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Background: /Aims: In early-phase cell therapy trials, each dose level being studied is defined by the number of cells infused into the trial participant. The issue of dose feasibility presents itself when the desired number of cells is not reached in the expansion process. Consequently, dose assignments for some patients may deviate from the planned dose according to the chosen design. Widely used algorithmic designs aren't flexible enough to handle this complication and can lead to the exclusion of safety data from the dose assignment algorithm. This article studies the impact of dose feasibility challenges on the behavior of the 3 + 3 decision rule. Methods: We conducted a simulation study across six dose-feasibility and dose-toxicity scenarios. Trials are simulated using the 3 + 3 algorithm. We present a novel algorithm for random feasibility curve generation. We used this algorithm to conduct a large-scale simulation study across 100 random scenarios. Results: We found that the 3 + 3 has problematic characteristics due to the exclusion of safety data from the algorithm. Ignoring toxicity data can complicate the allocation of subsequent patients in the trial and can bias the final maximum tolerated dose recommendation for the next phase of drug development. Conclusion: Our study demonstrates that excluding safety data from the 3 + 3 algorithm can be detrimental to trial conduct. Furthermore, there are existing methods that are flexible enough to include data that is observed away from the planned dose. We recommend that these methods be used in conducting phase I cell therapy trials.