The Modern Approach to Total Parenteral Nutrition: Multidirectional Therapy Perspectives with a Focus on the Physicochemical Stability of the Lipid Fraction.

Abstract

With advancements in medical technology, biochemistry, and clinical practices, the modern approach to total parenteral nutrition (TPN) has been focused on precision, safety, and the optimization of metabolic and nutritional parameters based on the patient's needs. In the last decade, TPN mixtures have been transitioning from a lifesaving intervention for patients unable to receive enteral nutrition to a highly specialized therapy aimed at improving clinical outcomes, reducing complications, and personalizing care. Total parenteral nutrition has attracted great interest, and its adaptation to the patient's needs is a topic of interest in the scientific community. However, there are problems related to shortages in the supply of the concentrates required to balance TPN mixtures and to infections linked to the venous access devices that are necessary for administering nutrition. Adjusting the TPN composition to meet specific patient needs requires specialist knowledge, as the ingredients available on the market differ in terms of excipients and this may increase the risk of physicochemical incompatibilities, particularly the destabilization of the lipid fraction. It is common clinical practice to inject drugs into the parenteral nutrition bag, and hence there is a high demand for confirmation of the compatibility of a given drug with the TPN composition. However, methods used in clinical practice still differ from the modern solutions proposed in scientific research. In order to ensure patient safety with the use of advanced therapy, continuous education and monitoring of the latest scientific research related to TPN is required. The integration of artificial intelligence (AI) into clinical nutrition represents a paradigm shift in the management of total parenteral nutrition (TPN). As TPN transitions from a standardized, one-size-fits-all approach to a highly personalized therapy, we must examine the challenges and future directions of AI-driven TPN to provide a comprehensive analysis of its impact on clinical practice.