MODEL INFORMATION

Method

Equations
\begin{align*} {FG}_{AUCR} &= \left( \frac{{CL_{Hint} \cdot (Q_h + CL_{RB}) + Q_h \cdot CL_{RB}}}{{AUCR \cdot \left( (inh_H \cdot fm \cdot CL_{Hint} + (1 - fm) \cdot CL_{Hint}) \cdot (Q_h + CL_{RB}) + Q_h \cdot CL_{RB} \right) \cdot (1 - inh_G)}} \right) - \left( \frac{{inh_G}}{{1 - inh_G}} \right) \\\\ {FG}_{CmaxR} &= \left( \frac{{CL_{Hint} + Q_h}}{{(Q_h + inh_H \cdot fm \cdot CL_{Hint} + (1 - fm) \cdot CL_{Hint}) \cdot (1 - inh_G)}} \right) \cdot \left( \frac{1}{{CMAXR}} \right) \cdot \left( \frac{{\exp(-k_{ei} \cdot t_{maxi})}}{{\exp(-k_e \cdot t_{max})}} \right) - \left( \frac{{inh_G}}{{1 - inh_G}} \right) \\\\ CL_b &= \frac{CL_p}{R_b} \\\\ CL_{Hint} &= \frac{CL_b}{fub \cdot \left(1 - \frac{CL_b}{Q_h}\right)} \\\\ CL_{RB} &= \frac{CLR}{BP} \\\\ \text{f}_m &: \text{fraction metabolised} \\\\ \text{F}_G &: \text{fraction escape gastro-intestinal metabolism} \\\\ \text{fu}_{b} &: \text{Fraction unbound in blood} \\\\ \text{BP} &:\text{blood to plasma ratio} \\\\ \text{CL}_{p} &: \text{plasma clearance} \\\\ \text{CL}_{R} &: renal clearance \\\\ \text{Q}_h &: \text{hepatic blood flow, used: 97 L/h (Yang and Jamei (2007)) } \\\\ \text{inh}_H &: \text{% of hepatic CYPs inhibition} \\\\ \text{inh}_G &: \text{% of gastro-intestinal CYPs inhibition} \\\\ \text{k}_e &: \text{elimination rate constant} \\\\ \text{k}_{ei} &: \text{elimination rate constant in the inhibited condition} \\\\ \text{t}_{max} &: \text{time at Cmax} (h) \\\\ \text{t}_{maxi} &: \text{time at Cmax in inhibited condition} (h)\\\\ \text{AUCR} &: \text{AUC inhibition/AUC no inhibition} \\\\ \text{CMAXR} &: \text{CMAX inhibition/CMAX no inhibition} \\\\ \end{align*}

Instructions

Pharmacokinetic and DDI Study Parameters

Pharmacokinetic and DDI Study Parameters

Pharmacokinetic (PK) Values

The typical PK values of the drug include:

  • IV plasma clearance
  • Blood to plasma ratio
  • Distribution volume

The model also considers extra hepatic clearance, which is assumed to be 0 by default (no extra hepatic clearance). The renal clearance and the inhibition percentage of the gut metabolism can be adjusted.

Drug-Drug Interaction (DDI) Study Parameters

Typical values for a DDI study include:

  • AUC ratio (with and without inhibition)
  • CMAX ratio (with and without inhibition)
  • Time to maximum concentration (Tmax) for oral administration (PO)
  • Body weight of the subjects

These parameters can be adjusted to reflect different study conditions.

Pharmacokinetic and DDI Study Parameters

Body Weight (BW) of Subjects, Height, and Age

The confidence interval is calculated based on the typical population used in the study, which includes both males and females. The user can adjust the sex ratio, and along with changes in height and age, this can affect the hepatic blood flow (calculation of Qh for each subject).

Typical body weights are as follows:

  • Typical BW of male: 81 Kg
  • Typical BW of female: 69 Kg
  • Typical BW log SD of male: 0.0365
  • Typical BW log SD of female: 0.0365

Calculation of Qh for Each Subject

The following equations were used to calculate the Q of each subject. The selection of subjects based on input parameters is done using the Latin Hypercube Sampling (LHS) method. LHS is a statistical technique that ensures efficient and comprehensive exploration of parameters by sampling the more representative sample with fewer iterations compared to random sampling.

  • BSA = 0.007184 * WT0.425 * Height0.725
  • CO = BSA * (194.15 + 4046.7 * (exp(-0.2117 * Age) - exp(-0.224 * Age)))
  • Qh = CO * (Sex_ratio * 0.28 + (1 - Sex_ratio) * 0.255)

CO (Cardiac Output): This is the volume of blood the heart pumps per minute, typically measured in liters per minute (L/min). BSA (Body Surface Area) in m2 Age: This is the age of the individual in years. Constants (194.15 and 4046.7): These are empirically derived constants that scale the contributions of the exponential terms to the cardiac output.

Additional parameters for the calculation

More advanced parameters can be modify in order to further customize the prediction. If the "Show segments variabilty" is ticked the interesection of the curves which provides the lower, the upper, and the typical value of the fm and the FG is displayed in the plot Additional paraemters can be changed such as the Height, the Age which are used as covariate in the model and the Sex ratio (female/male) The number of samplings is the number of repetions that are used to predict the parameters. In order to have less varaiblity due to the randomness is suggested to increase this parameters (100 is the dafualt value) even though it involves longer calcualtion time. The number of points are the number of steps beetween 0 and 1 which are used to define the FG(CMAX) and the fm(AUC)

Authors

Yumi Cleary1,2, Nicolo Milani1, Kayode Ogungbenro2, Leon Aarons2, Aleksandra Galetin2, Michael Gertz1

Affiliation

1Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, Switzerland

2Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, University of Manchester, Manchester, UK