SciCodePile/SciCode-Domain-Code
DATA1: Domain-Specific Code Dataset Dataset Overview DATA1 is a large-scale domain-specific code dataset focusing on code samples from interdisciplinary fields such as biology, chemistry, materials science, and related areas. The dataset is collected and organized from GitHub repositories, covering 178 different domain topics with over 1.1 billion lines of code. Dataset Statistics Total Datasets: 178 CSV files Total Data Size: ~115 GB Total Lines… See the full description on the dataset page: https://huggingface.co/datasets/SciCodePile/SciCode-Domain-Code.
42.4k
1"keyword","repo_name","file_path","file_extension","file_size","line_count","content","language"
2"PBPK model","Open-Systems-Pharmacology/OSP-PBPK-Model-Library","Fluconazole/Fluconazole_evaluation_report.md",".md","36595","577","# Building and evaluation of a PBPK model for Fluconazole in healthy adults3 4| Version | 2.0-OSP12.2 |5| ----------------------------------------------- | ------------------------------------------------------------ |6| based on *Model Snapshot* and *Evaluation Plan* | https://github.com/Open-Systems-Pharmacology/Fluconazole-Model/releases/tag/v2.0 |7| OSP Version | 12.2 |8| Qualification Framework Version | 3.5 |9 10This evaluation report and the corresponding PK-Sim project file are filed at:11 12https://github.com/Open-Systems-Pharmacology/OSP-PBPK-Model-Library/13 14# Table of Contents15 16 * [1 Introduction](#introduction)17 * [2 Methods](#methods)18 * [2.1 Modeling strategy](#modeling-strategy)19 * [2.2 Data used](#data-used)20 * [2.3 Model parameters and assumptions](#model-parameters-and-assumptions)21 * [3 Results and Discussion](#results-and-discussion)22 * [3.1 Fluconazole final input parameters](#fluconazole-final-input-parameters)23 * [3.2 Fluconazole Diagnostics Plots](#fluconazole-diagnostics-plots)24 * [3.3 Concentration-Time Profiles](#ct-profiles)25 * [3.3.1 Model Building](#model-building)26 * [3.3.2 Model Verification](#model-verification)27 * [4 Conclusion](#conclusion)28 * [5 References](#main-references)29 30# 1 Introduction<a id=""introduction""></a>31 32Fluconazole is an antifungal medication for the treatment of a number of different fungal infections. It is metabolized by UGT2B7 and renally excreted by glomerular filtration. About 70% of fluconazole is excreted unchanged in urine during 120 hours. Fluconazole is a moderate inhibitor of CYP3A4 and can therefore serve as a perpetrator for CYP3A4 in DDI studies. 33 34The herein presented PBPK model of fluconazole has been developed using published pharmacokinetic clinical data by Palkama et al. ([Palkama 1998](#5-references)), Ripa et al. ([Ripa 1993](#5-references)), Shiba et al. ([Shiba 1990](#5-references)), Ahonen et al. ([Ahonen 1997](#5-references)), Brammer et al. ([Brammer 1990](#5-references)), Brammer et al. ([Brammer 1991](#5-references)), Thorpe et al. ([Thorpe 1990](#5-references) and Varhe et al. ([Varhe 1996](#5-references)). 35The model has then been evaluated by comparing observed data to simulations of both intravenously and orally administered fluconazole covering a dose range of 25 mg to 400 mg. Both single dose and multiple dose administration are represented in the development and evaluation data sets. 36 37The presented model includes the following features:38 39- metabolism by UGT2B7,40- inhibition of CYP3A4,41- renal clearance by glomerular filtration,42- oral absorption with dissolution rate assigned to the Weibull function for low, medium and high doses.43 44# 2 Methods<a id=""methods""></a>45 46## 2.1 Modeling strategy<a id=""modeling-strategy""></a>47 48The general concept of building a PBPK model has previously been described by Kuepfer et al. ([Kuepfer 2016](#5-references)). Relevant information on anthropometric (height, weight) and physiological parameters (e.g. blood flows, organ volumes, binding protein concentrations, hematocrit, cardiac output) in adults was gathered from the literature and has been previously published ([Willmann 2007](#5-references)). The information was incorporated into PK-Sim® and was used as default values for the simulations in adults.49 50The applied activity and variability of plasma proteins and active processes that are integrated into PK-Sim® are described in the publicly available PK-Sim® Ontogeny Database Version 7.3 ([PK-Sim Ontogeny Database Version 7.3](#5-references)) or otherwise referenced for the specific process.51 52A mean model was built based on clinical data from studies with intravenous administration of fluconazole by Palkama et al. 1998 ([Palkama 1998](#5-references)), Ripa et al. 1993 ([Ripa 1993](#5-references)) and Shiba et al. 1990 ([Shiba 1990](#5-references)). The studies conducted by Palkama et al. and Ripa et al. reported plasma concentrations of fluconazole and the study by Shiba reported fraction of unchanged fluconazole excreted to urine in addition to plasma concentrations. The mean PBPK model was developed using a typical male European individual. The relative tissue-specific expressions of enzymes predominantly being involved in the metabolism of fluconazole (UGT2B7) were considered ([Meyer 2012](#5-references)).53 54A specific set of parameters (see below) was optimized to describe the distribution of fluconazole after intravenous administration using the Parameter Identification module provided in PK-Sim®. Structural model selection was mainly guided by visual inspection and total error of the resulting description of data, 95% confidence interval of the identified parameter values and biological plausibility.55 56Once the appropriate structural model was identified for the intravenous administration, the model was verified by simulating other clinical studies reporting pharmacokinetic concentration-time profiles after intravenous administration of fluconazole. 57 58Thereafter additional parameters for oral administration of non-dissolved formulations (i.e. capsules) were identified. Administered doses of fluconazole were ranging from single dose of 25 mg to multiple dosing of 400 mg, why the applied Weibull function to describe the dissolution of fluconazole were divided into low, medium and high dose. The dissolution shape were kept between the doses while the dissolution time were separated. 59 60The model was then verified by simulating further clinical studies reporting pharmacokinetic concentration-time profiles after oral administration of fluconazole.61 62Details about input data (physicochemical, *in vitro* and clinical) can be found in [Section 2.2](#22-data-used).63 64Details about the structural model and its parameters can be found in [Section 2.3](#23-model-parameters-and-assumptions).65 66## 2.2 Data used<a id=""data-used""></a>67 68### 2.2.1 In vitro and physicochemical data69 70A literature search was performed to collect available information on physicochemical properties of fluconazole. The obtained information from literature is summarized in the table below, and is used for model building.71 72| **Parameter** | **Unit** | **Value** | Source | **Description** |73| :---------------------- | -------- | --------- | ------------------------------------ | ------------------------------------------------------------ |74| MW | g/mol | 306.28 | [Debruyne 1993](#5-references) | Molecular weight |75| pK<sub>a</sub> | | 2.03 | [Charoo 2014](#5-references) | acid dissociation constant of conjugate acid; compound type: weak base |76| Solubility (pH) | mg/mL | 6.9 (7.4) | [Charoo 2014](#5-references) | Aqueous Solubility |77| logP | | 0.5 | [Christofoletti 2016](#5-references) | Partition coefficient between octanol and water |78| | | 0.5 | [Charoo 2014](#5-references) | Partition coefficient between octanol and water |79| fu | % | 89 | Pfizer | Fraction unbound in plasma |80| | % | 88 | [Christofoletti 2016](#5-references) | Fraction unbound in plasma |81| CL<sub>int</sub> UGT2B7 | 1/min | 0.005 | [Watt 2018](#5-references) | First order intrinsic clearance UGT2B7 |82| P<sub>eff</sub> | cm/s | 0.000213 | GastroPlus | Specific intestinal permeability |83| Ki CYP3A4 | µmol/L | 13.1 | [Sakaeda 2005](#5-references) | Non-competitive inhibition of CYP3A4 |84| GFR fraction | | 0.17 | [Watt 2018](#5-references) | glomerular filtration fraction |85 86### 2.2.2 Clinical data87 88A literature search was performed to collect available clinical data on fluconazole in adults. 89 90The following publications were found in adults for model building:91 92| Publication | Arm / Treatment / Information used for model building |93| :---------------------------- | :----------------------------------------------------------- |94| [Ahonen 1997](#5-references) | Plasma PK profiles in healthy subjects after single dose oral administration of 400 mg fluconazole |95| [Brammer 1990](#5-references) | Plasma PK profiles in healthy subjects after multiple oral administration of 200, 300 and 400 mg fluconazole |96| [Brammer 1991](#5-references) | Plasma PK profiles in healthy subjects after single dose oral administration of 50 mg fluconazole |97| [Shiba 1990](#5-references) | Plasma PK profiles and urine data in healthy subjects after single iv and oral administration of 25 and 50 mg fluconazole and single oral dose of 100 mg fluconazole |98| [Palkama 1998](#5-references) | Plasma PK profiles in healthy subjects after single dose iv and oral administration of 400 mg fluconazole |99| [Ripa 1993](#5-references) | Plasma PK profiles in healthy subjects after single dose iv administration of 100 mg fluconazole |100| [Thorpe 1990](#5-references) | Plasma PK profiles in healthy subjects after single dose oral administration of 100 mg fluconazole |101| [Varhe 1996](#5-references) | Plasma PK profiles in healthy subjects after multiple oral administration of 100 and 200 mg fluconazole |102 103The following table shows the data from the excretion studies ([Shiba 1990](#5-references)) used for model building:104 105| Observer | Value |106| ------------------------------------------------------------ | ----- |107| Fraction excreted to urine of unchanged fluconazole after iv administration 25 mg | 74% |108| Fraction excreted to urine of unchanged fluconazole after iv administration 25 mg | 72% |109| Fraction excreted to urine of unchanged fluconazole after oral administration 25 mg | 69% |110| Fraction excreted to urine of unchanged fluconazole after oral administration 50 mg | 67% |111| Fraction excreted to urine of unchanged fluconazole after oral administration 100 mg | 75% |112 113The following dosing scenarios were simulated and compared to respective data for model verification:114 115| Scenario | Data reference |116| ------------------------------------------------------------ | ------------------------------------ |117| iv 400 mg (60 min) | [Ahonen 1997](#5-references) |118| iv 50 mg (2 min) | [Brammer 1990](#5-references) |119| iv 25 mg (1 min) | [Shiba 1990](#5-references) |120| iv 800 mg (240 min) once daily for 14 days | [Sobue 2004](#5-references) |121| iv 100 mg (20 min) | [Yeates 1994](#5-references) |122| po 400 mg | [Palkama 1998](#5-references) |123| po 100 mg | [Shiba 1990](#5-references) |124| po 50 mg once daily for 4 days | [Varhe 1996](#5-references) |125 126## 2.3 Model parameters and assumptions<a id=""model-parameters-and-assumptions""></a>127 128### 2.3.1 Absorption129 130The parameter value for `Specific intestinal permeability` was used as in GastroPlus. Although, the permeability didn't seem to be the rate-limiting step in oral absorption as this parameter could not be identified when attempting to estimate a value using Parameter Identification. The default solubility was assumed to be the measured value in phosphate buffer (see [Section 2.2.1](#221-in-vitro-and-physicochemical-data))131 132The dissolution of capsules/tablets (not always specified in the literature which formulation for oral administration was used) were implemented via empirical Weibull dissolution. A different Weibull function was used for different dose categories, low, medium high and high dose to distinguish the dissolution time across the dose range; see results of optimization in [Section 2.3.4](#234-automated-parameter-identification).133 134### 2.3.2 Distribution135 136Fluconazole has a low protein bound (approx. 11 %) fraction in plasma (see [Section 2.2.1](#221-in-vitro-and-physicochemical-data)). A value of 89% was used in this PBPK model for `Fraction unbound (plasma, reference value)`. The major binding partner was set to alpha1- acid glycoprotein(see [Section 2.2.1](#221-in-vitro-and-physicochemical-data)).137 138An important parameter influencing the resulting volume of distribution is lipophilicity. The reported experimental logP values are in the range of 0.5-1.0 (see [Section 2.2.1](#221-in-vitro-and-physicochemical-data)) which served as a starting value. Finally, the model parameters `Lipophilicity` was optimized to match best clinical data (see also [Section 2.3.4](#234-automated-parameter-identification)).139 140After 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`.141 142### 2.3.3 Metabolism and Elimination143 144One metabolic pathway was implement into the model via first order kinetics 145 146* UGT2B7147 148The UGT2B7 expression profiles is based on high-sensitive real-time RT-PCR ([Nishimura 2003](#5-references)). Absolute tissue-specific expressions were obtained by considering the respective absolute concentration in the liver. The `Specific clearance ` of fluconazole accounted by UGT2B7 was identified to best describe observed clinical data after intravenous administration (see [Section 2.3.4](#234-automated-parameter-identification)).149 150Additionally, renal clearance (which is the main elimination process for fluconazole) assumed to be mainly driven by glomerular filtration was implemented. The `GFR fraction` was identified to best describe the observed fraction of unchanged fluconazole that was renally excreted (see [Section 2.3.4](#234-automated-parameter-identification)).151 152### 2.3.4 Automated Parameter Identification153 154This is the result of the final parameter identification for the intravenous model:155 156| Model Parameter | Optimized Value | Unit |157| ------------------------------ | --------------- | --------- |158| `Lipophilicity` | 0.83 | Log Units |159| `GFR fraction` | 0.14 | |160| `Specific clearance ` (UGT2B7) | 1.85E-3 | 1/min |161 162This is the result of the final parameter identification for the dissolution parameters of a oral administered fluconazole:163 164| Model Parameter | Optimized Value | Unit |165| --------------------------------------------------- | --------------- | ---- |166| `Dissolution time (50% dissolved) high dose` | 105.81 | min |167| `Dissolution time (50% dissolved) medium high dose` | 75.14 | min |168| `Dissolution time (50% dissolved) low dose` | 33.40 | min |169| `Dissolution shape` | 2.14 | |170 171# 3 Results and Discussion<a id=""results-and-discussion""></a>172 173The PBPK model for fluconazole was developed and verified with clinical pharmacokinetic data.174 175The model was built and evaluated covering data from studies including in particular176 177* intravenous infusions and oral administrations (capsules).178* a dose range of 25 to 800 mg.179 180The model quantifies excretion via urine (glomerular filtration) and metabolism via UGT2B7.181 182The next sections show:183 1841. the final model input parameters for the building blocks: [Section 3.1](#31-fluconazole-final-input-parameters).1852. the overall goodness of fit: [Section 3.2](#32-fluconazole-diagnostics-plots).1863. 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).187 188## 3.1 Fluconazole final input parameters<a id=""fluconazole-final-input-parameters""></a>189 190The compound parameter values of the final PBPK model are illustrated below.191 192### Compound: Fluconazole193 194#### Parameters195 196Name | Value | Value Origin | Alternative | Default197------------------------------------------------ | ---------------------- | --------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------- | -------198Solubility at reference pH | 6.9 mg/ml | | Measurement_Solubility_Charoo2014 | True 199Reference pH | 7 | | Measurement_Solubility_Charoo2014 | True 200Lipophilicity | 0.8302390226 Log Units | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 1' on 2021-07-13 15:29 | Optimized_Lipophilicity | True 201Fraction unbound (plasma, reference value) | 89 % | | Measurement_Fraction_Unbound_Pfizer | True 202Specific intestinal permeability (transcellular) | 0.000213 cm/s | | Measurement_Specific_Intestinal_Permeability_GastroPlus | True 203F | 2 | | | 204Is small molecule | Yes | | | 205Molecular weight | 306.328 g/mol | | | 206Plasma protein binding partner | α1-acid glycoprotein | | | 207 208#### Calculation methods209 210Name | Value 211----------------------- | -------------------212Partition coefficients | Rodgers and Rowland213Cellular permeabilities | PK-Sim Standard 214 215#### Processes216 217##### Metabolizing Enzyme: UGT2B7-Watt2018218 219Species: Human220 221Molecule: UGT2B7222 223###### Parameters224 225Name | Value | Value Origin 226------------------- | --------------------- | ---------------------------------------------------------------------------------------------------------------------227Intrinsic clearance | 0.008 l/min | 228Specific clearance | 0.0018460294654 1/min | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 1' on 2021-07-13 15:29229 230##### Systemic Process: Glomerular Filtration-Watt2018231 232Species: Human233 234###### Parameters235 236Name | Value | Value Origin 237------------ | ------------:| ---------------------------------------------------------------------------------------------------------------------238GFR fraction | 0.1433240785 | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 1' on 2021-07-13 15:29239 240##### Inhibition: CYP3A4-Sakaeda2005241 242Molecule: CYP3A4243 244###### Parameters245 246Name | Value | Value Origin247---- | ----------- | ------------:248Ki | 13.1 µmol/l | 249 250### Formulation: Fluconazole_Weibull_high dose251 252Type: Weibull253 254#### Parameters255 256Name | Value | Value Origin 257-------------------------------- | ------------------ | ---------------------------------------------------------------------------------------------------------------------258Dissolution time (50% dissolved) | 105.8071997888 min | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 2' on 2021-07-13 18:01259Lag time | 0 min | 260Dissolution shape | 2.1410681544 | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 2' on 2021-07-13 18:01261Use as suspension | Yes | 262 263### Formulation: Fluconazole_Weibull_low dose264 265Type: Weibull266 267#### Parameters268 269Name | Value | Value Origin 270-------------------------------- | ----------------- | ---------------------------------------------------------------------------------------------------------------------271Dissolution time (50% dissolved) | 33.3965005792 min | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 2' on 2021-07-13 18:01272Lag time | 0 min | 273Dissolution shape | 2.1410681544 | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 2' on 2021-07-13 18:01274Use as suspension | Yes | 275 276### Formulation: Fluconazole_Weibull_medium high dose277 278Type: Weibull279 280#### Parameters281 282Name | Value | Value Origin 283-------------------------------- | ----------------- | ---------------------------------------------------------------------------------------------------------------------284Dissolution time (50% dissolved) | 75.1395611322 min | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 2' on 2021-07-13 18:01285Lag time | 0 min | 286Dissolution shape | 2.1410681544 | Parameter Identification-Parameter Identification-Value updated from 'Parameter Identification 2' on 2021-07-13 18:01287Use as suspension | Yes | 288 289## 3.2 Fluconazole Diagnostics Plots<a id=""fluconazole-diagnostics-plots""></a>290 291Below 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).292 293The first plot shows observed versus simulated plasma concentration, the second weighted residuals versus time. 294 295<a id=""table-3-1""></a>296 297**Table 3-1: GMFE for Goodness of fit plot for concentration in plasma.**298 299|Group |GMFE |300|:----------------------------------------------------|:----|301|Fluconazole iv (model building) |1.09 |302|Fluconazole iv (model verification) |1.14 |303|Fluconazole oral administration (model building) |1.20 |304|Fluconazole oral administration (model verification) |1.26 |305|All |1.18 |306 307<br>308<br>309 310<a id=""figure-3-1""></a>311 312313 314**Figure 3-1: Goodness of fit plot for concentration in plasma.**315 316<br>317<br>318 319<a id=""figure-3-2""></a>320 321322 323**Figure 3-2: Goodness of fit plot for concentration in plasma.**324 325<br>326<br>327 328## 3.3 Concentration-Time Profiles<a id=""ct-profiles""></a>329 330Simulated versus observed concentration-time profiles of all data listed in [Section 2.2.2](#222-clinical-data) are presented below.331 332### 3.3.1 Model Building<a id=""model-building""></a>333 334<a id=""figure-3-3""></a>335 336337 338**Figure 3-3: Time Profile Analysis**339 340<br>341<br>342 343<a id=""figure-3-4""></a>344 345346 347**Figure 3-4: Time Profile Analysis**348 349<br>350<br>351 352<a id=""figure-3-5""></a>353 354355 356**Figure 3-5: Time Profile Analysis**357 358<br>359<br>360 361<a id=""figure-3-6""></a>362 363364 365**Figure 3-6: Time Profile Analysis**366 367<br>368<br>369 370<a id=""figure-3-7""></a>371 372373 374**Figure 3-7: Time Profile Analysis**375 376<br>377<br>378 379<a id=""figure-3-8""></a>380 381382 383**Figure 3-8: Time Profile Analysis**384 385<br>386<br>387 388<a id=""figure-3-9""></a>389 390391 392**Figure 3-9: Time Profile Analysis**393 394<br>395<br>396 397<a id=""figure-3-10""></a>398 399400 401**Figure 3-10: Time Profile Analysis**402 403<br>404<br>405 406<a id=""figure-3-11""></a>407 408409 410**Figure 3-11: Time Profile Analysis**411 412<br>413<br>414 415<a id=""figure-3-12""></a>416 417418 419**Figure 3-12: Time Profile Analysis**420 421<br>422<br>423 424<a id=""figure-3-13""></a>425 426427 428**Figure 3-13: Time Profile Analysis**429 430<br>431<br>432 433<a id=""figure-3-14""></a>434 435436 437**Figure 3-14: Time Profile Analysis**438 439<br>440<br>441 442<a id=""figure-3-15""></a>443 444445 446**Figure 3-15: Time Profile Analysis**447 448<br>449<br>450 451<a id=""figure-3-16""></a>452 453454 455**Figure 3-16: Time Profile Analysis**456 457<br>458<br>459 460### 3.3.2 Model Verification<a id=""model-verification""></a>461 462<a id=""figure-3-17""></a>463 464465 466**Figure 3-17: Time Profile Analysis**467 468<br>469<br>470 471<a id=""figure-3-18""></a>472 473474 475**Figure 3-18: Time Profile Analysis**476 477<br>478<br>479 480<a id=""figure-3-19""></a>481 482483 484**Figure 3-19: Time Profile Analysis**485 486<br>487<br>488 489<a id=""figure-3-20""></a>490 491492 493**Figure 3-20: Time Profile Analysis**494 495<br>496<br>497 498<a id=""figure-3-21""></a>499 500501 502**Figure 3-21: Time Profile Analysis**503 504<br>505<br>506 507<a id=""figure-3-22""></a>508 509510 511**Figure 3-22: Time Profile Analysis**512 513<br>514<br>515 516<a id=""figure-3-23""></a>517 518519 520**Figure 3-23: Time Profile Analysis**521 522<br>523<br>524 525<a id=""figure-3-24""></a>526 527528 529**Figure 3-24: Time Profile Analysis**530 531<br>532<br>533 534# 4 Conclusion<a id=""conclusion""></a>535 536The presented PBPK model adequately describes the intravenous and oral pharmacokinetics of fluconazole in adults.537 538# 5 References<a id=""main-references""></a>539 540**Ahonen 1997** Ahonen, Jouni, Klaus T. Olkkola, and Pertti J. Neuvonen. (1997). Effect of route of administration of fluconazole on the interaction between fluconazole and midazolam. *European journal of clinical pharmacology* 51.5, 415-419.541 542**Brammer 1990** Brammer, K. W., P. R. Farrow, and J. K. Faulkner. (1990). Pharmacokinetics and tissue penetration of fluconazole in humans. *Reviews of infectious diseases* 12.Supplement_3, S318-S326.543 544**Brammer 1991** Brammer, K. W., Coakley, A. J., Jezequel, S. G., & Tarbit, M. H. (1991). The disposition and metabolism of [14C] fluconazole in humans. *Drug metabolism and disposition* 19.4, 764-767.545 546**Charoo 2014** Charoo, N., Cristofoletti, R., Graham, A., Lartey, P., Abrahamsson, B., Groot, D. W., ... & Dressman, J. (2014). Biowaiver monograph for immediate-release solid oral dosage forms: fluconazole. *Journal of pharmaceutical sciences*, *103*(12), 3843-3858.547 548**Cristofoletti 2016** Cristofoletti, R., Charoo, N. A., & Dressman, J. B. (2016). Exploratory investigation of the limiting steps of oral absorption of fluconazole and ketoconazole in children using an in silico pediatric absorption model. *Journal of pharmaceutical sciences*, *105*(9), 2794-2803.549 550**Debruyne 1993** Debruyne, D., & Ryckelynck, J. P. (1993). Clinical pharmacokinetics of fluconazole. *Clinical pharmacokinetics*, *24*(1), 10-27.551 552**Kuepfer 2016** Kuepfer L, Niederalt C, Wendl T, Schlender JF, Willmann S, Lippert J, Block M, Eissing T, Teutonico D. (2016). Applied Concepts in PBPK Modeling: How to Build a PBPK/PD Model. *CPT Pharmacometrics Syst Pharmacol*. Oct;5(10), 516-531.553 554**Meyer 2012** Meyer M, Schneckener S, Ludewig B, Kuepfer L, Lippert J. (2012). Using expression data for quantification of active processes in physiologically based pharmacokinetic modeling. *Drug Metab Dispos*. May;40(5), 892-901.555 556**Nishimura 2003** Nishimura M, Yaguti H, Yoshitsugu H, Naito S, Satoh T. (2003). Tissue distribution of mRNA expression of human cytochrome P450 isoforms assessed by high-sensitivity real-time reverse transcription PCR. *Yakugaku Zasshi.* May;123(5), 369-75.557 558**Palkama 1998** Palkama, V. J., Isohanni, M. H., Neuvonen, P. J., & Olkkola, K. T. (1998). The effect of intravenous and oral fluconazole on the pharmacokinetics and pharmacodynamics of intravenous alfentanil. *Anesthesia & Analgesia*, *87*(1), 190-194.559 560**Ripa 1993** Ripa, S., Ferrante, L., & Prenna, M. (1993). Pharmacokinetics of fluconazole in normal volunteers. *Chemotherapy*, *39*(1), 6-12.561 562**Sakaeda 2005** Sakaeda, T., Iwaki, K., Kakumoto, M., Nishikawa, M., Niwa, T., Jin, J. (2005). Effect of micafungin on cytochrome P450 3A4 and multidrug resistance protein 1 activities, and its comparison with azole antifungal drugs. *J Pharm Pharmacol*, *57*, 759-764.563 564**Shiba 1990** Shiba, K., Saito, A., & Miyahara, T. (1990). Safety and pharmacokinetics of single oral and intravenous doses of fluconazole in healthy subjects. *Clinical therapeutics*, *12*(3), 206-215.565 566**Sobue 2004** Sobue, S., Tan, K., Layton, G., Eve, M., & Sanderson, J. B. (2004). Pharmacokinetics of fosfluconazole and fluconazole following multiple intravenous administration of fosfluconazole in healthy male volunteers. *British journal of clinical pharmacology*, *58*(1), 20-25.567 568**Thorpe 1990** Thorpe, J. E., Baker, N., & Bromet-Petit, M. (1990). Effect of oral antacid administration on the pharmacokinetics of oral fluconazole. *Antimicrobial agents and chemotherapy*, *34*(10), 2032-2033.569 570**Varhe 1996** Varhe, A., Olkkola, K. T., & Neuvonen, P. J. (1996). Effect of fluconazole dose on the extent of fluconazole‐triazolam interaction. *British journal of clinical pharmacology*, *42*(4), 465-470.571 572**Watt 2018** Watt, K. M., Cohen‐Wolkowiez, M., Barrett, J. S., Sevestre, M., Zhao, P., Brouwer, K. L., & Edginton, A. N. (2018). Physiologically based pharmacokinetic approach to determine dosing on extracorporeal life support: fluconazole in children on ECMO. *CPT: pharmacometrics & systems pharmacology*, *7*(10), 629-637.573 574**Willmann 2007** Willmann S, Höhn K, Edginton A, Sevestre M, Solodenko J, Weiss W, Lippert J, Schmitt W. (2007). Development of a physiology-based whole-body population model for assessing the influence of individual variability on the pharmacokinetics of drugs. *J Pharmacokinet Pharmacodyn.* 34(3), 401-431.575 576**Yeates 1994** Yeates, R. A., Ruhnke, M., Pfaff, G., Hartmann, A., Trautmann, M., & Sarnow, E. (1994). The pharmacokinetics of fluconazole after a single intravenous dose in AIDS patients. *British journal of clinical pharmacology*, *38*(1), 77-79.577 578","Markdown"
579"PBPK model","Open-Systems-Pharmacology/OSP-PBPK-Model-Library","dAb2/dAb2_evaluation_report.md",".md","19725","337","# Building and evaluation of a PBPK model for domain antibody dAb2 in mice580 581| Version | 1.0-OSP12.2 |582| ----------------------------------------------- | ------------------------------------------------------------ |583| based on *Model Snapshot* and *Evaluation Plan* | https://github.com/Open-Systems-Pharmacology/dAb2-Model/releases/tag/v1.0 |584| OSP Version | 12.2 |585| Qualification Framework Version | 3.5 |586 587This evaluation report and the corresponding PK-Sim project file are filed at:588 589https://github.com/Open-Systems-Pharmacology/OSP-PBPK-Model-Library/590 591# Table of Contents592 593 * [1 Introduction](#introduction)594 * [2 Methods](#methods)595 * [2.1 Modeling Strategy](#modeling-strategy)596 * [2.2 Data](#methods-data)597 * [2.2.1 In vitro / physico-chemical Data ](#invitro-and-physico-chemical-data)598 * [2.2.2 PK Data <a id=""PK-data""></a>](#PK-data)599 * [2.3 Model Parameters and Assumptions](#model-parameters-and-assumptions)600 * [2.3.1 Absorption ](#model-parameters-and-assumptions-absorption)601 * [2.3.2 Distribution ](#model-parameters-and-assumptions-distribution)602 * [2.3.3 Metabolism and Elimination ](#model-parameters-and-assumptions-metabolism-and-elimination)603 * [2.3.4 Tissue Concentrations ](#model-parameters-and-assumptions-tissue-concentrations)604 * [2.3.5 Automated Parameter Identification ](#model-parameters-and-assumptions-parameter-identification)605 * [3 Results and Discussion](#results-and-discussion)606 * [3.1 Final input parameters](#final-input-parameters)607 * [3.2 Diagnostics Plots](#diagnostics-plots)608 * [3.3 Concentration-Time Profiles](#ct-profiles)609 * [4 Conclusion](#conclusion)610 * [5 References](#main-references)611 612# 1 Introduction<a id=""introduction""></a>613 614The dAb2 domain antibody is a fusion protein consisting of a VH (heavy chain) and a Vk (light chain) antibody fragment without known binding affinity which was used to a develop a PBPK model ([Sepp2015](#5-references)). 615 616Since the dAb2 is smaller than antibodies, the PK data (blood and tissue concentration–time profiles in mice) ([Sepp2015](#5-references)) were also used together with pharmacokinetic (PK) data from 5 other compounds to identify unknown parameters during the development of the generic large molecule physiologically based pharmacokinetic (PBPK) model in PK-Sim ([Niederalt 2018](#5-references)). 617 618The herein presented evaluation report evaluates the performance of the PBPK model for dAb2 in mice for the PK data used for the development of the generic large molecule model in PK-Sim.619 620The presented dAb2 PBPK model as well as the respective evaluation plan and evaluation report are provided open-source (https://github.com/Open-Systems-Pharmacology/dAb2-Model)621 622# 2 Methods<a id=""methods""></a>623 624## 2.1 Modeling Strategy<a id=""modeling-strategy""></a>625 626The development of the large molecule PBPK model in PK-Sim® has previously been described by Niederalt et al. ([Niederalt 2018](#5-references)). In short, the model was built as an extension of the PK-Sim® model for small molecules incorporating (i) the two-pore formalism for drug extravasation from blood plasma to interstitial space, (ii) lymph flow, (iii) endosomal clearance and (iv) protection from endosomal clearance by neonatal Fc receptor (FcRn) mediated recycling. 627 628For model development and evaluation, PK data were used from compounds with a wide range of solute radii and from different species. The PK data used for parameter estimation were from the following compounds: antibody–drug conjugate BAY 79-4620 in mice (Bayer in house data), antibody 7E3 in wild-type and FcRn knockout mice ([Garg 2007](#5-references), [Garg2009](#5-references)), domain antibody dAb2 in mice ([Sepp 2015](#5-references)), antibodies MEDI-524 and MEDI-524-YTE in monkeys ([Dall'Acqua 2006](#5-references)), and antibody CDA1 in humans ([Taylor 2008](#5-references)). The PK data used for model evaluation were from inulin in rats ([Tsuji1983](#5-references)) and tefibazumab in humans ([Reilly 2005](#5-references)). 629 630The PBPK model including the estimated physiological parameters as described by Niederalt et al. ([Niederalt 2018](#5-references)) is available in the Open Systems Pharmacology Suite from version 7.1 onwards.631 632This evaluation report focuses on the PBPK model for the domain antibody dAb2.633 634Details about input data (physicochemical, *in vitro* and PK) can be found in [Section 2.2](#22-data).635 636Details about the structural model and its parameters can be found in [Section 2.3](#23-model-parameters-and-assumptions).637 638## 2.2 Data<a id=""methods-data""></a>639 640### 2.2.1 In vitro / physico-chemical Data <a id=""invitro-and-physico-chemical-data""></a>641 642A literature search was performed to collect available information on physicochemical properties of dAb2. The obtained information from literature is summarized in the table below. 643 644| **Parameter** | **Unit** | **Value** | Source | **Description** |645| :------------ | -------- | --------- | ------------------------- | ------------------------------------------------------------ |646| MW | g/mol | 25600 | [Sepp2015](#5-references) | Molecular weight |647| r | nm | 2.43 | calculated from MW | Hydrodynamic solute radius. Calculated by empirical equation given in [Niederalt2018](#5-references), supplemental material |648| Kd (FcRn) | µM | 999,999 | | high value representing no FcRn binding |649 650### 2.2.2 PK Data <a id=""PK-data""></a>651 652Published plasma and tissue PK data on dAb2 in mice were used.653 654| Publication | Description |655| :------------------------ | :----------------------------------------------------------- |656| [Sepp2015](#5-references) | Plasma and tissue PK data after an intravenous dose of dose of 10 mg/kg in mice. Tissue concentrations were analyzed using quantitative whole-body autoradiography. The concentrations were reported as percentage of injected dose / g tissue. These values were converted to concentrations in µg/ml assuming a density of 1 g/ml for all tissues except for bone for which a density of 1.5 g/ml was assumed (as in Ref. [Baxter 1994](#5-references)). Furthermore, a body weight of 29 g (i.e. a dose of 290 µg) was assumed for unit conversion of the experimental concentrations (body weight range reported: 26-33 g). |657 658## 2.3 Model Parameters and Assumptions<a id=""model-parameters-and-assumptions""></a>659 660### 2.3.1 Absorption <a id=""model-parameters-and-assumptions-absorption""></a>661 662There is no absorption process since dAb2 was administered intravenously.663 664### 2.3.2 Distribution <a id=""model-parameters-and-assumptions-distribution""></a>665 666The standard lymph and fluid recirculation flow rates and the standard vascular properties of the different tissues (hydraulic conductivity, pore radii, fraction of flow via large pores) from PK-Sim were used. dAb2, among other compounds, has been used to identify these lymph and fluid recirculation flow rates used in PK-Sim ([Niederalt 2018](#5-references)). 667 668### 2.3.3 Metabolism and Elimination <a id=""model-parameters-and-assumptions-metabolism-and-elimination""></a>669 670dAb2 is predominantly renally eliminated by glomerular filtration ([Sepp 2015](#5-references)). Due to the molecular size of dAb2 the glomerular filtration is hindered and the glomerular filtration fraction was fitted. While being only of minor importance, the endosomal clearance process is present. The standard physiological parameters related to endosomal clearance were used (assuming no binding to FcRn). 671 672### 2.3.4 Tissue Concentrations <a id=""model-parameters-and-assumptions-tissue-concentrations""></a>673 674For the comparison with experimental data, the parameters `Fraction of blood for sampling` used in the Observer for the tissue concentrations were set for all organs to 0.42 for comparison with autoradiography data according to the fit results (across compounds) in Ref. ([Niederalt 2018](#5-references)). (The parameter `Fraction of blood for sampling` specifies residual blood in tissue as ratio of blood volume contributing to the measured tissue concentration to the total in vivo capillary blood volume.)675 676In the present evaluation report, the experimental gut concentrations were compared to simulated organ concentrations for small and large intestine separately in the goodness of fit plots as well as in the concentration-time profile plot.677 678### 2.3.5 Automated Parameter Identification <a id=""model-parameters-and-assumptions-parameter-identification""></a>679 680The table shows the parameter values that were specified in the model based on the parameter identification reported in Ref. ([Niederalt 2018](#5-references)), and which were not included in the PK-Sim database since version 7.1.681 682| Model Parameter | Optimized Value | Unit |683| ------------------------------------------------------------ | --------------- | ---- |684| `GFR fraction` (glomerular filtration rate fraction) | 0.24 | - |685| `Fraction of blood for sampling` (all organs) - for comparison with autoradiography data | 0.42 | |686 687# 3 Results and Discussion<a id=""results-and-discussion""></a>688 689The PBPK model for dAb2 was evaluated with blood and tissue PK data in mice.690 691These PK data (except for kidney) have been used together with PK data from 5 other compounds to simultaneously identify parameters during the development of the generic model for proteins and large molecules in PK-Sim ([Niederalt 2018](#5-references)).692 693As expected, the kidney concentrations are considerably underestimated by the PBPK simulations. In the present PBPK model, the kidney has the same organ model structure as other organs. Thus, drug within the tubular fluid does not account to total kidney concentrations. Drug in tubular fluid is relevant for small proteins which are renally cleared by glomerular filtration. For these proteins, the representation of the kidney has to be extended in order to describe total kidney concentrations, see e.g. Sepp et. al. 2015 ([Sepp 2015](#5-references)). 694 695The next sections show:696 6971. the final model parameters for the building blocks: [Section 3.1](#final-input-parameters).6982. the overall goodness of fit: [Section 3.2](#diagnostics-plots).6993. simulated vs. observed concentration-time profiles for the clinical studies used for model building and for model verification: [Section 3.3](#ct-profiles).700 701## 3.1 Final input parameters<a id=""final-input-parameters""></a>702 703The compound parameter values of the final PBPK model are illustrated below.704 705### Compound: dAb2706 707#### Parameters708 709Name | Value | Value Origin | Alternative | Default710------------------------------------------ | ------------ | --------------------------------------------- | ----------- | -------711Solubility at reference pH | 9999 mg/l | Other-/Dummy value not used in the simulation | Measurement | True 712Reference pH | 7 | Other-/Dummy value not used in the simulation | Measurement | True 713Lipophilicity | -5 Log Units | Other-/Dummy value not used in the simulation | Measurement | True 714Fraction unbound (plasma, reference value) | 1 | Other-Assumption | Measurement | True 715Is small molecule | No | | | 716Molecular weight | 25600 g/mol | Publication-Sepp2015 | | 717Plasma protein binding partner | Unknown | | | 718 719#### Calculation methods720 721Name | Value 722----------------------- | ---------------723Partition coefficients | PK-Sim Standard724Cellular permeabilities | PK-Sim Standard725 726#### Processes727 728##### Systemic Process: Glomerular Filtration-GFR729 730Species: Mouse731 732###### Parameters733 734Name | Value | Value Origin 735------------ | -----:| ------------------------736GFR fraction | 0.24 | Parameter Identification737 738## 3.2 Diagnostics Plots<a id=""diagnostics-plots""></a>739 740Below you find the goodness-of-fit visual diagnostic plots for the PBPK model performance of all data used presented in [Section 2.2.2](#PK-data).741 742The first plot shows observed versus simulated plasma concentration, the second weighted residuals versus time. 743 744<a id=""table-3-1""></a>745 746**Table 3-1: GMFE for Goodness of fit plot for concentration in blood and tissues**747 748|Group |GMFE |749|:-----------------------------------------------|:-----|750|Blood and tissue concentrations - except kidney |1.89 |751|Kidney tissue concentrations |23.23 |752|All |2.29 |753 754<br>755<br>756 757<a id=""figure-3-1""></a>758 759760 761**Figure 3-1: Goodness of fit plot for concentration in blood and tissues**762 763<br>764<br>765 766<a id=""figure-3-2""></a>767 768769 770**Figure 3-2: Goodness of fit plot for concentration in blood and tissues**771 772<br>773<br>774 775## 3.3 Concentration-Time Profiles<a id=""ct-profiles""></a>776 777Simulated versus observed concentration-time profiles of all data listed in [Section 2.2.2](#PK-data) are presented below.778 779<a id=""figure-3-3""></a>780 781782 783**Figure 3-3: Blood - lin scale**784 785<br>786<br>787 788<a id=""figure-3-4""></a>789 790791 792**Figure 3-4: Blood - log scale**793 794<br>795<br>796 797<a id=""figure-3-5""></a>798 799800 801**Figure 3-5: Lung**802 803<br>804<br>805 806<a id=""figure-3-6""></a>807 808809 810**Figure 3-6: Skin**811 812<br>813<br>814 815<a id=""figure-3-7""></a>816 817818 819**Figure 3-7: Muscle**820 821<br>822<br>823 824<a id=""figure-3-8""></a>825 826827 828**Figure 3-8: Spleen**829 830<br>831<br>832 833<a id=""figure-3-9""></a>834 835836 837**Figure 3-9: Liver**838 839<br>840<br>841 842<a id=""figure-3-10""></a>843 844845 846**Figure 3-10: Heart**847 848<br>849<br>850 851<a id=""figure-3-11""></a>852 853854 855**Figure 3-11: Bone**856 857<br>858<br>859 860<a id=""figure-3-12""></a>861 862863 864**Figure 3-12: Intestine**865 866<br>867<br>868 869<a id=""figure-3-13""></a>870 871872 873**Figure 3-13: Brain**874 875<br>876<br>877 878<a id=""figure-3-14""></a>879 880881 882**Figure 3-14: Kidney - log scale**883 884<br>885<br>886 887# 4 Conclusion<a id=""conclusion""></a>888 889The herein presented PBPK model overall adequately describes the pharmacokinetics of a domain antibody dAb2 in mice - except for kidney concentrations. Total kidney concentrations cannot be described by the standard kidney representation of PK-Sim for renally excreted biologics, since drug within the tubular fluid is not represented in the organ concentration. Apart from kidney, the largest deviations between measured and simulated concentration-time profiles are observed for spleen for which the initial concentrations are overestimated by the model and bone for which the initial concentrations are underestimated. 890 891The PK data of dAb2 (except kidney concentrations) had been used during the development of the generic large molecule PBPK model in PK-Sim ([Niederalt 2018](#5-references)) together with PK data from 5 other compounds (7E3, BAY 79-4620, CDA1, MEDI-524 & MEDI-524-YTE). 892 893# 5 References<a id=""main-references""></a>894 895**Dall'Acqua 2006** Dall’Acqua WF, Kiener PA, Wu H. Properties of human IgG1s engineered for enhanced binding to the neonatal Fc receptor (FcRn). J Biol Chem. 2006 Aug; 281(33):23514-23524. doi: 10.1074/jbc.M604292200.896 897**Garg 2007** Garg A, Balthasar JP. Physiologically-based pharmacokinetic (PBPK) model to predict IgG tissue kinetics in wild-type and FcRn-knockout mice. J Pharmacokinet Pharmacodyn. 2007 Jul; 34(5):687-709. doi: 10.1007/s10928-007-9065-1. 898 899**Garg 2009** Garg A, Balthasar J. Investigation of the influence of FcRn on the distribution of IgG to the brain. AAPS J. 2009 July; 11(3):553-557. doi: 10.1208/s12248-009-9129-9. 900 901**Lobo 2004** Lobo ED, Hansen R J, Balthasar JP. Antibody pharmacokinetics and pharmacodynamics. J Pharm Sci. 2004 Nov;93(11):2645-2668. doi: 10.1002/jps.20178.902 903**Niederalt 2018** Niederalt C, Kuepfer L, Solodenko J, Eissing T, Siegmund HU, Block M, Willmann S, Lippert J. A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim. J Pharmacokinet Pharmacodyn. 2018 Apr;45(2):235-257. doi: 10.1007/s10928-017-9559-4.904 905**Reilly 2005** Reilley S, Wenzel E, Reynolds L, Bennett B, Patti JM, Hetherington S. Open-label, dose escalation study of the safety and pharmacokinetic profile of tefibazumab in healthy volunteers. Antimicrob Agents Chemother. 2005 Mar;49(3):959–962. doi: 10.1128/AAC.49.3.959-962.2005.906 907**Sepp 2015** Sepp A, Berges A, Sanderson A, Meno-Tetang G. Development of a physiologically based pharmacokinetic model for a domain antibody in mice using the two-pore theory. J Pharmacokinet Pharmacodyn. 2015 Jan;42(2):97-109. doi: 10.1007/s10928-014-9402-0.908 909**Taylor 1984** Taylor AE, Granger DN. Exchange of macromolecules across the microcirculation. Handbook of Physiology - Cardiovascular System. Microcirculation (Eds. Renkin EM and Michel CC. Bethesda, MD, American Physiological Society). 1984; Vol. 4(Pt 2):467–520.910 911**Taylor 2008** Taylor CP, Tummala S, Molrine D, Davidson L, Farrell RJ, Lembo A, Hibberd PL, Lowy I, Kelly CP. Open-label, dose escalation phase I study in healthy volunteers to evaluate the safety and pharmacokinetics of a human monoclonal antibody to Clostridium difficile toxin A. Vaccine. 2008 Jun;26(27-28):3404–3409. doi: 10.1016/j.vaccine.2008.04.042.912 913**Tsuji 1983** Tsuji A, Yoshikawa T, Nishide K, Minami H, Kimura M, Nakashima E, Terasaki T, Miyamoto E, Nightingale CH, Yamana T. Physiologically based pharmacokinetic model for beta-lactam antibiotics I: tissue distribution and elimination in rats. J Pharm Sci. 1983 Nov;72(11):1239-1252. doi: 10.1002/jps.2600721103.914 915","Markdown"
916"PBPK model","Open-Systems-Pharmacology/OSP-PBPK-Model-Library","Felodipine/Felodipine_evaluation_report.md",".md","41856","547","# Building and evaluation of a PBPK model for Felodipine in healthy adults917 918| Version | 2.0-OSP12.2 |919| ----------------------------------------------- | ------------------------------------------------------------ |920| based on *Model Snapshot* and *Evaluation Plan* | https://github.com/Open-Systems-Pharmacology/Felodipine-Model/releases/tag/v2.0 |921| OSP Version | 12.2 |922| Qualification Framework Version | 3.5 |923 924This evaluation report and the corresponding PK-Sim project file are filed at:925 926https://github.com/Open-Systems-Pharmacology/OSP-PBPK-Model-Library/927 928# Table of Contents929 930 * [1 Introduction](#introduction)931 * [2 Methods](#methods)932 * [2.1 Modeling Strategy](#modeling-strategy)933 * [2.2 Data](#data)934 * [2.3 Model Parameters and Assumptions](#model-parameters-and-assumptions)935 * [3 Results and Discussion](#results-and-discussion)936 * [3.1 Final input parameters](#final-input-parameters)937 * [3.2 Diagnostics Plots](#diagnostics-plots)938 * [3.3 Concentration-Time Profiles](#ct-profiles)939 * [3.3.1 Model Building](#model-building)940 * [3.3.2 Model Verification](#model-verification)941 * [4 Conclusion](#conclusion)942 * [5 References](#main-references)943 944# 1 Introduction<a id=""introduction""></a>945 946Felodipine is a calcium-channel blocker, indicated for angina pectoris and arterial hypertension. It is mostly metabolized by CYP3A4 making it a sensitive probe and victim drug for the investigation of CYP3A4 activity *in vivo*. It is a BCS class II compound. Felodipine shows substantial first pass metabolism resulting in a bioavailability of 15%. 947 948The model has been developed and evaluated by comparing observed data to simulations of a large number of clinical studies covering a dose range of 1.5 mg to 10 mg after intravenous and oral administrations. Furthermore, it has been evaluated within a CYP3A4 DDI modeling network as a victim drug. 949 950Model features include:951 952- metabolism by CYP3A4953- metabolism by an unknown enzyme *via* unspecific hepatic clearance954- a decrease in the permeability between the intracellular and interstitial space (model parameters `P (intracellular->interstitial)` and `P (interstitial->intracellular)`) in intestinal mucosa to optimize quantitatively the extent of gut wall metabolism955 956# 2 Methods<a id=""methods""></a>957 958## 2.1 Modeling Strategy<a id=""modeling-strategy""></a>959 960The general concept of building a PBPK model has previously been described by Kuepfer et al. ([Kuepfer 2016](#5-references)). Relevant information on anthropometric (height, weight) and physiological parameters (e.g. blood flows, organ volumes, binding protein concentrations, hematocrit, cardiac output) in adults was gathered from the literature and has been previously published ([Willmann 2007](#5-references)). The information was incorporated into PK-Sim® and was used as default values for the simulations in adults.961 962The applied activity and variability of plasma proteins and active processes that are integrated into PK-Sim® are described in the publicly available PK-Sim® Ontogeny Database Version 7.3 ([PK-Sim Ontogeny Database Version 7.3](#5-references)) or otherwise referenced for the specific process.963 964First, a mean model was built using clinical data from single dose and multiple doses studies with intravenous and oral administration of felodipine ([Edgar 1987](#5-references), [Bailey 1996](#5-references), [Gelal 2005](#5-references), [Bailey 2003](#5-references), [Goosen 2004](#5-references), [Jalava 1997](#5-references), [Blychert 1990](#5-references), [Lundahl 1998](#5-references), [Bailey 1995](#5-references), [Aberg 1997](#5-references), [Bailey 1993](#5-references), [Edgar 1992](#5-references), [Lundahl 1997](#5-references)). One DDI study ([Jalava 1997](#5-references)) was also used in the optimization to help the model describe DDI better. The mean PBPK model was developed using a typical male European individual. The relative tissue-specific expressions of enzymes predominantly being involved in the metabolism of felodipine (CYP3A4) were considered ([Meyer 2012](#5-references)).965 966A specific selected set of parameters (see below) was optimized using the Parameter Identification module provided in PK-Sim®. Structural model selection was mainly guided by visual inspection of the resulting description of data and biological plausibility.967 968Once the appropriate structural model was identified, dissolution kinetic parameters were optimized for immediate-release tablets. 969 970The model was then evaluated by simulating further clinical studies reporting pharmacokinetic concentration-time profiles of felodipine.971 972Details about input data (physicochemical, *in vitro* and clinical) can be found in [Section 2.2](#22-data).973 974Details about the structural model and its parameters can be found in [Section 2.3](#23-model-parameters-and-assumptions).975 976## 2.2 Data<a id=""data""></a>977 978### 2.2.1 In vitro and physicochemical data979 980A literature search was performed to collect available information on physicochemical properties of felodipine. The obtained information from literature is summarized in the table below, and is used for model building.981 982| **Parameter** | **Unit** | **Value** | Source | **Description** |983| :------------------------------------ | -------------------------- | ---------------- | --------------------------------- | ------------------------------------------------------------ |984| MW | g/mol | 384.254 | [DrugBank DB01023](#5-references) | Molecular weight |985| pK<sub>a1</sub> | | n.a. | [Alskar 2018](#5-references) | Acid dissociation constant of conjugate acid |986| pK<sub>a1</sub> | | 5.07 | [Pandey 2013](#5-references) | Acid dissociation constant of conjugate acid; compound type: acid |987| Solubility (pH) | mg/L | 14.3<br />(7.1) | [Takano 2016](#5-references) | Aqueous Solubility |988| | | 1 | [Scholz 2002](#5-references) | Aqueous Solubility |989| | | 53 | [Söderlind 2010](#5-references) | Solubility in fasted state simulated intestinal fluid I |990| | | 12 | [Söderlind 2010](#5-references) | Solubility in fasted state simulated intestinal fluid II |991| | | 14 | [Söderlind 2010](#5-references) | Solubility in fasted human intestinal fluid |992| | | 15<br />(7.5) | [Persson 2005](#5-references) | Solubility in fasted human intestinal fluid |993| | | 413<br />(6.1) | [Persson 2005](#5-references) | Solubility in fed human intestinal fluid |994| | | 191 | [Persson 2005](#5-references) | Solubility in fed state simulated intestinal fluid |995| | | 77<br />(6.35) | [Scholz 2002](#5-references) | Solubility in fasted state chyme |996| | | 56<br />(4.93) | [Scholz 2002](#5-references) | Solubility in fed state chyme |997| logP | | 4.36 | [DrugBank DB01023](#5-references) | Partition coefficient between octanol and water |998| | | 3.44 | [DrugBank DB01023](#5-references) | Partition coefficient between octanol and water |999| | | 3.86 | [McPherson 2020](#5-references) | Partition coefficient between octanol and water |1000| | | 4.5 | [Scholz 2002](#5-references) | Partition coefficient between octanol and water |1001| | | 4.8 | [Bu 2006](#5-references) | Partition coefficient between octanol and water |1002| fu | % | 0.36 | [Soons 1993](#5-references) | Fraction unbound in plasma |1003| | % | 0.36 | [Ushimura 2010](#5-references) | Fraction unbound in plasma |1004| V<sub>max</sub>, K<sub>m</sub> CYP3A | pmol/mg/min,<br />µmol/L | 1630<br />2.81 | [Walsky 2004](#5-references) | CYP3A liver microsomes Michaelis-Menten kinetics |1005| V<sub>max</sub>, K<sub>m</sub> CYP3A | pmol/mg/min,<br />µmol/L | 240<br />6.9 | [Bu 2006](#5-references) | CYP3A liver microsomes Michaelis-Menten kinetics | 1006| V<sub>max</sub>, K<sub>m</sub> CYP3A4 | pmol/mg/min,<br />µmol/L | 36.8<br />0.938 | [Walsky 2004](#5-references) | Recombinant CYP3A4 Michaelis-Menten kinetics |1007| V<sub>max</sub>, K<sub>m</sub> CYP3A5 | pmol/mg/min,<br />µmol/L | 24.2<br />1.41 | [Walsky 2004](#5-references) | Recombinant CYP3A5 Michaelis-Menten kinetics | 1008 1009### 2.2.2 Clinical data1010 1011A literature search was performed to collect available clinical data on felodipine in adults. 1012 1013The following publications were found in adults for model building:1014 1015| Publication | Arm / Treatment / Information used for model building |1016| :------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------------------------- |1017| [Lundahl 1997](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 1.5 mg intravenous infusion |1018| [Edgar 1987](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine:<br />- 10 mg oral solution <br />- 10 mg extended release tablet <br />- 10 mg immediate release tablet |1019| [Blychert 1990](#5-references) | Plasma PK profiles in healthy subjects with multiple dose administrations of a felodipine:<br />- 10 mg oral solution <br />- 10 mg extended release tablet |1020| [Goosen 2004](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 5 mg extended release tablet |1021| [Jalava 1997](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 5 mg extended release tablet <br />- alone (control) <br />- with itraconazole (treatment)|1022| [Bailey 1996](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 10 mg extended release tablet |1023| [Gelal 2005](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 10 mg extended release tablet |1024| [Bailey 2003](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 10 mg extended release tablet |1025| [Bailey 1993](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 5 mg immediate release tablet |1026| [Edgar 1992](#5-references) | Plasma PK profiles in healthy subjects with single dose administrations of a felodipine 5 mg immediate release tablet |1027| [Blychert 1990](#5-references) | Plasma PK profiles in healthy subjects with multiple dose administrations of a felodipine:<br />- 10 mg oral solution <br />- 10 mg extended release tablet |1028| [Lundahl 1998](#5-references) | Plasma PK profiles in healthy subjects with multiple dose administrations of a felodipine 10 mg extended release tablet |1029| [Bailey 1995](#5-references) | Plasma PK profiles in healthy subjects with multiple dose administrations of a felodipine 10 mg extended release tablet |1030| [Aberg 1997](#5-references) | Plasma PK profiles in healthy subjects with multiple dose administrations of a felodipine 10 mg extended release tablet |1031 1032The following dosing scenarios were simulated and compared to respective data for model verification:1033 1034| Scenario | Data reference |1035| ------------------------------------------------------------ | ------------------------------------ |1036| po 5 mg single dose (extended release tablet) | [Dresser 2000](#5-references) |1037| po 10 mg single dose (extended release tablet) | [Dresser 2017](#5-references) |1038| | [Dresser 2002](#5-references) |1039| | [Bailey 2000](#5-references) |1040| | [Bailey 1998](#5-references) |1041| | [Lundahl 1997](#5-references) |1042| | [Madsen 1996](#5-references) |1043| po 2.5 / 5 mg once daily (extended release tablet) | [Dresser 2000](#5-references) |1044| po 10 mg once daily (immediate release tablet) | [Blychert 1990](#5-references) |1045| po 10 mg twice daily (immediate release tablet) | [Blychert 1990](#5-references) |1046| | [Smith 1987](#5-references) |1047| po 10 mg three times daily (immediate release tablet) | [Bratel 1989](#5-references) |1048 1049 1050## 2.3 Model Parameters and Assumptions<a id=""model-parameters-and-assumptions""></a>1051 1052### 2.3.1 Absorption1053 1054The model parameter `Specific intestinal permeability` was was calculated by PK-Sim® and kept to that value since it was insensitive. The default solubility was assumed to be measured value in fasted state simulated intestinal fluid (see [Section 2.2.1](#221-in-vitro-and-physicochemical-data))1055 1056The dissolution of both immediate and extended-release tables was implemented via two Weibull dissolution tablets, and the dissolution kinetic parameters were optimized (see [Section 2.3.4](#234-automated-parameter-identification)).1057 1058### 2.3.2 Distribution1059 1060Felodipine is highly bound to proteins in plasma (see [Section 2.2.1](#221-in-vitro-and-physicochemical-data)). A value of 0.36% was used in this PBPK model for `Fraction unbound (plasma, reference value)`. 1061 1062An important parameter influencing the resulting volume of distribution is lipophilicity. The reported experimental logP values are in the range of 4 (see [Section 2.2.1](#221-in-vitro-and-physicochemical-data)) which served as a starting value. Finally, the model parameter `Lipophilicity` was optimized to match best clinical data (see also [Section 2.3.4](#234-automated-parameter-identification)).1063 1064After 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`.1065 1066### 2.3.3 Metabolism and Elimination1067 1068Two metabolic pathways were implement into the model via Michaelis-Menten kinetics 1069 1070* CYP3A41071* unknown hepatic enzyme *via* unspecific hepatic clearance1072 1073The latter was preferred over renal clearance, since there is evidence that felodipine is fully metabolized and not found in urine ([Edgar 1987](#5-references)).1074CYP3A5 was not implemented since the fraction metabolized appeared to be minor compared to CYP3A4.1075 1076The CYP3A4 expression profiles is based on high-sensitive real-time RT-PCR ([Nishimura 2003](#5-references)). Absolute tissue-specific expressions were obtained by considering the respective absolute concentration in the liver. The PK-Sim database provides a default value for CYP3A4 (compare [Rodrigues 1999](#5-references) and assume 40 mg protein per gram liver). 1077 1078The first model simulations showed that gut wall metabolism was underrepresented in the PBPK model. In order to increase gut wall metabolism, the “mucosa permeability on basolateral side” (jointly the model parameters in the mucosa: ``P (interstitial->intracellular)`` and ``P (intracellular->interstitial)``) was estimated. A decrease in this permeability may lead to higher gut wall concentrations and, in turn, to a higher gut wall elimination. This parameter was preferred over other parameters such as relative CYP3A4 expression or fraction unbound (fu) in the gut wall as it is technically not limited to a maximum value of 100%.1079 1080### 2.3.4 Automated Parameter Identification1081 1082This is the result of the final parameter identification for the base model:1083 1084| Model Parameter | Optimized Value | Unit |1085| ------------------------------------------------------------ | ------------------------------------------------------------ | --------- |1086| `Lipophilicity` | 4.51 | Log Units |1087| Basolateral mucosa permeability<br />(``P (interstitial->intracellular)``, ``P (intracellular->interstitial)``) |0.09 | cm/min |1088| `kcat` (CYP3A4) | 204.70 | 1/min |1089| `Dissolution time` (extended release tablet) | 286.95 | min |1090| `Dissolution shape` (extended release tablet) | 0.76 | |1091| `Lag time` (extended release tablet) | 18.68 | min |1092| `Tablet time delay factor` (extended release tablet) | 0.07 | |1093| `Dissolution time` (immediate release tablet) | 46.50 | min |1094| `Dissolution shape` (immediate release tablet) | 0.89 | |1095 1096# 3 Results and Discussion<a id=""results-and-discussion""></a>1097 1098The PBPK model for felodipine was developed and verified with clinical pharmacokinetic data.1099 1100The model was built and evaluated covering data from studies including in particular1101 1102* intravenous (infusions) and oral administrations (solutions, immediate release and extended release tablets).1103* a dose range of 1.5 to 10 mg.1104 1105The model quantifies metabolism via CYP3A4, and a second unknown hepatic enzyme.1106 1107The next sections show:1108 11091. the final model input parameters for the building blocks: [Section 3.1](#31-final-input-parameters).11102. the overall goodness of fit: [Section 3.2](#32-diagnostics-plots).11113. 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).1112 1113## 3.1 Final input parameters<a id=""final-input-parameters""></a>1114 1115The compound parameter values of the final PBPK model are illustrated below.1116 1117### Compound: Felodipine1118 1119#### Parameters1120 1121Name | Value | Value Origin | Alternative | Default1122------------------------------------------ | ---------------------- | ------------------------------------------------------------------------------------------------------------------------------- | ----------- | -------1123Solubility at reference pH | 12 µg/ml | Publication-Soderlind, 2010 | FaSSIF II | True 1124Reference pH | 6.5 | Publication-Soderlind, 2010 | FaSSIF II | True 1125Lipophilicity | 4.5085714616 Log Units | Parameter Identification-Parameter Identification-Value updated from 'PI_IV+Solution+ER+DDI_additionalCL_3' on 2022-08-10 10:40 | Measurement | True 1126Fraction unbound (plasma, reference value) | 0.0036 | Publication-Ushimura, 2010 | Measurement | True 1127Cl | 2 | Internet-DrugBank DB01023 | | 1128Is small molecule | Yes | | | 1129Molecular weight | 384.254 g/mol | Internet-DrugBank DB01023 | | 1130Plasma protein binding partner | Unknown | | | 1131 1132#### Calculation methods1133 1134Name | Value 1135----------------------- | -------------------1136Partition coefficients | Rodgers and Rowland1137Cellular permeabilities | PK-Sim Standard 1138 1139#### Processes1140 1141##### Metabolizing Enzyme: CYP3A4-Walsky 20041142 1143Molecule: CYP3A41144 1145###### Parameters1146 1147Name | Value | Value Origin 1148---------------------------------- | ----------------------------- | -------------------------------------------------------------------------------------------------------------------------------1149In vitro Vmax for liver microsomes | 1630 pmol/min/mg mic. protein | Publication-Walsky 2004 1150Km | 2.81 µmol/l | Publication-Walsky 2004 1151kcat | 204.6995652687 1/min | Parameter Identification-Parameter Identification-Value updated from 'PI_IV+Solution+ER+DDI_additionalCL_3' on 2022-08-10 10:401152 1153##### Systemic Process: Total Hepatic Clearance-Unspecific hepatic clearance1154 1155Species: Human1156 1157###### Parameters1158 1159Name | Value | Value Origin 1160----------------------------- | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------1161Fraction unbound (experiment) | 0.0036 | 1162Lipophilicity (experiment) | 4.3407865958 Log Units | 1163Plasma clearance | 0 ml/min/kg | 1164Specific clearance | 12.8042083376 1/min | Parameter Identification-Parameter Identification-Value updated from 'PI_IV+Solution+ER+DDI_additionalCL_3' on 2022-08-10 10:411165 1166### Formulation: Felodipine_IR tablet1167 1168Type: Weibull1169 1170#### Parameters1171 1172Name | Value | Value Origin 1173-------------------------------- | ----------------- | -------------------------------------------------------------------------------------------------------------1174Dissolution time (50% dissolved) | 46.5005948338 min | Parameter Identification-Parameter Identification-Value updated from 'PI IR Tablet alone' on 2022-08-10 11:291175Lag time | 0 min | 1176Dissolution shape | 0.8876005929 | Parameter Identification-Parameter Identification-Value updated from 'PI IR Tablet alone' on 2022-08-10 11:291177Use as suspension | Yes | 1178 1179### Formulation: Felodipine_ER tablet1180 1181Type: Weibull1182 1183#### Parameters1184 1185Name | Value | Value Origin 1186-------------------------------- | ------------------ | -------------------------------------------------------------------------------------------------------------------------------1187Dissolution time (50% dissolved) | 286.9463213309 min | Parameter Identification-Parameter Identification-Value updated from 'PI_IV+Solution+ER+DDI_additionalCL_3' on 2022-08-10 10:411188Lag time | 18.6758448616 min | Parameter Identification-Parameter Identification-Value updated from 'PI_IV+Solution+ER+DDI_additionalCL_3' on 2022-08-10 10:411189Dissolution shape | 0.7639975313 | Parameter Identification-Parameter Identification-Value updated from 'PI_IV+Solution+ER+DDI_additionalCL_3' on 2022-08-10 10:411190Use as suspension | Yes | 1191 1192## 3.2 Diagnostics Plots<a id=""diagnostics-plots""></a>1193 1194Below 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).1195 1196The first plot shows observed versus simulated plasma concentration, the second weighted residuals versus time. 1197 1198<a id=""table-3-1""></a>1199 1200**Table 3-1: GMFE for Felodipine concentration in plasma**