Design of assistance tools to manage robotic production with Kiro Oncology®

A. Mouradian1, M. Jobard2, M.-L. Brandely-Piat1, R. Batista1,2 1- Unité de Préparations Stériles Ophtalmologiques et Oncologiques, 2- Unité d’Assurance Qualité, Service de Pharmacie clinique, GH Centre Université de Paris, AP-HP, Hôpital Cochin, 27 rue du faubourg St Jacques, 75014 Paris, France

Introduction
The Kiro Oncology® robot (Grifols, Spain) ensures mainly the preparation of chemotherapy Standard Doses (SD) in our unit. It works in cycles and can produce from 1 to 8 preparations per cycle depending on their composition. The main difficulties encountered by operators to manage robotic production are the design of optimal cycles, the assessment of the automatic compounding time and the management of the potential alarms. However, cycle optimization and timely resolution of technical problems are correlated to productivity*. The aim of this work is to provide assistance tools to users to manage robotic production.

Material and method
An analysis of the limitations related to the robot was carried out in order to identify the critical points for the design of the cycles. Data relating to robotic production was collected for 6 months (type of SD cycles, automatic compounding time). The alarms and the means implemented to solve the technical problems were also collected between September 2019 and May 2021.

Results
The maximum number of vials per cycle was identified as the main limitation to optimize the cycle. This result led to the development of a guide with cycles of 8 SD, especially for drug requiring more than 2 vials per preparation (etoposide phosphate; daratumumab). A table listing the number of required vials for each SD prepared in our unit was also established. A total of 154 cycles were analyzed. The mean time for automatic compounding was determined for 31 SD including 9 drugs. It varied from 2 ± 0.3 min to compound an irinotecan bag (200 to 340 mg) to 8.3 ± 0.4 min to compound a rituximab bag of 1000 mg. This analysis led to define a list of 12 standard cycles with the average automatic compounding time. Over the analyzed period, 34 different alarms were collected, including 21 with an occurrence ≥ 5. A table summarizing the action to be taken for the most frequent alarms was set up and displayed near the robot to facilitate the resolution of technical problems.

Conclusion
By facilitating the design of cycles and providing a rapid solution to solve technical problems, the tools will make it possible to ensure constant productivity regardless of the operator’s level of training. An evaluation of these tools will soon be carried out in order to establish operator satisfaction and determine the impact on productivity. A request was also made to the supplier to integrate an optimization tool directly into the software of the robot.

* Riestra et al. Robotic chemotherapy compounding: A multicenter productivity approach. J Oncol Pharm Pract. (2021) Feb 11

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