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Principal scientist – Clinical Pharmacometrics

Clémence Pouzin

Oncology, Immunology, Cardio-vascular

“Collaborate with scientific experts to keep improving patients’ quality of life by innovating and bringing the best medicines to patients.”

Your role at Institut Roche and brief presentation of your professional background:

I joined Institut Roche in 2024 as a clinical pharmacometrician. My role is to support drug development for pRED (Roche Pharma Research and Early Development), by building mathematical models that describe the time course in the body of drugs and key biomarkers. These models help finding the right dose for the right patients. We describe the pharmacokinetics of a drug in a large population, and link it to safety or efficacy endpoints. With these models, we try to accelerate drug development by predicting as early as possible drug efficacy and safety in the targeted population.

My Focus at Institut Roche:

For immuno-oncology and cardio-vascular projects: develop non-linear fixed effect models to support drug development (population PK models with covariate selection, tumor growth inhibition models, PK-safety and PK-efficacy relationship) in collaboration with the project team members.

  1. Baranda JC, et al. “Safety, pharmacokinetics, pharmacodynamics, and antitumor activity of SAR439459, a TGFβ inhibitor, as monotherapy and in combination with cemiplimab in patients with advanced solid tumors: Findings from a phase 1/1b study.” Clin Transl Sci. 2024 Jun;17(6):e13854.
  2. Pouzin C, et al. “Prediction of CYP Down Regulation after Tusamitamab Ravtansine Administration (a DM4-Conjugate), Based on an In Vitro-In Vivo Extrapolation Approach.” Clin Pharmacol Ther. 2024 Feb;115(2):278-287.
  3. Mavroudis PD, et al. “A multi-model approach to predict efficacious clinical dose for an anti-TGF-β antibody (GC2008) in the treatment of osteogenesis imperfecta.” CPT Pharmacometrics Syst Pharmacol. 2022 Nov;11(11):1485-1496.
  4. Pouzin C, et al. "Integrated multiple analytes and semi-mechanistic population pharmacokinetic model of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate.” J Pharmacokinet Pharmacodyn. 2022 Jun;49(3):381-394.
  5. Pouzin C, et al. “Covariate analysis of tusamitamab ravtansine, a DM4 anti-CEACAM5 antibody-drug conjugate, based on first-in-human study.” CPT Pharmacometrics Syst Pharmacol. 2022 Mar;11(3):384-394.
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