Computational Modeling and Treatment Identification in the Myelodysplastic Syndromes

Curr Hematol Malig Rep. 2017 Oct;12(5):478-483. doi: 10.1007/s11899-017-0412-z.

Abstract

Purpose of review: This review discusses the need for computational modeling in myelodysplastic syndromes (MDS) and early test results.

Recent findings: As our evolving understanding of MDS reveals a molecularly complicated disease, the need for sophisticated computer analytics is required to keep track of the number and complex interplay among the molecular abnormalities. Computational modeling and digital drug simulations using whole exome sequencing data input have produced early results showing high accuracy in predicting treatment response to standard of care drugs. Furthermore, the computational MDS models serve as clinically relevant MDS cell lines for pre-clinical assays of investigational agents. MDS is an ideal disease for computational modeling and digital drug simulations. Current research is focused on establishing the prediction value of computational modeling. Future research will test the clinical advantage of computer-informed therapy in MDS.

Keywords: Biomarkers; Computational biology; In silico; Myelodysplastic syndromes.

Publication types

  • Review

MeSH terms

  • Computer Simulation*
  • Humans
  • Models, Biological*
  • Myelodysplastic Syndromes / drug therapy*
  • Myelodysplastic Syndromes / metabolism
  • Myelodysplastic Syndromes / pathology