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Key <t>PBPK</t> modelling steps and components of each clinical study used in model development, refinement, verification and application. BCRP, breast cancer resistance protein; DDI, drug–drug interaction; fu inc , fraction of unbound dersimelagon in in vitro system; K m , Michaelis constant; MAD, multiple ascending dose; OATP, organic anion transporting polypeptide; PBPK, physiologically based pharmacokinetic; PK, pharmacokinetic; QD, once daily; V max , maximum velocity of reaction; V ss , volume of distribution at steady state.
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Key PBPK modelling steps and components of each clinical study used in model development, refinement, verification and application. BCRP, breast cancer resistance protein; DDI, drug–drug interaction; fu inc , fraction of unbound dersimelagon in in vitro system; K m , Michaelis constant; MAD, multiple ascending dose; OATP, organic anion transporting polypeptide; PBPK, physiologically based pharmacokinetic; PK, pharmacokinetic; QD, once daily; V max , maximum velocity of reaction; V ss , volume of distribution at steady state.

Journal: British Journal of Clinical Pharmacology

Article Title: Physiologically based pharmacokinetic modelling to predict potential drug–drug interactions of dersimelagon (MT‐7117)

doi: 10.1111/bcp.16271

Figure Lengend Snippet: Key PBPK modelling steps and components of each clinical study used in model development, refinement, verification and application. BCRP, breast cancer resistance protein; DDI, drug–drug interaction; fu inc , fraction of unbound dersimelagon in in vitro system; K m , Michaelis constant; MAD, multiple ascending dose; OATP, organic anion transporting polypeptide; PBPK, physiologically based pharmacokinetic; PK, pharmacokinetic; QD, once daily; V max , maximum velocity of reaction; V ss , volume of distribution at steady state.

Article Snippet: All simulations were conducted using the Simcyp PBPK Simulator v21 (Certara), which integrates demographic, physiological, genomic and in vitro biochemical data to allow prediction of PK in virtual healthy populations.

Techniques: In Vitro

Input parameters of the physiologically based pharmacokinetic model for dersimelagon.

Journal: British Journal of Clinical Pharmacology

Article Title: Physiologically based pharmacokinetic modelling to predict potential drug–drug interactions of dersimelagon (MT‐7117)

doi: 10.1111/bcp.16271

Figure Lengend Snippet: Input parameters of the physiologically based pharmacokinetic model for dersimelagon.

Article Snippet: All simulations were conducted using the Simcyp PBPK Simulator v21 (Certara), which integrates demographic, physiological, genomic and in vitro biochemical data to allow prediction of PK in virtual healthy populations.

Techniques: Binding Assay, Software, Permeability, In Vitro, Inhibition