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CONTRACT RESEARCH


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Adaptive Trial Designs


Sometimes studies utilize an adaptive trial design that allows for modification of specific components during the trial, which also require careful consideration and planning in relation to the randomization methods to avoid bias. Adaptive trial designs are utilized to ensure certain changes to the study will be made based on data analyzed during the trial with a focus on getting results more quickly and at times, involving fewer patients. Any and all potential changes are clearly identified in advance in the protocol and statistical plan. Further, the design of such potential changes is generally based on results from previous trials, research on similar trials, feedback from regulators on safety issues and other considerations.


One of the more common uses of an adaptive trial has been dose finding. For example, a study may start with several arms, perhaps at doses of 10 mg, 20 mg, 30 mg, 40 mg, 50 mg and a placebo. Initially, the IRT may randomly assign patients to one of these dosing arms with equal probability. Then over time, as safety and efficacy factors are examined, either in an automated fashion or by an unblinded team, the randomization schema is altered by either changing the ratio in favor of the doses with better outcomes or by dropping an arm altogether. In this example, if the 50 mg dose was causing a high level of adverse events, it might simply be dropped and the IRT would no longer randomize patients to that dose. On the other hand, if the 10 mg dose was producing no health benefit, it too could be dropped. By the end of the trial, the majority of patients will have been randomized to one of the optimal dose levels.


Staying with this simple example of an adaptive design, if the medication was in tablet form, would it make sense to manufacture five separate tablets for the active medication? Doing so could be very expensive and if we rule out use of the 10 mg and 50 mg early in the trial, all that medication would be wasted. An IRT vendor with experience in these study designs can collaborate with the sponsor and the drug supply vendor to make recommendations that could easily be built into the system to optimize the entire supply chain for this, and for future studies. In this case, perhaps the team would suggest that manufacturing tablets in 10 mg, 20 mg and 30 mg doses would suffice. Then each patient could be given two vials with the clear instructions to take one tablet from each vial when it is time to take their medication. Table 2 shows a simple design for this scenario.


The table also shows how the IRT system could manage alternatives if stock levels of a particular dose were running low. Of course, several other configurations are also possible and again, an experienced team can present the optimal set up and can readily implement it in the IRT.


Other Considerations


The unexpected is bound to happen once a study is launched into the real world, but a thoughtful design scheme will help to ensure randomization methods aren’t compromised. For example, on occasion, a site may encounter a stock-out issue, meaning that the treatment to which a patient has been randomized is currently not in stock at the site. When this occurs, it’s a good protocol to have the patient return to the site, but this is inconvenient for both parties. A better solution may be to allow “forcing,” which means that the system automatically puts this patient onto a treatment that is currently available. Then the system would assign a higher probability that the next patient in the study would be assigned to the treatment group that was just skipped due to the stock-out. While forcing is not technically random, it is permitted by regulators as long as it is not occurring frequently. An experienced vendor can provide the necessary guidance to help ensure the quality


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CREATING THE PATH FOR SUCCESS


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and integrity of the study design and its execution throughout the trial’s lifecycle.


On the topic of human expertise, there is a current trend toward rapid development of IRT systems and this is bringing many benefits to clinical research. Chief benefits include establishing better, more consistent standards as well as validated and reusable libraries and modules that reduce the time and burden in system testing and that lead to higher quality and reliability. However, there are many other factors involved in the design, deployment and conduct of a study and having a team of experts who understand the critical success factors, from manufacturing and packaging through accountability, returns and destruction, is essential.


Summing It Up


Randomization is a key element in the success of a trial. An effective randomization plan built into an IRT system forms the basis of an adequate and well-controlled trial that is free of bias, maintains the study blind and ensures that the desired balance and treatment allocation ratios are preserved throughout the trial. Modern systems and simulation techniques are in place that have also greatly reduced the timelines to implement an IRT system while also providing high- quality, reusable algorithms with a greatly reduced validation effort. Finally, there is no replacement for a qualified and experienced team who can provide guidance on all the critical factors involved in running a successful trial.


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