Leveraging Pharmacokinetic Modeling & Scientific Communications Expertise Advances Sarcoidosis Drug Program

Sarcoidosis is a complex, debilitating rare condition with few effective treatment options, especially for cases that are resistant to first-line therapies. This condition affects multiple organs- including the lungs- leading to persistent inflammation and non-caseating epithelioid granulomas. Unlike other types of granulomas, the distinct characteristics of sarcoidosis granulomas further complicates developing viable treatment strategies.

Xentria is a pioneering biopharmaceutical company focused on developing biologic and innovative drug therapies. Their investigational drug, XTMAB-16, is a novel chimeric anti-tumor necrosis factor alpha (TNFα) antibody that holds promise as a potential breakthrough treatment for pulmonary sarcoidosis.

The Xentria team, having already established a safe dose regimen in a first-in-human study of XTMAB-16, needed to identify dosing regimens to enable ongoing clinical development of XTMAB-16 in patients with pulmonary sarcoidosis. To do this, Xentria collaborated with Certara and Dr. Elliott Crouser from Ohio State University Wexner Medical Center to identify clinical regimen(s) predicted to achieve pulmonary interstitial concentration of XTMAB-16 sufficient to inhibit granuloma formation based on an ex-vivo model that used cells derived from patients with pulmonary sarcoidosis. Finally, the Xentria team wanted their drug development research on XTMAB-16 to be published in peer-reviewed biomedical journals but lacked in-house scientific and medical communications expertise.

Certara scientists collaborated with the Xentria team to develop population pharmacokinetic (PPK) modeling to analyze data from the first-in-human study of XTMAB-16. Certara’s Phoenix® NLME population modeling and simulation software was utilized to perform this PPK analysis. A two-compartment PPK model was developed, and covariate analysis was conducted to determine the factors that influence the drug’s pharmacokinetics, including the presence of anti-drug antibodies (ADA). Standard diagnostics and a prediction-corrected visual predictive check (pcVPC) were employed to assess the model’s performance and validate its reliability in predicting XTMAB-16 exposure in patients’ lungs.