GastroPlus Case Studies

Guide further clinical trials, or decide to discontinue human trials for a compound that is unlikely to be successful

During Phase I trials, data on compound behavior in human is gathered for the first time. These data can be used to guide further clinical trials, or to decide to discontinue human trials for a compound or formulation that is unlikely to be successful. During Phase II and later clinical trials, final formulations must be designed and shown to be effective. Scale-up to larger batch sizes, changes in processing, and other factors may affect the dissolution of formulations. Assessing the possible effects of such changes before they happen, and designing formulations that minimize such effects, can avoid serious and costly problems later.

In a recent contracted study, GastroPlus was used to determine that six new controlled-release formulations that had been manufactured for a second round of human trials would all fail to meet requirements – saving our customer considerable time and money. The program was also then used to design a controlled-release profile that would meet Cp-time requirements with the absorption and pharmacokinetic characteristics of the drug.

Step 1: Build the Absorption Model
The first step in analyzing clinical trial data is building the absorption model. Knowing where and how fast the dose is absorbed in human provides the foundation for all other analysis using GastroPlus™.
This is accomplished in the following steps:

1. Gather the data:
a. PO (and IV, if available) plasma concentration-time data
b. Basic physicochemical properties
c. Solubility-pH data
d. Pharmacokinetic parameters, if known (mean or individual subject)
e. Fraction absorbed and first pass extraction or bioavailability, if known
f. Formulation information (mean particle size & density, diffusion coefficient)
g. Dose amount (active compound only)
h. Controlled-release data, if any (in vitro % released vs. time)

2. Create GastroPlus™ database and support files:
a. Create database record for each dose for each test subject, or a single record for each dose using mean subject data for that dose
b. Create solubility-pH files for each record, if used (*.spd)
c. Create IV plasma concentration-time files for each record (*.ipd) if PKPlus will be used to generate PK parameter estimates
d. Create PO plasma concentration-time files for each record (*.opd)
e. Create chemical degradation vs pH files for each record, if needed (*.cdd)
f. Create controlled-release files, if used (*.crd)

3. Determine IV pharmacokinetic parameters, if IV data are available. This can be done quickly and easily using the PKPlus Module within GastroPlus or using an external method.

4. Optimize the absorption scale factors (assumes PK parameters available):
a. Start with minimum number of absorption scale factors and optimize
b. Add absorption scale factors and check Akaike Information Criterion and Schwartz Criterion
c. Stop when best fit is obtained to plasma concentration-time data
d. If PK parameters are not available from IV data, optimize them along with absorption scale factors, enforcing Fa and FPE constraints to compensate for covariance of PK and absorption parameters

Step 2: Run Sensitivity Analysis and Studies
With a good absorption and pharmacokinetic model, many types of analysis are possible:
1. Parameter Sensitivity Analysis
2. Virtual Trials
3. Formulation studies
4. Deconvolution of in vivo release
5. Optimization of formulations to meet plasma concentration-time targets

Parameter Sensitivity Analysis provides an indication of how predicted results change with variations in input variables – one at a time. This enables you to see which of your inputs need to be carefully determined, and which are not so sensitive, so that a good approximation is sufficient. For example, if your compound has good permeability, but low solubility, you would see that variations in permeability would have less effect than variations in solubility and formulation. The actual magnitude of these variations can enable you to determine whether additional experiments are needed to more accurately determine the actual solubility, particle size, etc... for your compound, or whether the input value is close enough to provide a reasonable estimate of Fa%, Cmax, Tmax, and AUC.

Virtual Trials provide a type of population analysis, allowing you to see the combined effects of many parameters varying at once. In the Virtual Trials mode, you select the parameters to be included in the study, and you define the expected distribution of the parameters around the baseline value by specifying a coefficient of variation in percent, and a distribution type (Gaussian, log-Normal, or uniform). The Virtual Trials feature then runs a series of N simulations (you specify N), each time generating a random sample for all selected parameters. When the N simulations are done, GastroPlus provides the mean and coefficient of variation for Fa%, F%, Cmax, Tmax, and AUC. If variations exceed comfortable limits, you can change formulation parameters to determine if they can be brought into a desirable range, or if the compound exhibits characteristics that make it unsuitable for further trials. Limited formulation studies can be conducted by modifying dose, particle size, particle density, diffusion coefficient, and controlled-release profiles to assess the effects of such changes on Fa%, F%, Cmax, Tmax, and AUC. The cumulative effects of multiple dosing can be assessed using "subsequent dose" and "dosing interval" inputs.

Deconvolution of in vivo release for controlled-release formulations can be accomplished if plasma concentration-time data are available for such formulations, once the absorption and pharmacokinetic parameters have been calibrated for the compound. These studies are accomplished by starting with in vitro dissolution-time data as the best first estimate of in vivo release. With the calibrated absorption and pharmacokinetic parameters, and using the in vitro dissolution data for in vivo release, the plasma concentration-time is predicted and compared to observed values. Any differences are assumed, at this point, to be caused by differences between the actual in vivo release and the in vitro dissolution-time profile. The Optimization module is used to adjust the controlled-release profile until the best match is obtained between predicted and observed plasma concentration-time. This release profile can then be compared to the in vitro dissolution-time data to obtain an IVIV correlation using the optional IVIVCPlus Module.

The Optimization (or IVIVCPlus) Module can also be used "going forward" – to design formulations and controlled- release profiles to meet therapeutic goals for plasma concentration-time. This is accomplished by creating an artificial plasma concentration-time data set that represents the desired plasma concentration-time profile. The Optimization module can then adjust dose, particle size, and/or controlled-release profiles to best meet the desired plasma concentration-time profile.