# Detecting Methotrexate in Pediatric Patients Using Artificial Neural Networks
###### Abstract  
Methotrexate is an antimetabolic agent with proliferative and immunosuppressive activity. It has been demonstrated to be an effective treatment for acute lymphoblastic leukemia (ALL) in children. However, there is evidence of an association between methotrexate and toxicity risks, which influences the personalization of treatment, particularly in the case of childhood ALL. This article presents the development and implementation of an algorithm based on artificial neural networks to detect methotrexate toxicity in pediatric patients with acute lymphoblastic leukemia. The algorithm utilizes historical clinical and laboratory data, with an effectiveness of 99% in the tests performed with the patient dataset. The use of neural networks in medicine is often linked to disease diagnosis systems. However, neural networks are not only capable of recognizing examples but also hold very important information. For this reason, one of the main areas of application of neural networks is the interpretation of medical data. In this article, we diagnose, with the application of neural networks in medicine, a concrete example: detecting methotrexate in its early stages in pediatric patients. methods: artificial neural networks; acute lymphoblastic leukemia (ALL); detection system +
Footnote †: journal: Applied sciences  
0000-0001-5000-5000]J. M. S.  
High-dose methotrexate (HD-MTX) plays a significant part in the therapy of acute lymphoblastic leukemia (ALL) in many treatment procedures around the world. However, there is a large variability in the pharmacokinetics and toxicity of the drug [1]. Polymorphisms in the MTX pathway genes influence the kinetics and response to high-dose MTX therapy in childhood ALL. Acute leukemias are the most common group of cancer in children, where acute lymphoblastic leukemia (ALL) represents 80% of the cases. Although the etiology is uncertain, there are predisposing factors, such as genetic, viral, and environmental factors. The clinical manifestations, on occasion, are produced by the existence of malignant cells in the bone marrow, such as in anemia, thrombocytopenia, and leukopenia [1]. The diagnosis is made by morphological, cytogenetic, and molecular analysis of the bone marrow aspirate. The treatment takes an average of two years. The expectation of cure for children with ALL has improved exponentially thanks to new drugs and in recent years to a treatment adapted to the risk of patients. Currently, the percentage of cured patients with ALL is 75% [2]. Many studies have been carried out on methotrexate and its application in the treatment of ALL: the researchers in [3] investigated the influence of the polymorphisms C677T and A1298C on the gene for methylenetetrahydrofolate reductase (MTHFR) on the toxicity induced by MTX during the treatment of children with ALL. Performing a regression analysis in patients with ALL, it was found that the ALL subtype was the strongest predictor of MTXPG accumulation, which shows that the genetic variation acquired in the ALL cells themselves had a stronger influence on the accumulation of MTXPG [4]. Children with ALL with multiple common polymorphisms in SLCO1B1 who received high doses of MTX in tests were associated with MTX clearance [5; 6; 7]. The authors of [8; 9; 10] found that variants of the SLC19A1, SLC22A8, MTR, and MTHFD1 genes were shown to be associated with the development of acute toxicity after HD-MTX treatment. The results in [11; 12; 13] show evidence for the contribution of pharmacogenetics to the toxicity of high-dose MTX and plasma MTX concentrations 48 h after treatment in patients with ALL or non-Hodgkin lymphoma. The influence of MTHFR C677T on MTX-related toxicities and plasma levels was confirmed. The authors of [14; 15] found that the TT genotype of the MTHFR gene is associated with an increase in MTX toxicity and the relapse rate. They consider the dose adjustment of MTX in the treatment protocols, depending on the genotype of the patient.