Santiago-de-la-Cruz Jose Alberto, Rivero-Segura Nadia Alejandra, Gomez-Verjan Juan Carlos
Dirección de Investigación, Instituto Nacional de Geriatría, Mexico City, 10200, México.
J Cheminform. 2025 Jul 15;17(1):106. doi: 10.1186/s13321-025-01058-5.
Age-related diseases and syndromes result in poor quality of life and adverse outcomes, representing a challenge to healthcare systems worldwide. Several pharmacological interventions have been proposed to target the aging process to slow its adverse effects. The so-called geroprotectors have been proposed as novel molecules that could maintain the organism's homeostasis, targeting specific aspects linked to the hallmarks of aging and delaying the adverse outcomes associated with age. On the other hand, machine learning (ML) is revolutionising drug design by making the process faster, cheaper, and more efficient.
与年龄相关的疾病和综合征会导致生活质量下降和不良后果，这对全球医疗保健系统构成了挑战。已经提出了几种药物干预措施来针对衰老过程，以减缓其不良影响。所谓的老年保护剂已被提议作为新型分子，它们可以维持机体的稳态，针对与衰老特征相关的特定方面，并延缓与年龄相关的不良后果。另一方面，机器学习正在彻底改变药物设计，使这个过程更快、更便宜且更高效。
