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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.

case study sarcoidosis v2
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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.

Monte-Carlo simulations were conducted for dosage regimens of 2 and 4 mg/kg over a 16-week period, taking into account factors such as body weight and the presence of ADA. Prediction of pulmonary interstitial fluid XTMAB-16 concentrations were informed by published biodistribution coefficients. Simulations enabled visualization of the XTMAB-16 concentrations at or above the threshold of efficacy estimated from the non-clinical model of sarcoidosis. Optimal dosage levels of 2 and 4 mg/kg administered at specific intervals were determined as a result of the simulations and informed the ongoing clinical development of XTMAB-16 in the treatment of patients with sarcoidosis.

Figure 1. Model-predicted lung XTMAB-16 concentration in virtual subjects.
Source: Offman et al. 2023

Furthermore, Certara’s medical communications and publications writing team collaborated with Xentria to transform the study’s findings into a well-crafted manuscript that was published in The Frontiers in Pharmacology. Certara’s expertise in publication planning and scientific writing ensured the manuscript’s accuracy, integrity, and adherence to rigorous standards, streamlining the publication process.




Certara played a pivotal role in helping the Xentria team determine optimal dosing strategies for XTMAB-16. These insights provided invaluable guidance for Xentria’s clinical development efforts for this product in a rare indication.

Certara’s comprehensive support, from dose optimization through advanced modeling to expert medical writing assistance, empowers pharmaceutical companies like Xentria to advance their research, make informed drug development decisions, and share their research findings with the scientific community.

Figure 2. Certara scientific and medical communications and publications team.
Certara Casestudy Using MBMA to run virtual head to head trials 3


  1. Xentria. Available from:
  2. Certara. Phoenix® NLME. Available from:
  3. Certara. Phoenix NLME: Population Pharmacokinetic Modeling and Simulation Software. Available from:
  4. Certara. Top 10 Reasons Why Phoenix NLME Is Your Go-To PK/PD Modeling & Simulation Software. Available from:
  5. Certara. Scientific and Medical Communications and Publications. Available from:
  6. Certara. Scientific and Medical Communications Brochure. Available from:
  7. Offman E, Singh N, Julian MW, et al. Leveraging in vitro and pharmacokinetic models to support bench to bedside investigation of XTMAB-16 as a novel pulmonary sarcoidosis treatment. Front Pharmacol. 2023;14:1066454. Published 2023 Mar 20. doi:10.3389/fphar.2023.1066454

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