Integrated TK-TD modeling for drug-induced concurrent tachycardia and QT changes in beagle dogs

Physiologically Based Biopharmaceutics Modeling to Demonstrate Virtual Bioequivalence and Bioequivalence Safe-space for Ribociclib which has Permeation Rate-controlled Absorption

A physiologically based biopharmaceutics model (PBBM) was developed to support formulation development of ribociclib, an orally bioavailable selective CDK4/6 inhibitor. Ribociclib is a weak base with moderate permeability and complete in vitro dissolution under stomach pH. GastroPlus™ was used to simulate the pharmacokinetics (PK) in healthy volunteers after capsule dosing. Simulations showed rapid, complete dissolution in human stomach without intestinal precipitation and with permeation-controlled absorption. Permeability was identified as controlling the systemic exposure. PBBM predicted bioequivalence (BE) between capsule and tablet in healthy volunteers, despite non-similarity between in vitro dissolution kinetics (f2<50). BE was verified in a clinical study. Then virtual bioequivalence (VBE) simulations predicted comparable PK in cancer patients between capsule and tablet of commercial batch, which was also confirmed in a clinical study. Finally, virtual trial simulations using virtual batches with slower dissolution were used to define an in vitro BE safe-space for tablets, where BE is expected. PBBM can identify drugs with permeability-controlled absorption for which formulation optimization can focus more on manufacturability rather than dissolution. PBBM can be used to predict BE study outcomes, define clinically relevant specification and BE safe-space, superseding dissolution similarity f2 criteria.

Applications of Quantitative Systems Pharmacology in Model-Informed Drug Discovery: Perspective on Impact and Opportunities

Quantitative systems pharmacology (QSP) approaches have been increasingly applied in the pharmaceutical since the landmark white paper published in 2011 by a National Institutes of Health working group brought attention to the discipline. In this perspective, we discuss QSP in the context of other modeling approaches and highlight the impact of QSP across various stages of drug development and therapeutic areas. We discuss challenges to the field as well as future opportunities.