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Prediction of fetal exposure from ex-vivo human placental perfusion study by pharmacometrics

Pharmacometrics was born with the goal of improving the efficiency of new drug development by integrating and quantitatively considering all available information in a rational manner. It includes PK/PD, PB-PK, and PPK technologies, but it also applies QSP and models without drug concentration and the latest machine learning concepts. The integration with drug development strategies, such as MIDD and MID3, is often discussed. In addition to the drug development field, pharmacometrics is also being applied to optimize patient outcomes by organizing information in the medical field where a lot of information is complicated. In addition to the MBMA, which collects a wide range of information from the literature, the diversity of the information used is also expanding, including the use of individual clinical trial information disclosure systems and real-world clinical data. In this symposium, we will introduce some examples of such efforts, such as modeling of cardiac loads and relationship between drug therapy and exercise therapy in chronic heart failure, prediction of fetal drug exposure, and precise analysis of TDM information collected in clinical practice. We will discuss how these analyses can contribute to new drug development strategies and advances in patient care.

Precision medicine promoted by pharmacometrics analysis

The 142nd Annual Meeting of the Pharmaceutical Society of Japan (Nagoya)

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[S04-3]Prediction of fetal exposure from ex-vivo human placental perfusion study by pharmacometrics

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