The selection of a project among a set of possible alternatives is a difficult task decision makers have to face. Difficulties in selecting a project arise because of the different goals involved and because of the large number of attributes to consider. Our approach is based upon a fuzzy extension of the Analytic Hierarchy Process (AHP). This paper focuses on the constraints that have to be considered within fuzzy AHP in order to take in account all the available information. This study demonstrates that by considering all the information deriving from the constraints better results in terms of certainty and reliability can be achieved

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell-based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator-introduced variations, and affected by heterogeneity of the processed organs/tissues and lot-dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell-based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo-quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.

Background. Induction with monoclonal antibodies for prevention of acute cellular rejection (ACR) may avoid many of the adverse events associated with polyclonal antibodies. Basiliximab, a chimeric monoclonal antibody directed against the ␣-chain of the interleukin 2 receptor (CD25), has been extensively evaluated as an induction therapy for kidney transplant recipients, more frequently in combination with a cyclosporine-based regimen. In this study, we assessed the efficacy and safety of basiliximab in combination with a tacrolimus-based regimen after liver transplantation. Methods. Fifty consecutive liver transplants (47 cadaveric donors; 3 living donors) were analyzed. All patients received two 20-mg doses of basiliximab (days 0 and 4 after transplantation) followed by tacrolimus (0.15 mg/kg/day; 10 -15 ng/mL target trough levels) and a tapered dose regimen of steroids. Follow-up ranged from 404 to 1,364 days after transplantation (mean 799.89 days, SDϮ257.37; median 796 days). Results. A total of 88% of patients remained rejection-free during follow-up with an actuarial rejection-free probability of 75% within 3 months. The actuarial patient survival rate at 3 years was 88%, and the graft survival rate was 75%. Twelve (24%) patients experienced one episode of sepsis, requiring temporary reduction of immunosuppressive therapy. There were no immediate side effects associated with basiliximab and no evidence of cytomegalovirus infection or posttransplant lymphoproliferative disorder. Conclusions. Basiliximab in combination with a tacrolimus-based immunosuppressive regimen is effective in reducing episodes of ACR and increasing ACR-free survival after liver transplantation. In addition, basiliximab does not increase the incidence of adverse effects or infections.

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