Medical imaging has developed extensively over the last 30 years. It now plays an ever-increasing role in the development of new therapeutics, either as a surrogate endpoint or an endpoint in its own right. Recent years have also witnessed the development of the so-called "core lab" or imaging laboratory for the centralized quality control and assessment of images. The so-called imaging core labs (ICLs) were formally defined in 20031 and are shown in Figure 1. Central processing vendors have become a major part of the clinical trial process, to the point that at the Partnering with Central Labs, ECG and Imaging Labs Conference in 2004 and again in 2005, several speakers commented that 80% of the data going to the FDA passes through the vendors in this category.  

The development of the ICL has been driven to a great extent by Food and Drug Administration (FDA) requirements. The first noticeable direct statement to this effect was in the draft FDA guidelines issued in 1983 for the Development of Drugs in the Field of Osteoporosis.2 These draft guidelines still provide the basis for trial design in osteoporosis and clearly state that the data for assessing bone mineral density (BMD) from dual energy X-ray absorptiometry (DXA/DEXA) instruments should be centrally evaluated and reviewed. The European guidelines on postmenopausal osteoporosis follow a similar pattern.3 The Clinton-Kessler Oncology Initiative of March 19964 gave pharmaceutical companies an opportunity to use tumor shrinkage as evidence of therapeutic efficacy in clinical trials, although the usage of imaging had already been used with Betaseron.4 The FDA Guidance of March 13, 19975 provides an opportunity for biotechnology and pharmaceutical companies to expedite their respective clinical development by executing a single clinical trial with judiciously selected multiple endpoints in lieu of several separate clinical trials, each with its own endpoint. This FDA Guidance cites the approval of Berlex's Betaseron for multiple sclerosis, where clinical efficacy and magnetic resonance imaging (MRI) were the combined endpoints.  

The acceptance of multiple endpoints within a single trial places medical imaging in a more central role within clinical trial development. The most recent guidance was issued jointly with the Center for Biologic Evaluation and Research (CBER) and the Center for Drug Evaluation and Research (CDER), focusing on the image data requirements for submissions of medical imaging (contrast) agents and biological products.6 Furthermore, there are now a series of presentations available discussing the role of medical imaging with respect to the Critical Path Initiative.    

This change in the agency's attitude toward medical imaging is evidenced by the focus on the rigor and attention to detail that will be required when including an imaging endpoint in a clinical trial. The advances in technology have paved the way for regulatory agencies to now review medical imaging data and audit the procedures performed at the clinical sites without leaving their desk. Furthermore, in oncology, there are new draft guidelines provided by the FDA for the submission of therapeutics in the treatment of cancer7 that reference the imaging guidelines for medical imaging and biological products. Therefore, it can be assumed that these imaging guidelines pertain to all drugs in the oncology arena, which is supported by the recent creation of the Division of Medical Imaging and Radiopharmaceutical Drugs within the Center for Drug Evaluation and Research (CDER). This division is headed up by Dr. George Mills, the principal author of the imaging guidelines. 

ICLs now form an integral part of the clinical trial arena in all therapeutic areas where medical images have to be collected. The need for an ICL is therefore predicated on regulatory issues to standardize the data and to remove bias from site evaluation (ICLs fall into the heading "Central Processing Vendors" area in Figure 1.)

 Figure 1. Schema of the Central Processing Vendors in relationship to other key clinical trial participants. (ICL = imaging core lab.)			

Medical imaging is gaining an increasingly important role in clinical trials. This is due to three major driving forces in the industry.  First, there are the improvements in medical imaging technology and image quality, such as 3D Computerized Tomography (multislice CT) and standardized fast acquisition modes in MRI. Ultrasound has also seen major strides in improvement in imaging quality and increased use in cardiovascular applications. New ultrasound contrast agents have also contributed to improvements in image quality and diagnostic efficacy. In addition, nuclear medicine has also made major strides in PET and SPECT technology, due in no small way to the Centers for Medicare and Medicaid Services' (CMS) approval of PET for lung cancer and, more recently, other oncology and neurology applications. Other improvements in imaging technology include the combination PET/CT scanner and 3-Tesla magnet MR systems. Newly approved imaging contrast agents will also improve our ability to gain functional assessment of organ and tissue function and provide more direct measure of therapeutic effect within the target tissue.  Even within the standard acquisitions, there is a constant development of new analysis techniques that provide more information from imaging than had initially thought possible. 

The continuing need to shorten the drug and biologics development time continues to provide an impetus to use imaging endpoints in clinical trials—particularly in early phases of clinical development—and this will only be enhanced with the development of the new Pre-IND or so-called Phase 0 studies being suggested by the FDA. Early assessment of safety and efficacy can also be accomplished with many imaging applications. There is excitement about the impact that imaging will have on genomics and the search for disease-targeted therapy. The development of molecular imaging contrast agents and markers, particularly for PET and functional MRI, will be valuable tools in development of pharmacogenomic therapeutics. As imaging methodologies become more useful surrogate markers of disease, the ICL will play a key role in the design and execution of therapeutic clinical trials. 

As with the selection of all central vendors, sponsors must now carefully evaluate who they want to handle their central processing data and how these are going to be integrated into the overall trial management. Even if only 50% of the data going to the FDA (and not the 80% that has been claimed) passes through this box of service providers, it is imperative that sponsors ensure that the data is handled by companies with the experience that can ensure success in getting their data through the FDA review process expeditiously.  

, PhD, FICR, is with Bio-Imaging Technologies, Inc., 826 Newtown-Yardley Road, Newtown, PA 18940-1721, email: 

1. C.G. Miller and K. Noever, "Taking Care of Your Subject's Image:  The Role of Medical Imaging Core Laboratories,"  

2. Guidelines for Preclinical and Clinical Evaluation of Agents Used in the Prevention or Treatment of Postmenopausal Osteoporosis. Division of Metabolic and Endocrine Products: Food and Drug Administration, April 1994. http://

3. Notes for Guidance on Postmenopausal Osteoporosis in Women. Committee for Proprietary Medicinal Products, 2001. http://

www.emea.eu.int/pdfs/human/ewp/055295en.pdf

4. W. Clinton and A. Gore, "Re-inventing the Regulation of Cancer Drugs:  Accelerating Approval and Expanding Access," Food and Drug Administration, March 1996. http://

5. Cancer Therapies: Accelerating Approval and Expanding Access.  Food and Drug Administration, 29 March 1996. (No longer available on the FDA Web site.)        

6. Guidance. Developing Medical Imaging Drug and Biological Products.  Part 1.  Conducting Safety Assessments.  Part 2.  Clinical Indications.  Part 3.  Design, Analysis and Interpretation of Clinical Studies.  Food and Drug Administration: Center for Drug Education and Research, Center for Biologics Evaluation and Research, 17 June 2004. http://

www.fda.gov/cder/regulatory/medimaging/default.htm

7. Guidance for Industry. Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics. Draft Guidance, April 2005. http://

Articles

Feature Article

Technological advances have lead to an increasingly important role for centralized imaging laboratories.

Medical Imaging Core Laboratories

In May 2005, concepts on how cardiac safety of a new drug should be determined during its clinical development were formalized with completion of Step 4 of an intensive International Conference on Harmonisation (ICH) process, resulting in the document: 

ICH Harmonised Tripartite Guideline: The Clinical Evaluation of QT/QT

 Interval Prolongation and Proarrhythmic Potential for Non-Antiarrhythmic Drugs

]. This guidance has now been transmitted for implementation by the regulatory bodies of the three ICH regions—European Union, Japan, and the United States. The purpose of this article is to provide a summary of this guidance document with commentary on areas requiring more definition/details that should be of assistance in developing strategies for its practical implementation to ensure compliance with best practices. 

ICH E14 represents a significant landmark. It is the first globally harmonized regulatory guidance for assessment of cardiac safety during clinical drug development. Concurrently with ICH E14, a second ICH guideline also reached Step 4 status for implementation by the three ICH regions: 

The Non-Clinical Evaluation of the Potential for Delayed Ventricular Polarization (QT Interval Prolongation) by Human Pharmaceuticals

].  The objective of ICH S7B is to describe the types of studies that can be carried out during nonclinical testing to identify the potential for a drug candidate to delay ventricular repolarization and relate this effect to the concentrations of the drug candidate and its metabolites.

 The results of these nonclinical studies are intended to be considered in conjunction with other clinical studies of the sort that will be discussed in this article to provide an integrated assessment of cardiac proarrhythmic risk.   

Cardiac safety of drugs is the most common cause of drug withdrawal from the market or delay in or denial of regulatory approval for marketing. Examples include astemizole, cisapride, grepafloxacin, levacetylmethadol, lidoflazine, prenylamine, sertindole, sparfloxacin, terfenadine, and terodiline. In addition, it is important to note that numerous biologics have been associated with a QT

 prolongation effect and/or proarrhythmias. These substances include oxytocin, vasopressin, and gonadotropin-releasing hormone agonists and antagonists. Although this association is rare and the causality uncertain, the E14 guidance should also provide an aid in formulating clinical development programs for biologics as well.

The global clinical research process should anticipate that regulators worldwide will require cardiac safety data in accordance with the principles set forth in ICH E14. This will result in much more careful and uniform evaluation of the ECG profiles of new drugs.  Over time, significant data and information will be aggregated in a standard format to facilitate effective assessment of compounds within a therapeutic area and enable sophisticated data mining to detect patterns within and across drug classes. 

A primary focus of ICH E14 is the call for a Thorough QT/QT

 Study or, stated more appropriately, a Thorough ECG Trial (TET).

 interval, the more expansive TET designation points to the need that the trial should address the full description of all ECG changes observed. The TET is a robust trial to determine the cardiac (ECG) effects of a new drug on healthy subjects and, with exceptions that are detailed later in this article, is likely to be required for every new bioactive compound.

 In addition, a TET is also likely to be required when a drug already approved is being considered for development of a new dose, route of administration, or in a new patient population, especially when increased exposure and/or concentration are likely to occur. 

The TET should be conducted early in the clinical development program as soon as relevant pharmacologic and early clinical efficacy data are available. It is advisable to conduct the TET prior to exposing large patient populations with co-morbidities in later Phase IIb or III studies. Depending on compound specifics, a TET is usually conducted in early Phase II. This sequencing offers a benefit to sponsors, who reach an important milestone of understanding the cardiac safety profile of their product, to make a go/no go decision and to design proper ECG collection schedules in the target population based on the results of the TET. 

TETs may utilize a parallel or crossover design. Crossover studies are thought to provide an advantage in that classically they require a smaller number of subjects than parallel designs. However, the endpoint is not a difference between treatment and placebo on-treatment but a placebo-corrected change from baseline, and as such there is minimal advantage in the use of a crossover design for a reduced sample size. In contrast, parallel study designs are preferable for drugs with a long half-life for the parent drug or its pharmacologically active metabolites, or if multiple doses or treatment groups are being compared.

 As a practical matter, crossover studies take longer to complete and run higher risks associated with subject drop-out

 and potential period effects that may invalidate the trial. Experience of a leading ECG core laboratory across about 45 TETs indicates that sponsors have chosen parallel design in about 70% of trials, with multiple-dose studies running at a ratio of about 2:1 over single-dose studies.

 Single-dose studies are appropriate when the pharmacokinetic parameters of a single dose are identical to those parameters after multiple dosing to steady state. 

A typical TET design includes at least four treatment arms: placebo, positive control, therapeutic dose (single or multiple), and a supratherapeutic dose of the test agent. ICH E14 specifies that consideration should be given to addition of arms using a drug from the same class if the compound being studied belongs to a class that has been associated with QT/QT

 Sponsors have elected to add therapeutic comparator arms to TETs during the most recent two years for a range of scientific and competitive purposes. The use of a positive control with a well-defined QT/QT

 effect is intended to detect a change that represents the threshold of regulatory concern—typically about 5 milliseconds with an upper confidence bound of 10 milliseconds.

 This technique confirms the sensitivity of the assay used for a specific trial. Oral moxifloxacin has been overwhelmingly the preferred drug, but not exclusively so, used for this purpose. Moxifloxacin may be used as a single dose even in studies with multiple doses to steady state designs. In these cases, placebo is administered in the positive control arm for the days just prior to a single dose of moxifloxacin so that the positive control arm is treated identically to all other treatment arms in the trial. This treatment arm need not be blinded; if feasible, the active agent and placebo should be double-blinded. The positive control should be employed within the randomization schedule applied to the placebo and new agent, and thus not used either first or last in a crossover design or before randomization in a parallel design.  

The goal of the supratherapeutic dose is to expose healthy volunteers to the highest plasma levels and systemic exposure of the parent drug and active metabolites that could occur in the patient population, including those associated with maximal inhibition of metabolism of the drug and impairment of liver and kidney functions and target disease-related susceptibility. Obviously, if a maximum tolerated dose of the new agent has not been properly established in Phase I, it may require a separate study to determine whether the ideal supratherapeutic dose is tolerable and safe for the volunteer population enrolled in the TET.   

Collection of ECGs at multiple timepoints at baseline for each treatment group and again at the same timepoints for each treatment is an important design element of the TET. This technique is the most reliable way to determine if the trial conducted has minimized the large degree of spontaneous QT

 variability that can be observed within a single subject. Variability results from many factors, such as diurnal variation, effects of food, and other autonomic influences. Typically, three baseline ECGs are collected at each of many timepoints that match the collection of all on-treatment ECG timepoints. Further, meal composition and schedules, activity level, and environmental stress should be equalized between baseline and on-treatment periods. Conditions of ECG recording should always be consistent, e.g., supine, immediately prior to blood sampling. These special attributes for conducting a TET study require a well-equipped clinical pharmacology unit (CPU) with trained and experienced staff. 

Time-averaged versus time-matched analysis

Perhaps one of the most significant clarifications that evolved in the process of finalizing ICH E14 was the move from "time-averaged" to "time-matched" analysis. Earlier ECG trials usually employed the time-averaged approach. The "time-averaged" approach requires that all baseline ECGs for each subject are averaged and that all on-treatment ECGs for each subject are averaged. Subjects on active treatment are corrected for placebo and the mean change from baseline for each subject is calculated. The procedure is then repeated for all individuals in a treatment group. The obvious limitation of this approach is that the maximum effects on QT

 intervals are "diluted," and therefore, in absence of a separate analysis of maximum mean central tendency, a false negative conclusion may be drawn. To avoid this, the "time-matched" method indicated in the guidance was developed. In the "time-matched" method, each timepoint on-treatment (active, placebo or positive control) is compared with the baseline value for the corresponding timepoint. The value at each timepoint is achieved by averaging the ECGs taken at that timepoint for each individual. This enables one to calculate an increase in QT

) at each timepoint for each treatment arm. The parameter of interest is the largest difference (ΔΔQT

) between the change on the active treatment and the placebo (the two ΔQT

 at the same timepoint). This approach requires that the timepoints at baseline and on-treatment be identical. This allows for change from placebo analysis to help ensure that impact of spontaneous QT

In addition, an outlier analysis should be conducted. The focus of this analysis should be to identify the percentage of subjects (as opposed to the number of ECG observations) that exhibit a pre-determined QT

 change from baseline of 30–60 milliseconds or ≥60 milliseconds and a new QT

 value of >500 milliseconds). While other thresholds are frequently recommended (such as new QT

 values of >450 milliseconds and >480 milliseconds), these are often redundant or overlapping to the above more generally accepted criteria. Any new instances of morphological changes such as abnormal T or U waves should be noted. 

The "time-matched" method of analysis has significant implications on sample size when examined in conjunction with the threshold of regulatory concern of around 5 milliseconds as evidenced by an upper bound of the 95% confidence interval around the mean effect on QT

 The sample size for parallel or crossover studies results from defining the variance in QT

 duration and results in about 60–80 subjects (typically 65 subjects) exposed per treatment. Thus for a parallel study with four treatment arms, 260 (4 times 65) subjects are recruited, whereas for a crossover just over 65 volunteers (allowing for potential dropouts) are exposed to each treatment and washout period. 

If the upper bound of the 95% confidence interval of the "time-matched" effect on QT

 interval exceeds 10 milliseconds, the guidance designates the study as positive. The impact of a positive TET on subsequent trials will be discussed later in this article. However, it is important to note that a positive TET does not of itself imply that a drug is proarrhythmic. There is little doubt that drugs prolonging the mean QT

 by >20 milliseconds have a substantial likelihood of being proarrhythmic and that proarrhythmias could be observed during drug development. In contrast, the 5-millisecond threshold can seem overly cautious; yet, the potentially fatal torsade de pointes (TdP) arrhythmia can occur in the absence of QT

 prolongation. In practice, the risk associated with this scenario is too remote to be of clinical or regulatory concern; however, this fact does point out that even rigorous TET standards may fail to detect all drugs with a very low proarrhythmic potential.

Careful consideration should be given to the degree of QT

 prolongation in conjunction with the overall risk/benefit ratio of the compound. A range for basic risk assessment can be found in Table 1. Also, it is important to note that QT

 is an imperfect surrogate for the risk of TdP. While there is good evidence that the extent of QT

 prolongation relates to the degree of TdP risk, there could be other properties that might mitigate or enhance risk following prolongation of the QT

Table 1. Likely prognostic significance of mean placebo-corrected peak effects on QTc interval (clinical dose x 1)			

A drug developer faces the potential, albeit not very likely, scenario of executing an appropriate TET study that yields a single timepoint on a single subject showing a categorical response discussed earlier while the trial otherwise appears negative. In this case, the use of PK/PD relationships will prove important. If the slope of the plasma concentration of parent and possibly metabolites versus change in QT

interval following individual correction) is relatively flat, then an abnormal single timepoint is likely to represent a false positive signal. 

QT interval has an inverse relationship to heart rate. This means that it is important to correct the measured QT intervals for heart rate to determine if they are prolonged compared with those calculated at baseline. Because a TET is designed to detect prolongation of a relatively subtle threshold of 5 milliseconds, the impact of QT correction formulae is important. The most commonly used formulae are Bazett's and Fridericia's, and data corrected by these formulae are required for at least historical comparative purposes. For TET studies, data using both formulae should be submitted, along with uncorrected QT, RR, and heart rate data.

 In recent years, techniques that correct using QT/RR relationships using individual subject data have been developed. This approach is considered most appropriate for a TET because each individual's exponent for correction is defined as the single exponent that gives a heart rate to QT

 slope relationship as close to one as possible.

Beyond ICH E14, regional guidance may be implemented in incremental areas. For example, the FDA is currently implementing new cardiac safety data submission, review, and warehousing requirements that include support of an HL7 XML annotated ECG waveform standard. The FDA has entered into a Cooperative Research and Development Agreement (CRADA) with Mortara Instrument to develop a digital ECG warehouse, which will provide tools for FDA reviewers and the industry to manage, review, and analyze digitally submitted cardiac safety data and waveforms more efficiently.

The method of determining interval duration measurements (IDMs) is among the most critical, yet the most widely misunderstood, aspects of the ECG core laboratory industry.

 Manual IDM determination has long been acknowledged as the best method to determine the ECG IDMs, especially QT intervals. In this method, a highly trained and skilled professional marks IDMs on an ECG waveform without the aid of or visibility to any measurements determined by ECG collection devices or software algorithms. Today, the blinded analysis is typically accomplished using on-screen calipers to mark or "annotate" IDMs on a digital ECG waveform. The waveform along with annotations can be saved in a standard format and recalled for viewing later in the analysis process or during regulatory review by the FDA.  This truly manual methodology has been generally accepted to be more precise and has been preferred by sponsors for use in greater than 95% of the TETs contracted out to a leading ECG core laboratory.

 The manual standard process has been considered more precise because it addresses nuances in ECG waveforms that cannot be recognized and interpreted effectively by a software algorithm. 

Interim drafts of the E14 guidance made reference to "semi-automatic" IDM methodologies, in which software algorithms execute initial caliper placement and one or more individuals subsequently review already annotated waveforms on-screen and make determinations on which caliper placements require modification or "adjudication." This methodology may be appropriate for routine early and later phase studies where cardiac safety is not targeted as a primary or secondary endpoint and where immediate patient safety is the primary use for the ECG data. 

The final guidance addresses the significance of methodology and states, "the method chosen will depend on the level of precision appropriate for a given trial." The TET is cited as an example of a trial requiring particular attention to IDM methodology. The guidance as ratified makes no reference to the acceptability of semi-automated methodologies. It simply specifies "measurement by a few skilled readers (whether or not assisted by a computer) operating from a centralized ECG laboratory."

 Semantics of the parenthetical expression have already sparked a debate, with some claiming that the reference to computer assistance implies semi-automated measurements. In fact, one member of the ICH E14 Expert Working Group has stated unequivocally his understanding that this reference to computer assistance is not intended to include semi-automated measurements whereby trained professional readers operating from a central laboratory review the machine-read ECGs and recompute any intervals for which the automated placement of the fiduciary points is considered to be inappropriate.

Another important principle concerning methodology is the concept of consistency of a clinical development program with respect to data that are pooled for analysis. The TET stands alone in this regard, which means that a program manager may safely choose the E14 specified true manual measurement standard even if earlier trials employed semi-automated methods.  Later phase development for the same compound can leverage semi-automated methodologies if desired, provided that consistency at the level of data pooling is respected. Sponsors should insist on on-site, visual inspection of ECG core laboratory processing to confirm that the methodology to be deployed is the one specified by them.   

Continuous 12-lead Holter recording technologies have emerged as a just-in-time advancement critical to successful conduct of TETs. These platforms should not be confused with traditional two- or three-channel analog Holter devices used primarily for heart rate variability and arrhythmia analysis studies.  Continuous 12-lead Holter solutions have been used extensively in TETs performed by at least one leading ECG core laboratory.  The platform has been chosen for about 75% of the approximately four-dozen studies contracted to this laboratory. This methodology has gained regulatory acceptance, and multiple compounds have obtained approval, while others are in the approval process.

These platforms enable continuous 12-lead ECG collection throughout an entire 24-hour period. ECG waveforms are collected and stored on solid-state memory cards that are forwarded to the ECG core laboratory. Continuous 12-lead ECG platforms enhance precision, as the core laboratory can extract multiple ECGs at specific timepoints without having to rely on CPU staff for exactly timed collection. If an ECG at a timepoint is of poor quality, the core laboratory can extract a quality ECG closest to the specified timepoint. In addition, the technology is highly cost-effective in two important ways. First, CPU costs for collection of 15,000 to 20,000 ECGs are displaced by once-daily subject connection to the continuous recording device and occasional safety ECGs collected with traditional 12-lead equipment that features local printing capabilities. Second, the ability to extract additional timepoints for analysis from the continuous 12-lead recording platform provides an easy mechanism for adding additional timepoints to a study retroactively to address unexpected issues, such as the behavior of a metabolite. 

ICH E14 recognizes that TETs may not be possible with some compounds due to safety or tolerability concerns, e.g., cytotoxic oncology agents. It may be possible that a TET or a variation can be conducted in patients. When this is not possible either, other means of focusing on the potential for QT/QT

 prolongation should be explored, such as collection of ECGs at multiple timepoints across multiple doses in a tightly controlled setting during early clinical pharmacology studies.   

If a drug is administered under a continuous cardiac monitoring setting, then the need for a TET study may be reduced.  Also, there may be a reduced need if a drug is not absorbed system-wide, such as with certain topical products and therapies administered locally. 

Impact of TET results on later phase development

TET results are key to defining cardiac safety data collection and analysis in later phase development. In almost all cases, a negative TET will allow for routine collection of ECGs in later phase trials in a manner consistent with current practice for the relevant therapeutic area. However, if the TET is negative and non-clinical results were strongly positive and the discrepancy cannot be explained by data, then expanded ECG collection and analysis in later phase development should be considered. 

More intensive ECG collection and analysis is required subsequent to a positive TET. The focus should be on fully characterizing the QT/QT

 effects of the new drug candidate on the target patient population, with emphasis on dose- and concentration-related effects. Analysis should include both mean QT/QT

 change and outliers. In addition, particular interest should be placed on patient subgroups such as those with: 									

Electrolyte abnormalities, e.g., hypokalemia

Impaired drug metabolizing capacity or clearance, e.g., due to liver or kidney impairment, or drug interactions

Other considerations and future directions

ICH E14 establishes a clear mandate for the important role of the TET in clinical development programs. However, it is important to consider other data and issues to derive a comprehensive "cardiac safety package." Chief among these are key nonclinical studies and verification of cardiac effect through routine monitoring following a negative TET. Also important are relative risk/benefit and comparison to other available in-class therapies. Negative nonclinical data and a positive TET need not result in a "black box." Even in the face of a negative TET, a strong nonclinical signal may still require intense monitoring throughout the entire development program. 

A consistent high-level study design framework and efforts to standardize the format for data analysis by the FDA and others will expedite the aggregation of data and information that will expand our understanding of the nuances and complexities of the effect of compounds on cardiac function.  The role of ECG core laboratories will continue to grow in scope and importance, providing an important trusted third-party function in analysis of data, along with the science, process, and technology required to meet the rigorous demands of both high-intensity TETs, requiring close collaboration with sponsors and CPUs, and massively distributed later phase trials. 

 is senior vice president and chief marketing officer with eResearchTechnology, Inc., 1150 U.S. Highway 22 East, Bridgewater, NJ 08807, (908) 203-6430, fax (908) 947-5122, email: 

, MD, is clinical professor of medicine at the University of Pennsylvania School of Medicine, Philadelphia, PA, and chief scientist with eResearchTechnology, Inc., (215) 972-0420, fax (215) 972-8775, email: 

, BSc, MD, FRCP, is a pharmaceutical consultant. He was previously a senior clinical assessor with the Medicines and Healthcare products Regulatory Agency, London, UK, and EU topic leader and member of ICH E14 Expert Working Group, email: 

1. ICH Harmonised Tripartite Guideline: The Non-Clinical Evaluation of the Potential for Delayed Ventricular Polarization (QT Interval Prolongation) by Human Pharmaceuticals, S7B, Step 4, 12 May 2005, Page 2, Section 2.1. 

2. V.F. Mauro, J.F. Bingle, S.M. Ginn, F.M. Jafri, "Torsade de pointes in a patient receiving intravenous vasopressin," 

3. B. Charbit, C. Funck-Brentano, E. Samain, V. Jannier-Guillou, P. Albaladejo, J. Marty, "QT Interval Prolongation After Oxytocin Bolus During Surgical Induced Abortion," 

Implementing ICH E14 to define cardiac safety in new drug development

A Practical Approach to Cardiac Safety

Institut De Pathologie B35  Chu Sart-Tilman

Resources

Clinical laboratories arranged by type of diagnostic service provided

Lab Services Directory

A variety of economic and social pressures have fueled a widespread search for reductions to the cost of research and development (R&D) in the health care industry.  Pharmaceutical companies (pharma) and clinical research organizations (CROs) have been working vigorously to improve their productivity and return on investment by modifying processes, decreasing cycle times, and implementing improvements wherever possible.

Furthermore, experts believe that pharma companies previously averse to strategic alliances are being required to find more long-term development partnerships.  This trend is expected to continue due to the enormous competitive emphasis on demonstrating a positive return on R&D investment and continuous need to bring significant new products to market.

  While ultimately beneficial, management of relationships with multiple strategic partners further complicates efforts to reduce the cost of R&D, improve operational efficiencies, and benchmark performance.  Consequently, the need to better manage the efficiency, productivity, and economics of long-term drug discovery through the use of performance metrics has become a top priority for outsourcing teams involved in clinical trials. The value of performance metrics has taken on a dual meaning: to measure and compare performance between service providers and to analyze operational proficiencies that reveal potential elements to be adjusted during the conduct of the clinical trial. 

One aspect of clinical research that offers opportunity for application of performance metrics is that of central laboratory services. A central laboratory is a network of people, capabilities, and facilities structured to process human specimens for diagnostic testing that generates information subsequently reported to participating clinicians and the organization sponsoring the research.  The primary role of a central laboratory is to obtain accurate, timely diagnostic testing data to support a clinical trial protocol.  

Potential benefits to central lab metrics

Due to the diverse nature of clinical research, many companies have invested a substantial amount of time and resources to develop standard central laboratory performance metrics that are used to benchmark service providers. When the design and application of central laboratory performance metrics are done well, a number of benefits can be realized. These include: 					

Metrics can communicate and reinforce a clear set of standards for performance and provide measurement of performance against those standards.

Identification of areas for improvement and potential issues can be achieved in a timely manner, allowing for early corrective action.

Performance against key metrics can provide an objective source for feedback to the central laboratory and serve as a means of comparison between central laboratory service providers.

Measurement of overall progress of the clinical trial and forecasting of future trends can be accomplished with the use of selected metrics. 

Financial and budgetary status measurement and forecasts can be provided through analysis of performance metrics.

The fact-based and objective information and feedback provided by well-designed metrics serve as a sound foundation for fair and consistent relationships between the sponsor client and central lab provider.

Full realization of the benefits available through the use of central laboratory performance metrics requires thought and planning in their design, selection, and implementation. Some key considerations in successfully implementing and managing the overall process include: 					

Use of performance metrics is a powerful asset in managing the performance of central laboratory service providers, but it is not a panacea, nor a substitute for a robust process for relationship management. Having realistic expectations regarding the utility and impact of metrics on the overall relationship is essential.

The primary strategic goals driving the performance metrics process should be directly reflected in the design, implementation, and management of the metrics utilized. For example, if financial control is a primary goal of the process, appropriate metrics that provide insight into financial status should be included in the process. 

A disciplined approach to application of performance metrics is critical in keeping the process manageable and meaningful. The total activities contained within the central laboratory process offers a high number of variables, which can be measured and subsequently used as performance metrics. Unless discipline in selection is maintained, an overabundance of measurable parameters can easily be selected, creating significant work burden both at the central lab (in gathering and arranging the data) and sponsor (who read, analyze, and interpret the data). Selection and management of performance metrics using the "vital few" approach greatly enhances the overall impact of a metrics strategy.

The performance metrics chosen should be relevant to the role of a central laboratory within the clinical trial process. Measuring study enrollment as a central laboratory metric, for example, is at best an indirect measure of lab performance; the lab has little impact on enrollment beyond the provision of the specimen collection kits to the investigator site, which is a relevant and measurable indicator of central lab performance and therefore a useful performance metric.  

The performance metric should provide information and insight that is actionable by both the central lab and sponsor. This is a key component of the "vital few" selection process noted above. Given the information technology capabilities currently available, it is simple to track variables down to parts per million impact levels, but whether an error rate finding of 3 parts per million on a central lab test process is actionable in the sense of possible improvement is questionable, thus making such a measurement a less than ideal candidate as a performance metric.

Use caution in the degree in which data from performance metrics are used to forecast study progress, in both the operational and financial sense. The significant number of variables involved in the clinical trial process makes "straight line" forecasting a challenge; using metrics as indicators or confirmation of progress (versus absolute forecasting) is more suitable for the information gained by most metrics.

The performance metrics should be applied consistently from design through implementation and use; the metrics used should periodically be reviewed for impact and utility—those rarely noted or used can be eliminated and replaced with more meaningful measures. 

Maintain discipline in the use of performance metrics as part of an overall relationship management strategy and avoid using metrics as a punitive device or weapon.    

Designing a scorecard for central laboratory services

The responsibility for developing a performance metrics scorecard is equally placed on the sponsor and the central laboratory participating in a clinical trial. When a critical, actionable, and measurable metric is identified and mutually agreed upon, process improvement is enabled. Recently, some companies have undertaken to collect actionable metrics as a means for facilitating rapid change through performance gap analysis while a study is underway, and although outsourcing groups have traditionally used metrics primarily to manage costs, recent reports indicate that their primary responsibility is to increase supplier productivity.

  Therefore, selecting an appropriate set of performance metrics is critical to both the sponsor and the central laboratory. As noted above, in the clinical research environment, the use of metrics can be overdone considering the scope of an average global clinical trial in a challenging therapeutic area, and decision makers can find it very tempting to track a large number of metrics, which can lead to a disproportionate amount of time being spent on managing the data as it accumulates over time. Therefore, clinical researchers should adopt a "vital few" or "less is more" approach to collecting only those metrics that are actionable or meaningful.   

A combination of laboratory metrics, financial outcomes, and study team satisfaction ratings are typically the key components of a comprehensive central laboratory services scorecard.  These categories encompass the performance expectations for the various interested parties within the sponsor organization. The attempt to drive process improvement is the premise by which performance metrics are identified and categorized; however, it is unfortunate that outcomes are analyzed more routinely than processes. A well-balanced scorecard should incorporate a combination of both process-based metrics and outcome-based metrics.   

While financial outcomes are bottom-line oriented, they are not particularly useful in driving rapid change nor do they routinely impact productivity. The value of financial metrics is to provide information regarding the actual "burn rate" of the project budget in terms of service fees, pass-through costs, and other expenses. 

Study team satisfaction ratings are becoming more common on scorecards because they offer easily quantifiable metrics that reveal trends regarding the customer–sponsor relationship.  Depending upon the methodology used to obtain customer feedback, a detailed view of functional areas can be highlighted to uncover specific information regarding opportunities to increase efficiency and improve outcomes. This information can be used to impact both short-term changes during the conduct of a study and to illuminate issues that require long-term process enhancements.   

Categories of central laboratory performance metrics

Well-designed central laboratory performance metric categories essentially reflect the scope of responsibilities of a central laboratory within the clinical trial process. There are three general categories of scorecard metrics: Study Start, Study Management, and Study Close. The purpose for grouping performance metrics into these categories is to differentiate between functional areas and as a means for driving process improvements.  These categories are comprised of fundamental processes and critical outcomes, including many that are project specific. In practice, grouping project-specific metrics under these categories is the first step toward identifying a set of common benchmarks to use across the central laboratory industry. Outcomes-based metrics are considered by industry experts to be common to central laboratories, i.e., number of kits shipped, number of demographic holds, TAT of specimen results, and time from LP/LV to database lock. Since performance metrics must be actionable in order to drive change, they must focus on processes and standard operating procedures (SOPs), which vary from company to company.   

Performance metrics that pinpoint operational processes can drive efficiencies and improve productivity. These process-based metrics uncover issues that can sometimes be resolved by modifying SOPs, increasing training or allocating additional resources to meet study timelines and contractual obligations.  For example, in order to measure improvement over time, a metric that measures how a patient specimen is handled is much more valuable than one that measures the outcome, i.e., the number of specimens handled. 

Evaluating processes by measuring outcomes

Within each category there are specific processes and outcomes to be analyzed that reflect progress toward achieving study goals. The Study Start processes are arguably the most important ones to support a clinical trial due to their direct impact on project timelines, which in turn significantly impact the overall project budget. Therefore, the activities that surround communication, setting expectations, and establishing project timelines are critical. The number of change orders (CO) made to the original, approved scope of work (SOW) is a key indicator of whether the initial communications were well managed.  Another example is adherence to study timelines that control getting the initial test supplies to the study sites, programming the study database, and validating the database. Outcomes associated with each of these processes are completion of the tasks on time and the number of days to complete the task.   

Once a study has been initiated and sites are enrolling patients, Study Management performance metrics are tracked and analyzed through the duration of the study, which can run for months or years.  Performance metrics collected during this phase have the greatest impact on driving process improvements, assuming that the metrics selected are actionable and can positively impact study outcomes. For example, once sites receive their initial supplies, the processes that control resupply and getting specimens to the laboratory become an ongoing priority for project managers and coordinators assisting with materials and logistics. Shipping specimens to the central laboratory for testing in accordance with project specific requirements is only the first step in a series of interrelated Study Management processes and outcomes. Other examples of well-known study management performance metrics include: turn-around time (TAT) of laboratory results, reporting results to sites, percent of demographic holds, and percent of data corrections. Outcomes associated with these processes usually involve time requirements to complete the task, although actual counts and percentages are also frequently tracked project outcomes.   

The completion of a study, in terms of central laboratory responsibilities, is usually defined as the period from last patient/last visit (LP/LV) to final database transfer. The processes and outcomes associated with Study Close performance metrics are often very few. Most common are activities that occur between LP/LV to database lock and database lock to final database transfer. An outcome associated with each of these processes is either time-related or a measurement of the number of transfers that occurred.   

 Figure 1. Common central laboratory performance metrics by study phase.			

Figure 1 indicates common central laboratory performance metrics by study phase. Some performance metrics such as financial measurements and customer satisfaction ratings are outcomes that transcend each of the three metric categories, as these outcomes can be linked to different processes in more than one category. Examples of financial outcome metrics include percent of total spend versus budget forecast and deviation from original project budget due to change orders. Customer satisfaction performance metrics can also be very general if the ratings measure subjective questions such as "comparison to other central labs"; however, specific feedback should also be obtained that highlights operational performance in one or more of the three study categories. An example of a customer satisfaction outcome is the number of comments made about a specific area of operations. Figure 2 indicates examples of outcomes used on central laboratory scorecards. 

Figure 2. Examples of outcomes used on central laboratory scorecards.			

A clearly defined set of central laboratory performance metrics is essential in selecting and managing a central laboratory service provider. An optimized set of metrics is a valuable asset in managing the sponsor–supplier relationship and can be used to drive efficiencies during the life of the trial by focusing on both outcomes and processes. Measurement of operational processes helps to pinpoint areas for improvement, which are in turn measured by study outcomes. These resulting improvements drive long-term efficiencies and have a direct positive impact on productivity and managing the cost of research and development. By following the "process versus outcome" model and designing and implementing relevant and meaningful central laboratory performance metrics, sponsor teams can develop well-balanced scorecards that accurately measure central laboratory performance.   			

, is director of strategic alliance and global marketing, and 

, is manager, bids & contracts, all with Quest Diagnostics Clinical Trials, 1201 South Collegeville Road, Collegeville, PA 19426, (610) 454-6542, fax (610) 983-2120, email: 

Anthony.J.Santicerma@questdiagnostics.com

1. E. Pena, "Making Metrics Matter: The Changing Paradigm of R&D Metrics," 

2. L.D. Fitzsimons, "Stronger Together," 

3.  K.A. Getz, "Entering the Realm of Flexible Clinical Trials," 

A clearly defined set of performance measures is an integral part of the central laboratory selection and management process.

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