Epilepsy is a chronic neurological disease with a relatively high incidence in the pediatric population. Anti-seizure medication (ASM) may cause adverse drug reactions (ADRs), which may occur repeatedly. Objective: This study aimed to analyze the recurrence of ADRs caused by ASMs over a period of 122 months in hospitalized Mexican pediatric epilepsy patients. The patients were under monotherapy or polytherapy treatment, with valproic acid (VPA), phenytoin (PHT), and levetiracetam (LEV), among others. A total of 313 patients met the inclusion criteria: 211 experienced ADRs, whereas 102 did not. Patient sex, age, seizure type, nutritional status and related drugs were considered explanatory variables. Methods: Four statistical models were used to analyze recurrent events that were defined as “one or more ADRs occurred on a single day”, considering both the classification of ADR seriousness and the ASM causing the ADR. Results: A total of 499 recurrence events were identified. The recurrence risk was significantly greater among younger patients for both nonsevere and severe ADRs and among those with focal seizures for nonsevere ADRs. Interestingly, malnutrition was negatively associated with the risk of nonsevere ADRs, and obesity was positively associated with the risk of severe ADRs. Finally, LEV was associated with a significantly greater risk of causing nonsevere ADRs than VPA. However, LEV significantly reduced the risk of severe ADRs compared with VPA, and PHT increased the risk in comparison with VPA. In conclusion, this study offers a robust clinical tool to predict risk factors for the presence and recurrence of ASM-ADRs in pediatric patients with epilepsy.

Epilepsy is a chronic neurological disease characterized by the presence of spontaneous seizures, with a higher incidence in the pediatric population. Anti-seizure medication (ASM) may produce adverse drug reactions (ADRs) with an elevated frequency and a high severity. Thus, the objective of the present study was to analyze, through intensive pharmacovigilance over 112 months, the ADRs produced by valproic acid (VPA), oxcarbazepine (OXC), phenytoin (PHT), and levetiracetam (LEV), among others, administered to monotherapy or polytherapy for Mexican hospitalized pediatric epilepsy patients. A total of 1034 patients were interviewed; 315 met the inclusion criteria, 211 patients presented ADRs, and 104 did not. A total of 548 ASM-ADRs were identified, and VPA, LEV, and PHT were the main culprit drugs. The most frequent ADRs were drowsiness, irritability, and thrombocytopenia, and the main systems affected were hematologic, nervous, and dermatologic. LEV and OXC caused more nonsevere ADRs, and PHT caused more severe ADRs. The risk analysis showed an association between belonging to the younger groups and polytherapy with ADR presence and between polytherapy and malnutrition with severe ADRs. In addition, most of the severe ADRs were preventable, and most of the nonsevere ADRs were nonpreventable.

Tuberculosis (TB) pathogenesis is driven by the rapid proliferation of Mycobacterium tuberculosis bacilli, which breach host defenses to invade pulmonary tissue and precipitate active disease. While both natural and synthetic compounds have contributed to successful Mycobacterium tuberculosis (Mtb) therapies, researchers should now prioritize harnessing the synergistic effects of complementary treatments to maximize efficacy. Deploying natural and synthetic small molecules offers a powerful strategy to circumvent drug resistance, enhance Mycobacterium tuberculosis (MTB) therapeutic efficacy, and minimize the toxicities associated with conventional regimens and emerging PROTAC modalities. Consequently, clarifying how these natural and synthetic agents target resistant strains and alter associated genetic biomarkers is essential. This paper reviews recent advancements in natural and synthetic drugs, highlighting their structure-activity relationships to enhance anti-tuberculosis (TB) therapies. Additionally, we present a novel computational framework utilizing target prediction and probability scoring to identify high-potential synthetic compounds for future first-line TB regimens.