Artificial intelligence in early drug discovery enabling precision medicine

F Boniolo, E Dorigatti, AJ Ohnmacht… - Expert Opinion on …, 2021 - Taylor & Francis
Introduction: Precision medicine is the concept of treating diseases based on environmental
factors, lifestyles, and molecular profiles of patients. This approach has been found to …

Machine learning and feature selection for drug response prediction in precision oncology applications

M Ali, T Aittokallio - Biophysical reviews, 2019 - Springer
In-depth modeling of the complex interplay among multiple omics data measured from
cancer cell lines or patient tumors is providing new opportunities toward identification of …

Treatment of multiple myeloma with high-risk cytogenetics: a consensus of the International Myeloma Working Group

P Sonneveld, H Avet-Loiseau, S Lonial… - Blood, The Journal …, 2016 - ashpublications.org
Abstract The International Myeloma Working Group consensus updates the definition for
high-risk (HR) multiple myeloma based on cytogenetics Several cytogenetic abnormalities …

Variational autoencoders for cancer data integration: design principles and computational practice

N Simidjievski, C Bodnar, I Tariq, P Scherer… - Frontiers in …, 2019 - frontiersin.org
International initiatives such as the Molecular Taxonomy of Breast Cancer International
Consortium are collecting multiple data sets at different genome-scales with the aim to …

Computational models for predicting drug responses in cancer research

F Azuaje - Briefings in bioinformatics, 2017 - academic.oup.com
The computational prediction of drug responses based on the analysis of multiple types of
genome-wide molecular data is vital for accomplishing the promise of precision medicine in …

Rethinking drug repositioning and development with artificial intelligence, machine learning, and omics

M Koromina, MT Pandi, GP Patrinos - Omics: a journal of integrative …, 2019 - liebertpub.com
Pharmaceutical industry and the art and science of drug development are sorely in need of
novel transformative technologies in the current age of digital health and artificial …

Genetics of multiple myeloma: another heterogeneity level?

J Corre, N Munshi… - Blood, The Journal of the …, 2015 - ashpublications.org
Our knowledge of myeloma genetics remained limited and lagged behind many other
hematologic malignancies because of the inherent difficulties in generating metaphases …

An overview of machine learning methods for monotherapy drug response prediction

F Firoozbakht, B Yousefi… - Briefings in …, 2022 - academic.oup.com
For an increasing number of preclinical samples, both detailed molecular profiles and their
responses to various drugs are becoming available. Efforts to understand, and predict, drug …

Myeloid-derived suppressor cells: The green light for myeloma immune escape

E Malek, M de Lima, JJ Letterio, BG Kim, JH Finke… - Blood reviews, 2016 - Elsevier
Myeloid-derived suppressor cells (MDSCs) are a heterogeneous, immature myeloid cell
population with the ability to suppress innate and adaptive immune responses that promote …

[HTML][HTML] Treatment options for patients with heavily pretreated relapsed and refractory multiple myeloma

MA Dimopoulos, P Richardson, S Lonial - Clinical Lymphoma Myeloma …, 2022 - Elsevier
Despite the increasing number of treatment options available for multiple myeloma, relapse
is still inevitable and there remains a critical unmet need for treatments for patients with late …