Dataset Information

Decoding kinase-adverse event associations for small molecule kinase inhibitors.

ABSTRACT: Small molecule kinase inhibitors (SMKIs) are being approved at a fast pace under expedited programs for anticancer treatment. In this study, we construct a multi-domain dataset from a total of 4638 patients in the registrational trials of 16 FDA-approved SMKIs and employ a machine-learning model to examine the relationships between kinase targets and adverse events (AEs). Internal and external (datasets from two independent SMKIs) validations have been conducted to verify the usefulness of the established model. We systematically evaluate the potential associations between 442 kinases with 2145 AEs and made publicly accessible an interactive web application "Identification of Kinase-Specific Signal" ( https://gongj.shinyapps.io/ml4ki ). The developed model (1) provides a platform for experimentalists to identify and verify undiscovered KI-AE pairs, (2) serves as a precision-medicine tool to mitigate individual patient safety risks by forecasting clinical safety signals and (3) can function as a modern drug development tool to screen and compare SMKI target therapies from the safety perspective.

SUBMITTER: Gong X

PROVIDER: S-EPMC9329312 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Decoding kinase-adverse event associations for small molecule kinase inhibitors.

Gong Xiajing X Hu Meng M Liu Jinzhong J Kim Geoffrey G Xu James J McKee Amy A Palmby Todd T de Claro R Angelo RA Zhao Liang L

Nature communications 20220727 1

Small molecule kinase inhibitors (SMKIs) are being approved at a fast pace under expedited programs for anticancer treatment. In this study, we construct a multi-domain dataset from a total of 4638 patients in the registrational trials of 16 FDA-approved SMKIs and employ a machine-learning model to examine the relationships between kinase targets and adverse events (AEs). Internal and external (datasets from two independent SMKIs) validations have been conducted to verify the usefulness of the e ...[more]

PMID: 35896580

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Project description:BackgroundThe development of anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) has improved the survival outcomes of patients with advanced ALK-rearranged non-small-cell lung cancer (NSCLC). The adverse events (AEs) related to ALK inhibitors are fairly well known; notably, about 20% of patients receiving lorlatinib experienced cognitive effects and behavioral alterations in pivotal trials. Therefore, psychiatric disorders could represent AEs of special interest for all ALK TKIs, deserving careful assessment in the post-marketing setting.ObjectiveWe conducted a real-world pharmacovigilance study on psychiatric AEs with marketed ALK inhibitors in subjects with advanced NSCLC.Patients and methodsWe performed an observational, retrospective analysis of spontaneous reports submitted to the Food and Drug Administration Adverse Events Reporting System (FAERS, as of December 2020), selecting psychiatric AEs to ALK TKIs approved in NSCLC (crizotinib, ceritinib, alectinib, brigatinib, lorlatinib). These AEs were independently scrutinized by three oncologists applying predefined exclusion criteria, described in terms of clinical/demographic features and assessed for drug-related causality according to an adaptation of the WHO-UMC system, a standardized probabilistic algorithm.ResultsAmong 584 reported psychiatric AEs, 95 cases were selected as potentially treatment related, with higher reporting frequency for lorlatinib (26, 2.8%), followed by brigatinib (10, 1.2%), alectinib (18, 0.7%), ceritinib (12, 0.6%), and crizotinib (29, 0.3%). Reported psychiatric symptoms were mood disorders (39), psychotic disorders (24), and anxiety, agitation, and irritability (25). In the majority (74%) of cases, psychiatric AEs were serious and required hospitalization in about 32% of patients; 15.8% of retained cases were considered as highly probable and 69.5% as probable. Drug discontinuation was recorded in 31.6% of the reported cases, with the highest proportion for lorlatinib (65.4%).ConclusionNotwithstanding limitations, our study found a higher proportion of psychiatric AEs with lorlatinib, but also raised the hypothesis of psychiatric reactions as a class effect of ALK TKIs.

Dataset Information

Decoding kinase-adverse event associations for small molecule kinase inhibitors.

Publications

Decoding kinase-adverse event associations for small molecule kinase inhibitors.

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