In earlier installments to this series, we reviewed how advanced and reliable interactive response technology (IRT) systems can be used to manage the need for different visit schedules per arm, the complexities of central vs. local sourcing of standard-of-care treatments, and other RTSM-related challenges oncology clinical trials.
Here we review how a flexible IRT system can address complexities regarding the need for rescue medication and its impact on study drug expiration dates and drug wastage.
Rescue Medication – Impact on Study Drug Expiration
In addition to not knowing how many visits each patient will complete, oncology clinical trial sponsors face unknowns as to if patients might need to discontinue treatment and begin using rescue medication – or for how long. This raises concerns not only for patient safety but for study budgets as well.
Because oncology treatments are typically very expensive, sponsors strive to minimize the amount of study drug wasted during clinical development. Any time a patient experiences an adverse event and must pause treatment to begin rescue medication, there is a risk of the study drug expiring before the patient can resume treatment.
To reduce the risk of excessive drug wastage but to ensure study drug availability when the patient can continue treatment, the IRT system must be designed with flexibility. Not only because when the patient resumes treatment they may be on a different visit/treatment schedule, but also because most often it’s unknown how long the patient will be on rescue meds.
When designing an IRT system for oncology trials, Calyx assumes that rescue medication could be needed at any point – during or in between site visits – and that if needed, the patient will remain on it for the maximum amount of time allowed by the protocol. The IRT design can be configured to support monitoring of the length of time in the rescue status for a patient. Understanding the real-world application of the rescue process is key to identifying the most efficient IRT design for the medication that will be dispensed.
A good IRT partner will wish to understand this aspect to avoid unnecessary waste of kits and to ensure the required flexibility is included to place the patient on the correct visit post-rescue intervention. This can be used to ensure investigative site personnel can restart treatment at the expected next scheduled visit aligned with the protocol if the patient is able to continue.
The next scheduled visit could be impacted by the rescue allocation, with adjustments required to move the patient in the visit schedule. These are rules that can be included regarding when the IRT is required to assist the investigative site personnel. However, if site staff are suitably trained, their selection of the next scheduled visit at the patient’s restart point could also be considered.
How Much Medication is Needed?
Additionally, Calyx solution designers can apply Fractional Prediction, one of the advanced inventory management strategies available through Calyx IRT. Fractional Prediction allows for flexibility based on site recruitment and is helpful for minimizing the amount of standard of care and/or rescue drug needed at each site, based on the number of patients enrolled.
With a Fractional Prediction strategy, the IRT system can be designed with a fraction amount that automatically tweaks the amount of drug (rescue drug, in this case) needed at each site based on the number of patients for the fraction.
Consider this scenario. If one site has ten enrolled patients – and it’s highly unlikely that all ten will need rescue medication at one time – the system can assign a fraction, say, 0.2, and only send 2 packs of rescue medication to accommodate that number of patients.
But if a site has only one enrolled patient, then the 0.2 is rounded up to 1.0 and the system sends only one pack of rescue medication.
The fraction that is predicted is an important variable: setting the fraction too high can increase drug wastage while setting it too low could result in dispensing failures. Calyx solution designers leverage their extensive experience from having designed thousands of effective IRT algorithms and work closely with the sponsor’s trial supply team to optimize the fraction applied, ensuring the risk of failures is low while keeping the minimum amount of medication at each site. If the assumptions used to set the fraction are not borne out during the running of the trial, the figure can be amended.
A Fractional Prediction strategy ensures drug availability without incurring excessive drug wastage and removes burdens for site personnel who would otherwise need to constantly change their supply schemes to meet changing oncology trial patients’ needs.