From Real World Data to Real Impact: A Co‐Medication Framework for Lung Cancer to Advance DDI Assessment and Patient‐Centric Drug Development

Lung cancer predominantly affects older adults who already experience comorbidities and are at increased risk of drug-drug interactions (DDIs) due to polypharmacy. Traditional DDI assessments often do not fully capture complex co-medication patterns observed in real-world practice due to the risk of introducing confounding factors. This study used U.S. Optum claims data from 2019 to 2024 to characterize co-medication patterns in predominately non-small cell lung cancer (NSCLC) patients and map enzyme- and transporter-mediated liabilities across commonly used medications, chemotherapy agents, and biomarker-driven therapies. Potential DDI liabilities were further prioritized using a semi-quantitative clinical framework based on perpetrator strength, substrate sensitivity, narrow therapeutic index status, and available evidence. Frequently used medications included disease-specific supportive therapies such as ondansetron and dexamethasone, as well as treatments for common U.S. comorbidities such as cardiovascular and endocrine disorders. Many of the co-medications were substrates, inhibitors, and inducers of pathways critical for NSCLC treatments such as CYP3A, CYP2D6, P-gp, and OATP1B and additional risks were identified when giving treatments with acid-reducing agents or QT-prolonging drugs. These findings demonstrate how integrating real-world data (RWD) can strengthen DDI assessment by improving clinical trial design, informing risk-mitigation strategies, and supporting more patient-centric drug development.

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Publication Details

Journal
Clinical and Translational Science
Published
2026-09-30
DOI
https://doi.org/10.1111/cts.70734
Primary Topic
Lung Cancer Treatments and Mutations
Type
article
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article

From Real World Data to Real Impact: A Co‐Medication Framework for Lung Cancer to Advance DDI Assessment and Patient‐Centric Drug Development

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Clinical and Translational Science
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From Real World Data to Real Impact: A Co‐Medication Framework for Lung Cancer to Advance DDI Assessment and Patient‐Centric Drug Development

Fenglei Huang, Shilpa Madari, Christina Kunz, Hee Jae Choi, Mareena Biju, Ashish Sharma, Annie Carlisle
article en

Abstract

Lung cancer predominantly affects older adults who already experience comorbidities and are at increased risk of drug-drug interactions (DDIs) due to polypharmacy. Traditional DDI assessments often do not fully capture complex co-medication patterns observed in real-world practice due to the risk of introducing confounding factors. This study used U.S. Optum claims data from 2019 to 2024 to characterize co-medication patterns in predominately non-small cell lung cancer (NSCLC) patients and map enzyme- and transporter-mediated liabilities across commonly used medications, chemotherapy agents, and biomarker-driven therapies. Potential DDI liabilities were further prioritized using a semi-quantitative clinical framework based on perpetrator strength, substrate sensitivity, narrow therapeutic index status, and available evidence. Frequently used medications included disease-specific supportive therapies such as ondansetron and dexamethasone, as well as treatments for common U.S. comorbidities such as cardiovascular and endocrine disorders. Many of the co-medications were substrates, inhibitors, and inducers of pathways critical for NSCLC treatments such as CYP3A, CYP2D6, P-gp, and OATP1B and additional risks were identified when giving treatments with acid-reducing agents or QT-prolonging drugs. These findings demonstrate how integrating real-world data (RWD) can strengthen DDI assessment by improving clinical trial design, informing risk-mitigation strategies, and supporting more patient-centric drug development.

Clinical and Translational ScienceVol. 19(10)
Boehringer Ingelheim (Germany) (DE), Astellas Pharma (China) (CN), Boehringer Ingelheim (United States) (US), Astellas Pharma (United States) (US)
Partnerships for the goals
Openalex Percentile: Top 12%
Lung Cancer Treatments and Mutations
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