, CROs, and central labs have been establishing new facilities in China. However, these young investments will need time to mature and establish the experience pools needed to negotiate the complexities of this emerging and resource competitive landscape. Moreover, the competition is tight for access to the most experienced resources and researchers, and the complex regulatory affairs environment is a challenge. 

It's clear, therefore, that partnering early with a regionally experienced company is crucial to success. China-based central labs often have detailed understanding of regulatory concerns and relationships with investigators that can assist in accelerating the application process and managing the recruitment of subjects effectively. 

Seasoned local staff can resolve issues quickly and in the local language. As mentioned earlier, the newcomers will need some time to develop the appropriate local experience pool. Staff in these new entities generally are junior and rely on direction from out-of-country management or resources. For major issues, the staff may require support from teams several time zones away. 

Access to real-time lab metrics is a success factor for managing Chinese trials due to time zone difference with European- and U.S.-based sponsor companies. If access to safety reports and screening results are delayed, there is a resultant delay in response to issues contained in that data, which may impact the clinical trial. 

Any weaknesses in training of Chinese investigators, communication with local transport and logistic providers, and cultural challenges will be reflected in these metrics. Formalizing a process to review, analyze, and course correct on a regular basis can protect program investments. 

Establishing a strong relationship with a central lab partner early on can lead to a more efficient and effective use of study protocol design, appropriate assay choice, and biomarker selection and design, as well as provide insight on geographic considerations. In addition, tools and processes, from study set up to invoicing, can be customized with key input from the lab. 

Other points to consider when selecting partner include:  

It is essential that an outsourcing partner is also well-versed in the GCP guidelines established by the SFDA. 

Cultural differences can pose challenges, so a partner that knows the country, culture, and the best way to navigate the local business climate will help save both time and money. 

Your outsourcing partner should have a demonstrated ability to attract and retain experienced, local, professional, and scientific staff. 

While China is a unique and complex country, the formula for success can be put simply: early collaboration with a central lab partner with substantial experience in China. 

With a financial and operationally vested interest in achieving the same goals set by the sponsor, a central lab with experience in China can offer insight to help maximize value from a trial as well as reduce direct and indirect costs associated with logistic and regulatory issues. 

 is vice president and general manager, MDS Pharma Services Global Central Lab, and 

 is general manager, Asia Pacific of MDS Pharma Services Global Central Lab, 203-204 Shidao Soloon, 2 Tongji Middle Rd., BDA, Beijing 100176, China, email: 

To whom all correspondence should be addressed.

, "Chinese Pin Hope on Health Care Reform," 

http://www.chinadaily.com.cn/china/2009-01/22/content_7422769.htm

http://www.economist.com/finance/displaystory.cfm?story_id=13145849

Biospectrum, "Outsourcing Market in China will See 35% Growth," 

http://www.biospectrumasia.com/Content/100209CHN8544.asp

Best practices for selecting a central lab partner in this popular trial destination.

Partnering in CHINA

As health care stakeholders, from regulators to providers to payers, demand more evidence on the safety and effectiveness of drugs and medical devices in real-world use, they are also increasingly asking life science companies to develop patient registries to fulfill this need. 

(PHOTOGRAPHY: MARTIN POOLE, GETTY IMAGES ILLUSTRATION: PAUL A. BELCI) 

Since registries are similar in many ways to clinical trials, on first review a CRO partner—strong in trials—would seemingly also be strong in patient registries. However, it is in fact the subtle (and not so subtle) differences that make this a potentially risky assumption for a purchaser. 

For a number of reasons, an organization's need for designing and operating high-quality registries at a reasonable cost is best met by partnering with service providers that are experienced in this rapidly evolving research space. 

Registries are a valuable pre- and postapproval tool. In general, registries provide complementary data to that obtained from trials and are an increasingly important tool in safety surveillance. 

In addition to safety evaluation, they are particularly useful for generalizing the findings of clinical trials to populations not studied in those trials and for evaluating the impact of physician decision making and actions on patient care. 

Registries are also being utilized for observational comparative effectiveness studies because they can provide useful information at a lower cost than alternative methods. 

These efforts require specialized knowledge in design and evaluation. More importantly, whether for review by a regulator evaluating a risk evaluation and mitigation strategy (REMS) or by a journal editor considering a registry manuscript for publication, registries are now judged on quality. 

Registries for Evaluating Patient Outcomes: A User's Guide

 by the Agency for Healthcare Research and Quality, the ability to review a registry on its quality has become common.  

Many CROs have extensive experience with Phase I–III and sometimes Phase IV trials, but have not managed a proportionate number of registries, cohort studies or quasi-experimental designs. In choosing your partner, consider:  

Does the CRO have specific standard operating procedures (SOPs) and personnel focused on registries or are they borrowed from clinical trials?

Have you reviewed the training and experience of the team that will be working on your registry?

While some functions are similar between clinical trials and registries, there are two key areas that are not: scientific skills (including protocol development, advisory panel guidance, biostatistics, and publications) and operations (including project and site management). Look for specialists in these critical areas—CRO personnel that focus entirely on registries and similar real-world studies and do not cross between study types. 

A patient registry is "an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition or exposure, and that serves a predetermined scientific, clinical or policy purpose."

While clinical trials focus on efficacy—the extent to which medical interventions achieve health improvements under ideal circumstances—registries provide strong evidence for the extent to which medical interventions achieve health improvements in real practice settings. 

A single standard does not exist for the conduct of observational research, but there are a series of publications and consensus efforts that can serve as guides to registry design and evaluation. These include AHRQ and their 2007 handbook mentioned earlier, the GRADE Working Group,

  These resources serve as useful guides in shifting from a trial focus to an observational strategy. 

An effective CRO partner will field a scientific team that will guide your organization through key stages of the registry, including developing a good protocol and case report forms; making an advisory board effective; and, generating high-level publications for top tier journals. 

A quality registry begins with a good protocol. If a protocol is hard to understand or provides irrelevant background information, it can confuse or alienate physicians. As a consequence, it can compromise the study's ability to recruit sites and enroll eligible patients. A registry protocol that is forced into a clinical trial template can cause incorrect, and often unnecessary, safety reporting. 

A scientific partner must have the ability to write a clear, simple protocol that will provide guidance on the different safety requirements that exist for a registry—not a clinical trial—and then facilitate the regulatory team in determining the appropriate procedures for the study. 

In addition to protocol complexity, there are several other telltale signs of an inexperienced CRO working on a registry. Identifying the right data to collect requires an understanding of the analytical needs in the future; data sets can be broader and are generally focused differently than for a clinical trial. A CRO must understand what the minimum data set should be and how much data is too much. 

Beyond the protocol, the scientific partner must also be able to educate registry advisors on the purpose and power of a registry; that education is typically ongoing throughout the registry. If the advisory board and CRO are inexperienced with registries and do not fully understand the benefits of the design, the reasons it was chosen over a trial, and what the pitfalls are along the way, all too often the project will drift to the more comfortable clinical trials paradigm—sometimes with disastrous consequences. 

A third common problem with an inexperienced scientific team is that the benefits of the registry in terms of output are not realized. While certainly the lack of appropriately sophisticated analytic support for observational data will limit success, even more commonly, inexperienced CROs and advisors set expectations too low for registry outputs. 

Good registry data and quality manuscripts from them are in high demand from top tier journals. Lower tier journals should not be the expectation for manuscripts produced from a high-quality study. If the CRO isn't suggesting top scientific journals for your registry, that could be a red flag. 

Sponsors should review the publication lists of potential partners and ensure that the CRO has successfully published results from patient registries in high-quality journals. 

The project management and site communication teams must also understand the unique considerations of observational research and be able to explain these to the enrolling physicians and other data contributors. The issues they encounter are frequently different than in a clinical trial. 

For example, site managers may need to explain to a site why a registry does not pay for health care services. The CRO registry team must have the ability to build strong relationships with sites typically with lower payment levels than in a trial. The CRO must have methods to engage the practices or they will lose motivation and enrollment will lag. 

A good understanding of technology and physician practice workflow is important in implementation, as busy practices commonly ask for workflow recommendations that are not commonly seen in clinical trials—which rarely take place in small, private practices. Appropriate technology, particularly technologies that provide workflow tools and can integrate with billing systems or electronic health records, can also be vitally important to successful implementation. 

Quality assurance is a key area where registry operations and ultimately registry data will be judged. Registry experts have advocated for a risk-based approach to identifying the most likely causes for error and diligently creating processes and procedures to both avoid likely errors and to evaluate and report the types of errors that occur. 

Because the types of bias that enter observational research are different than in a randomized trial, the quality assurance procedures also may need to be different. Simply borrowing QA processes from clinical trials can both dramatically increase costs and, at the same time, fail to provide the assurance of quality that is being sought. 

This is a common and often very costly error of CROs inexperienced in high-quality registries. 

With increasing global requirements for sponsors, leveraging a registry across multiple countries is both efficient and often necessary. Experience in conducting registries in the countries targeted for the registry is often critical. 

Ethical regulations, in particular, vary internationally for observational research, and they are not the same as those that govern clinical trials. For example, each of the 27 member states in the EU defines its own legislation pertaining to when ethical review is needed. Not all of these are clearly defined, and some countries allow local regions to outline their own specific requirements. Some countries, such as Germany, have additional regulatory requirements for observational research that one might not expect if accustomed to managing U.S. studies. 

Similarities exist, but successful design requires that CROs understand the differences.

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