correct links in online version

Evaluation/report/markdown_for_github/report.md

@@ -59,9 +59,9 @@ The model was then verified by simulating:
 - multiple dose studies
 - a food effect study
 
-Details about input data (physicochemical, *in vitro* and clinical) can be found in [Section 2.2](#2.2-Data).
+Details about input data (physicochemical, *in vitro* and clinical) can be found in [Section 2.2](#22-Data).
 
-Details about the structural model and its parameters can be found in [Section 2.3](#2.3-Model-Parameters-and-Assumptions).
+Details about the structural model and its parameters can be found in [Section 2.3](#23-Model-Parameters-and-Assumptions).
 
 
 ## 2.2 Data
@@ -128,7 +128,7 @@ The metabolic pattern was determined as shown in the following table.
 
 *** The fraction excretion to feces of unchanged dapagliflozin of 18.90% (see above) was added and distributed proportionally to Dapagliflozin-3-O-glucuronide and Dapagliflozin-2-O-glucuronide under the assumption that the measured fraction of unchanged dapagliflozin resulted from originally glucuronidated metabolites that underwent biliary excretion and subsequent degradation to dapagliflozin by bacterial glucurinodases in feces.
 
-The following table shows the final mass balance data used for model building under the assumption of that unchanged dapagliflozin molecules in feces were originally glucuronides. Please refer to [Section 2.3](#2.3-Model-Parameters-and-Assumptions) for rationale.
+The following table shows the final mass balance data used for model building under the assumption of that unchanged dapagliflozin molecules in feces were originally glucuronides. Please refer to [Section 2.3](#23-Model-Parameters-and-Assumptions) for rationale.
 
 | Observer                                                     | Value      |
 | ------------------------------------------------------------ | ---------- |
@@ -155,7 +155,7 @@ The following studies were used for model verification:
 ## 2.3 Model Parameters and Assumptions
 ### 2.3.1 Absorption
 
-Studies including oral applications of dapagliflozin used for model building applied either a capsule or immediate release tablets. They all demonstrated rapid and extensive absorption. The availability of dense data during absorption, data covering a broad range of doses (from 2.5 up to 500 mg, and intravenous pharmacokinetic data ([Boulton 2013](#5-References)) allowed the identification of the *in vivo* intestinal permeability and an effective *in vivo* solubility in this PBPK model (see also [Section 2.3.4](#2.3.4-Automated-Parameter-Identification)).
+Studies including oral applications of dapagliflozin used for model building applied either a capsule or immediate release tablets. They all demonstrated rapid and extensive absorption. The availability of dense data during absorption, data covering a broad range of doses (from 2.5 up to 500 mg, and intravenous pharmacokinetic data ([Boulton 2013](#5-References)) allowed the identification of the *in vivo* intestinal permeability and an effective *in vivo* solubility in this PBPK model (see also [Section 2.3.4](#234-Automated-Parameter-Identification)).
 
 During model building, two different "data scenarios" regarding mass balance information were tested:
 
@@ -171,15 +171,15 @@ The dissolution of the tablets from Chang *et al.* ([Chang 2015](#5-References))
 
 Dapagliflozin is moderately protein bound (91 %) in plasma ([Kasichayanula 2014](#5-References)). This value was used in this PBPK model. It was assumed that the major binding partner is albumin.
 
-An important parameter influencing the resulting volume of distribution is lipophilicty. The reported experimental logP value of 2.7 ([DrugBank DB06292](#5-References)) served as a starting value. Finally, the model parameters `Lipophilicity` and `logP (veg.oil/water)` were optimized to match best clinical data (see also [Section 2.3.4](#2.3.4-Automated-Parameter-Identification)).
+An important parameter influencing the resulting volume of distribution is lipophilicty. The reported experimental logP value of 2.7 ([DrugBank DB06292](#5-References)) served as a starting value. Finally, the model parameters `Lipophilicity` and `logP (veg.oil/water)` were optimized to match best clinical data (see also [Section 2.3.4](#234-Automated-Parameter-Identification)).
 
-After testing the available organ-plasma partition coefficient and cell permeability calculation methods built in PK-Sim, observed clinical data was best described by choosing the partition coefficient calculation by `Rodgers and Rowland` and cellular permeability calculation by `PK-Sim Standard`. The specific organ permeability was also optimized to match best clinical data (see also [Section 2.3.4](#2.3.4-Automated-Parameter-Identification)).
+After testing the available organ-plasma partition coefficient and cell permeability calculation methods built in PK-Sim, observed clinical data was best described by choosing the partition coefficient calculation by `Rodgers and Rowland` and cellular permeability calculation by `PK-Sim Standard`. The specific organ permeability was also optimized to match best clinical data (see also [Section 2.3.4](#234-Automated-Parameter-Identification)).
 
 The reported blood to plasma ratio of 0.88 ([Obermeier 2009](#5-References)) was fixed in the model.
 
 ### 2.3.3 Metabolism and Elimination
 
-As previously described in [Section 2.2.2](#2.2.2-Clinical-Data),  mass balance data ([Kasichayanula 2008](#5-References), [Obermeier 2009](#5-References), [Kasichayanula 2014](#5-References)) indicated that UGT1A9 is predominatly responsible for the metabolism of dapagliflozin to dapagliflozin-3-O-glucuronide. A minor fraction is metabolized via UGT2B7 to dapagliflozin-2-O-glucuronide and via oxidative cyotochrome-P450 enzymes.
+As previously described in [Section 2.2.2](#222-Clinical-Data),  mass balance data ([Kasichayanula 2008](#5-References), [Obermeier 2009](#5-References), [Kasichayanula 2014](#5-References)) indicated that UGT1A9 is predominatly responsible for the metabolism of dapagliflozin to dapagliflozin-3-O-glucuronide. A minor fraction is metabolized via UGT2B7 to dapagliflozin-2-O-glucuronide and via oxidative cyotochrome-P450 enzymes.
 
 In summary, three metabolic first order routes were implement into the model:
 
@@ -190,7 +190,7 @@ In summary, three metabolic first order routes were implement into the model:
 
 Additionally, a renal clearance (assumed to be mainly driven by glomerular filtration) was implemented.
 
-This clearance and excretion pathways were quantified during parameter optimization to best match clinical data (see also [Section 2.2.2](#2.2.2-Clinical-Data), [Section 2.3.1](#2.3.1-Absorption), and [Section 2.3.4](#2.3.4-Automated-Parameter-Identification)).
+This clearance and excretion pathways were quantified during parameter optimization to best match clinical data (see also [Section 2.2.2](#222-Clinical-Data), [Section 2.3.1](#231-Absorption), and [Section 2.3.4](#234-Automated-Parameter-Identification)).
 
 ### 2.3.4 Automated Parameter Identification
 
@@ -224,9 +224,9 @@ The model quantifies metabolism via UGT1A9 and UGT2B7.
 
 The next sections show:
 
-1. the final model parameters for the building blocks: [Section 3.1](#3.1-Final-Input-Parameters).
-2. the overall goodness of fit: [Section 3.2](#3.2-Diagnostics-Plots).
-3. simulated vs. observed concentration-time profiles for the clinical studies used for model building and for model verification: [Section 3.3](#3.3-Concentration-Time-Profiles).
+1. the final model parameters for the building blocks: [Section 3.1](#31-Final-Input-Parameters).
+2. the overall goodness of fit: [Section 3.2](#32-Diagnostics-Plots).
+3. simulated vs. observed concentration-time profiles for the clinical studies used for model building and for model verification: [Section 3.3](#33-Concentration-Time-Profiles).
 
 
 ## 3.1 Final input parameters
@@ -317,7 +317,7 @@ Dissolution shape                | 0.6    |              |
 Use as suspension                | Yes    |              |
 
 ## 3.2 Diagnostics Plots
-Below you find the goodness-of-fit visual diagnostic plots for the PBPK model performance of all data used presented in [Section 2.2.2](#2.2.2-Clinical-Data).
+Below you find the goodness-of-fit visual diagnostic plots for the PBPK model performance of all data used presented in [Section 2.2.2](#222-Clinical-Data).
 
 The first plot shows simulated versus observed plasma concentrations, the second weighted residuals versus time. 
 
@@ -329,7 +329,7 @@ The first plot shows simulated versus observed plasma concentrations, the second
 GMFE = 1.222396 
 
 ## 3.3 Concentration-Time Profiles
-Simulated versus observed concentration-time profiles of all data listed in [Section 2.2.2](#2.2.2-Clinical-Data) are presented below.
+Simulated versus observed concentration-time profiles of all data listed in [Section 2.2.2](#222-Clinical-Data) are presented below.
 
 
 ### 3.3.1 Model Building