Genetic algorithm for making pharmacotherapy decision in the patients with multimorbidity: approaches for clinicians

Abstract

Purpose of our investigation was to propose and verify the algorithm for making pharmacotherapy decision in the patients with multimorbidity. Material and methods: Object of investigation: patients with multimorbidity. Observations were conducted according to European Guidelines. We proposed and tested genetic algorithm for making pharmacotherapy decision for such patients. It is necessary to mention, that each person is representing a variant of treating with certain pathology. Chromosome of this variant is composed from genes, where each gene is certain group of drugs. The sequence of solutions of this problem comes down to the selection of drugs for the di-morbid conditions as the descendants of mono-morbidity. At the next stage of selection continues the most successful combinations of drugs for multimorbid conditions as descendants di-morbid and monomorbid conditions. When breeding pairs must take into account the mutual potentiating pathogenic and / or sanogenetic effects. Results: We had optimal patient’s treatment as a result of crossing genes, groups of drugs and obtaining their offspring with the best combination without absolute contraindications and minimal relative contraindications. Conclusion: Thus, genetic algorithm for making pharmacotherapy decision in the patients with multimorbidity showed effectiveness of drugs choosing.