New Approaches to Assess the Transfer of Analytical and Bioanalytical Methods Using Monte Carlo Simulation and Estimation of Uncertainty

The purpose of this paper is to unveil two novel statistical strategies to decide on the acceptability of an analytical and bioanalytical method transfer. These new approaches, namely the uncertainty assessment approach and the risk-based approach, are based on the measurement uncertainty as a decision-making tool. At first, we illustrate step by step all the calculations required to construct the maximum tolerated interval and the limits of uncertainty in the transfer phase from a Monte Carlo simulation. Then, we exemplify an original equation to assess the expected risk or probability that a receiving laboratory measurement will fall outside the maximum tolerated interval according to the estimated trueness, fidelity, and uncertainty parameters. We elucidate the applicability and flexibility of uncertainty approach as well as risk procedure to consider the fitness for purpose of analytical and bioanalytical methods in the transfer phase. We also demonstrate here that our approaches provide guarantees that each future measurement made by the receiving laboratory will be inside the specified acceptance limits. We show that there is no difference statistically between the decisions taken throughout the analytical transfer by our methodologies and those arising from the accuracy strategies.