AIMC Topic: Antineoplastic Combined Chemotherapy Protocols

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In silico analysis of atrial fibrillation and hypertension mechanism of action secondary to ibrutinib/acalabrutinib in chronic lymphocytic leukemia.

Scientific reports
Ibrutinib and acalabrutinib are first- and next-generation Bruton Tyrosine Kinase inhibitors (BTKi), respectively, approved for chronic lymphocytic leukemia (CLL). Ibrutinib has been associated with cardiovascular events, including atrial fibrillatio...

Machine learning-assisted exploration of multidrug-drug administration regimens for organoid arrays.

Science advances
Combination therapies enhance the therapeutic effect of cancer treatment; however, identifying effective interdependent doses, durations, and sequences of multidrug administration regimens is a time- and labor-intensive task. Here, we integrated mach...

Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Scientific reports
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BMC cancer
BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorectal cancer owing to its potential to improve surgical outcomes and prognosis. However, reliable biomarkers to predict the response to NAC are lacking. ...

Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: While triplet therapy (HTI), which combines hepatic arterial infusion chemotherapy (HAIC) with tyrosine kinase inhibitors and immune checkpoint inhibitors, is widely used in the treatment of large hepatocellular carcinoma (HCC), there are...

Forecasting optimal treatments in relapsed/refractory mature T- and NK-cell lymphomas: A global PETAL Consortium study.

British journal of haematology
There is no standard of care in relapsed/refractory T-cell/natural killer-cell lymphomas. Patients often cycle through cytotoxic chemotherapy (CC), epigenetic modifiers (EM) or small molecule inhibitors (SMI) empirically. Ideal therapy at each line r...

Circumventing glioblastoma resistance to temozolomide through optimal drug combinations designed by systems pharmacology and machine learning.

British journal of pharmacology
BACKGROUND AND PURPOSE: Glioblastoma (GBM), the most frequent and aggressive brain tumour in adults, is associated with a dismal prognostic despite intensive treatment involving surgery, radiotherapy and temozolomide (TMZ)-based chemotherapy. The ini...

Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials Group/AGITG CO.17/20 Trials.

JCO clinical cancer informatics
PURPOSE: Cetuximab (CET), targeting the epidermal growth factor receptor, is a systemic treatment option for patients with colorectal cancer. One known predictive factor for CET efficacy is the presence of CET-related rash; other putative toxicity fa...