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In the past thirty years, drug companies involved in late-stage drug development have initiated Phase II testing in humans in clinical research units typically located in the United States, the United Kingdom, Canada, and Western Europe. However, an increasingly intense competitive environment1 and the shrinking pools of treatment populations in the traditional North American and Western European markets have forced drug companies to approach emerging markets to conduct research and secure trial enrolment. This article analyzes the unique challenges posed by international clinical trials, as well as systematic, quantitative, and integrative operational approaches to overcome the challenges. A recent, real-life case study is included to exemplify how international trials are managed to ensure a consistent output of high quality data, on time and without surprises.
Lawrence A. Meinert, Vice President, Medical and Scientific Affairs, Covance
International trials’ success depends on the management of variability. When performing trials abroad, the number of potential pitfalls, site idiosyncrasies and country-specific regulatory, ethical, and administrative requirements increases exponentially. Any challenges which previously plagued trial performance in ‘traditional’ markets tend to multiply, and no single adjustment can be counted on to remedy those challenges.
Instead, integrative, quantitative trial management is required, and it needs to be geared toward handling not only current day site performance variance or variability, but also the variability in the underlying patient population, which can dramatically impact trial outcomes, especially in the complex longer term studies that are increasingly common. This is true both in terms of effectiveness versus varying levels of standard care, patient population baseline health, common co-morbidities and -medications (including traditional and herbal medicines), and in terms of safety versus varying level of adverse event (AE) reporting.
Patient populations suffering from the exact same disease can vary widely from one country to another in terms of the local healthcare system and culture. For example, while Western European and U.S. patients generally report all adverse events, Russian patients are unlikely to report anything short of a serious adverse event. Understandably, such cultural and wholly non-drug related differences in the reporting of AEs could reek havoc on the conduct of
Pharmacovigilance. These variations shine a bright light on the need to maintain rigorous control in an era of global dispersion. Systematic quantitative and integrative operational approaches are necessary to manage this increased variability.
Approaches to Proactively Managing Performance Variability
a. The Predictive, Proactive, Preventive clinical trial model (the Covance P3 model)
Covance has focused for the past four years on a formal re-engineering of our approach to the clinical trials process to focus on predictive, proactive and preventive measures, centered on a consistent dedication to site interaction and planning.
A detailed review of our own experience servicing more than 12,000 clinical trials revealed that in today’s drug development paradigm, an increasing proportion of overall costs is being devoted to data verification and remediation, trying to address performance consistency challenges as they invariably crop up during the trial process.
However, we not only focused on diagnosing challenges, but also on overcoming them. Hence, the review led us to recast our own internal teams and processes based on a proactive planning paradigm. Specifically, we have developed processes to build quality into the initial selection, initiation, and training of investigator sites, and developed ongoing processes and tools for tracking and optimizing the program throughout its entire lifecycle.
Our experience with this site-centric operational platform indicates that an approach favoring risk prevention rather than remediation of investigator errors delivers improved productivity, lower operational risk, and improved scientific robustness — not to mention increased investigator satisfaction. This paradigm, which we call the Predictive, Proactive, Preventative (P3) clinical trial model, features:
Predictive feasibility and modeling — analyzing and leveraging similar study experiences to optimize study design and site selection to best meet the requirements of a specific study, as previously described.
Proactive project planning — anticipating sources of poor performance and shifting study budget allocations away from error detection and repair activities toward study center performance prediction and risk mitigation.
Prevention of errors — emphasizing new approaches to investigator grants that encourage improved pre-activation preparation efforts, and promoting and rewarding primary data quality.
b. Site-Centric Philosophy
This systematic, quantitative operations-driven trial management platform is coupled with — and driven by — our site-centric philosophy, which places the investigator at the heart of the study. We specifically organize project teams around the individual investigative site in order to maximize patient accrual and improve data quality. This approach has led to operationally smoother studies and, subsequently, to higher investigator satisfaction which translates into satisfaction with the sponsor and drug.
c. Integrated Trial Management
From an overall trial perspective, these predictive, proactive, and prevention-focused tools and approaches for managing clinical trial sites tie into what we term Integrated Trial Management. This concept includes the closely coordinated use of central laboratory and cardiac safety services to further optimize trial processes and reduce duplication of efforts and resource and time waste.
The payoff of this systematic, quantitative operations-driven trial management platform coupled with our site-centric approach is a remarkable drop in the incidence of the factors most frequently causing study delays, including patient recruitment and enrollment delays.
Case Study: Pulmonary Disorder, Phase III International Trial
Situation
The client, a U.S.-based biotechnology company, was investigating a drug for use against a rare and fatal pulmonary disorder and had moved the drug to Phase III trials. There is no known cause for this disorder, necessitating an exacting method-of-exclusion diagnostic process, which carries with it a high risk of screening failure. On average, patients have a life expectancy of approximately five years following disease onset. Patient recruitment would be very challenging considering the very limited prevalence of the disorder and its lack of predictable features such as geography, ethnicity or seasonality.
The client was aware that only Centers of Excellence would qualify as investigative sites, and had done some in-house feasibility work to determine sites and recruitment targets. The funding and future survival of the company would be severely impacted by whether these targets were met, because the targets had been widely broadcast to the investor community.
Solution
Early in trial implementation, using modeling and thorough discussions with the sites and client, Covance predicted that hitting the patient recruitment targets and deadlines would be very unlikely. To clearly document the reasons why, as well as identify amendments to support alternative solutions, we performed a more extensive feasibility analysis. This in-depth analysis uncovered a number of factors that would negatively affect recruitment, including competing protocols, standard practice (off-label usage) concerns, and the introduction of new European regulations that would render a large portion of sites unfeasible for an interim period, based on geography alone.
As part of the prediction of the obstacles facing the trial, we initiated informatics modeling to forecast ways to meet the patient recruitment targets, and strategic amendments. This scenario-based contingency planning triggered several changes including a geographically optimized and intensified site recruitment program. Also, we initiated a program of visits by both Covance and the client’s physicians to the targeted sites to address negative perceptions about the drug’s promise, of which the client was previously unaware.
To help sites prevent screening errors, and help monitors ensure data consistency, we created an easy-to-use online tool. This tool contained preprogrammed inclusion and exclusion criteria and fixed formulas permitting the addition of variable patient information and results. Prompts would clearly indicate patient suitability for the trial, and flag any data inconsistencies.
In parallel with efforts to improve site enrollment for the first part of the trial, we also worked to prevent delays in upcoming trial stages. This effort focused on targeting European sites that, due to the introduction of new European legislation, were unfeasible for an interim period, but which would once again become feasible, coinciding with subsequent recruitment needs.
Finally, to ensure the interim analysis timelines, we predefined the conventions for the required data, and proactively reviewed current data. Additional data needs were clearly isolated which permitted resources to be proactively and strategically directed toward acquiring these specific datapoints through tightly scheduled monitoring activity at select sites.
Payoff
Covance was able to meet the goal for stage one recruitment within the agreed upon timeline. The interim analysis and next stage recruitment are on track as well, due to predictive analysis and proactive contingency planning. As a result, the sponsor has been able to meet crucial investor expectations.
Data quality was significantly enhanced and variance reduced through the up-front deployment of online tools to prevent and flag errors. Sites were motivated for enrollment and better performance both through sponsor visits proactively addressing their concerns, and through time saving tools to eliminate screening errors that would steal time and resources from eligible patients.
1According to FDA data released in June 2005, 6,079 new studies were started in the period 1981-1985, 16,435 new studies 1991-1995 and a record 36,839 new studies in 2001-2004 (State of the Clinical Trials Industry 2006, Thomson
CenterWatch)
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