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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.