In this paper, an evolutionary algorithm for solving the problem of predicting the safety of opioid therapy for patients with pancreatic cancer is proposed. Opioid analgesics such as fentanyl and morphine are used as a therapy for pain syndromes. Using the patient database, based on the results of the therapy applied to them, it is determined whether there is a correlation between the outcome and the combination of input data taken into account. To find a set of informative features, it is proposed to use the genetic algorithm for multi-criterion optimization, in which two criteria are reduced to one generalized criterion using the method of “additive convolution”. The formed combination of the selected input features, which affects the outcome, is used to build a decision support model and to evaluate it afterwards.

This review presents the results of recent studies on the role of pathogenic mechanisms of chronic pain syndrome in patients with pancreatic cancer. The authors searched Russian and international databases, including MedLine, PubMed, NEL elibrary.ru, Wiley Online Library, Web of Science, Oxford University Press, SAGE Premier, for the period from 1996 to 2016 (10 years). Our results demonstrate the preconditions for multimodal analgesic therapy in anesthesia and pain treatment. We show the key role of selecting basic pharmacological groups of drugs for the patients with pancreatic cancer with chronic pain syndrome. The dependence of patient survival on the intensity, diversity and complexity of pancreatic pain in pancreatic cancer means that individual therapy is extremely important as inadequate pain relief can have profound negative effects on the psychosocial and physical well-being of pancreatic cancer patients and their relatives.