Predicting Efficacy of Cancer Drug Combinations Using Machine Learning

Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 425 - 431

Опубликована: Янв. 1, 2025

Язык: Английский

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Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data

Expert Opinion on Drug Discovery, Год журнала: 2024, Номер 19(7), С. 841 - 853

Опубликована: Июнь 11, 2024

Introduction Prostate cancer (PC) is the most common malignancy and accounts for a significant proportion of deaths among men. Although initial therapy success can often be observed in patients diagnosed with localized PC, many eventually develop disease recurrence metastasis. Without effective treatments, aggressive PC display very poor survival. To curb current high mortality rate, investigations have been carried out to identify efficacious therapeutics. Compared de novo drug designs, computational methods widely employed offer actionable predictions fast cost-efficient way. Particularly, powered by an increasing availability next-generation sequencing molecular profiles from patients, computer-aided approaches tailored screen candidate drugs.

Язык: Английский

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Computational Advancements in Cancer Combination Therapy Prediction

JCO Precision Oncology, Год журнала: 2023, Номер 7

Опубликована: Сен. 1, 2023

Given the high attrition rate of de novo drug discovery and limited efficacy single-agent therapies in cancer treatment, combination therapy prediction through silico repurposing has risen as a time- cost-effective alternative for identifying novel potentially efficacious cancer. The purpose this review is to provide an introduction computational methods summarize recent studies that implement each these methods. A systematic search PubMed database was performed, focusing on published within past 10 years. Our included reviews articles ongoing retrospective studies. We prioritized with findings suggest considerations improving over providing meta-analysis all currently available Computational used research include networks, regression-based machine learning, classifier learning models, deep approaches. Each method class its own advantages disadvantages, so careful consideration needed determine most suitable when designing method. Future directions improve current technology incorporation disease pathobiology, characteristics, patient multiomics data, drug-drug interactions maximally tolerable regimens As their capability integrate patient, drug, more comprehensive models can be developed accurately predict safe other complex diseases.

Язык: Английский

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Construction of a Waddington-like landscape model that can guide clinical exploration of p53-dynamics-activating parameters in the face of divergent p53 dynamics

Communications in Nonlinear Science and Numerical Simulation, Год журнала: 2024, Номер 132, С. 107893 - 107893

Опубликована: Фев. 10, 2024

Язык: Английский

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Exploring potential therapeutic combinations for castration-sensitive prostate cancer using supercomputers: a proof of concept study

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Авг. 13, 2024

To address the challenge of finding new combination therapies against castration-sensitive prostate cancer, we introduce Vini, a computational tool that predicts efficacy drug combinations at intracellular level by integrating data from KEGG, DrugBank, Pubchem, Protein Data Bank, Uniprot, NCI-60 and COSMIC databases. Vini is drugs their level. It addresses problem comprehensively considering all known target genes, proteins small molecules mutual interactions involved in onset development cancer. The results obtained point to new, previously unexplored could theoretically be promising candidates for treatment cancer prevent inevitable progression incurable castration-resistant stage. Furthermore, after analyzing triple targets, most common targets became clear: ALK, BCL-2, mTOR, DNA androgen axis. These may help define future use computer model explore therapeutic represents an innovative approach search effective treatments which, if clinically validated, potentially lead breakthrough therapies.

Язык: Английский

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