A first approach for an evidence-based in vitro digestion method to adjust pancreatic enzyme replacement therapy in cystic fibrosis.

Abstract

BackgroundPatients with cystic fibrosis have to take enzymatic supplements to allow for food digestion. However, an evidence-based method to adjust Pancreatic Enzyme Replacement Therapy (PERT) is inexistent, and lipid content of meals is used as a rough criterion.ObjectiveIn this study, an in vitro digestion model was set up to determine the theoretical optimal dose (TOD) of enzymatic supplement for a selection of foods, which is the dose that allows for maximum lipolysis extent.MethodsA static in vitro digestion model was applied to simulate digestion of eight foods covering a wide range of lipid contents. First, the dose of the enzymatic supplement was fixed at 2000 lipase units per gram of fat (LU/g fat) using intestinal pH and bile salt concentration as variables. Second, intestinal pH and bile salt concentrations were fixed and the variable was the dose of the enzymatic supplement. Lipolysis extent was determined by measuring the free fatty acids released from initial triglycerides content of foods after digestion. Results in terms of percentage of lipolysis extent were fitted into a linear-mixed segmented model and the deducted equations were used to predict the TOD to reach 90% of lipolysis in every food. In addition, the effect of intestinal pH and bile salt concentration were investigated.ResultsThe predictive equations obtained for the assessed foods showed that lipolysis was not only dependent on the dose of the enzyme supplement or the lipid content. Moreover, intestinal pH and bile salt concentration had significant effects on lipolysis. Therefore an evidence-based model can be developed taking into account these variables.ConclusionsDepending on food characteristics, a specific TOD should be assigned to achieve an optimal digestion extent. This work represents a first step towards an evidence-based method for PERT dosing, which will be applied in an in vivo setting to validate its efficacy.