Quantitative systems pharmacology : models and model-based systems with applications

417 Pages·2018·19.823 MB·English

by  Davide Manca

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Computer Aided
Chemical Engineering
Quantitative Systems
Pharmacology
Models and Model-Based Systems
with Applications
Volume 42
Edited by
Davide Manca
Process Systems EngineeringLaboratory,
Dipartimento di Chimica,
Materialie Ingegneria Chimica “Giulio Natta”,
Politecnico di Milano, Milano, Italy
Elsevier
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Contents
Contributors.............................................................................................................xv
Preface....................................................................................................................xix
Acknowledgments..................................................................................................xxi
SECTION 1 INTRODUCTION TO QUANTITATIVE
SYSTEMS PHARMACOLOGY
CHAPTER 1 Quantitative Systems Pharmacology: Extending
the Envelope Through Systems Engineering...................3
Clara Hartmanshenn, Rohit T.Rao,Seul-A.Bae,
Megerle L. Scherholz, Alison Acevedo, Kamau K.Pierre,
Ioannis P. Androulakis
1. Introduction.....................................................................................3
2. TheEmergence ofQSP Modeling.................................................4
2.1. Multiscale Modeling:Beyond the DrugTarget.....................5
2.2. Modelingthe Disease State....................................................6
3. Modeling Drug Exposure andDrugResponse
at the Systemic Level.....................................................................9
4. Modeling Biological and Drug Interactions
at the Molecular Level..................................................................11
4.1. Omics Data...........................................................................11
4.2. Genomics..............................................................................11
4.3. Transcriptomics....................................................................12
4.4. Proteomics............................................................................13
4.5. Metabolomics........................................................................13
4.6. Omics Network Using PathwayEnrichment.......................14
4.7. Case Study: PathwayEnrichment for
Synthetic MPL......................................................................15
5. Summary of the Model Development Process.............................17
6. QSPinContext.............................................................................18
6.1. Case Study: Cortisol Regulation inthe Context
ofEnvironmentalClues: Next Challenges...........................20
7. HowSystems Engineering Can Enable QSP...............................22
8. FinalComments............................................................................23
Acknowledgments.............................................................................24
References..........................................................................................24
v
vi Contents
SECTION 2 MODELING AND APPLICATIONS
OF SYSTEMIC PHARMACOKINETICS
AND PHARMACODYNAMICS
CHAPTER 2 An Engineering Oriented Approach to
Physiologically Based Pharmacokinetic and
Pharmacodynamic Modeling...............................................37
Roberto A. Abbiati, Adriana Savoca, Davide Manca
1. Introduction...................................................................................37
2. Classic Compartmental Pharmacokinetic Models........................39
3. Physiologically Based Pharmacokinetic Models.........................40
3.1. Individualizationof the PharmacokineticPrediction...........44
3.2. Model Identification.............................................................44
4. Introduction toPharmacodynamics..............................................49
5. Mathematical Formulation of aPBPK Model.............................49
5.1. The PBPK Model.................................................................50
6. Mathematical Formulation of PDModels....................................55
6.1. Direct Effect Model:Hill Equation......................................56
6.2. IndirectResponse Models....................................................58
6.3. Irreversible Effect Models....................................................60
7. Conclusions...................................................................................60
References..........................................................................................61
CHAPTER 3 Advanced Techniques for the Optimal Design
of Experiments in Pharmacokinetics...............................65
Federico Galvanin, Fabrizio Bezzo
1. Introduction...................................................................................65
2. Identifying aPhysiologicalModel: TheNeedfor
Experimental Design.....................................................................66
3. Design of Experiments Under Constraints for
Physiological Models....................................................................67
3.1. Design Procedure..................................................................69
3.2. Design ofExperimental Protocols Under
Uncertainty............................................................................69
4. Case Study I: Identification of aPK–PD Model.........................71
5. Case Study II: Design of More Effective ClinicalTests
for the Study ofVWD..................................................................76
6. Conclusions...................................................................................81
References..........................................................................................82
Contents vii
CHAPTER 4 On the Identifiability of Physiological Models:
Optimal Design of Clinical Tests.......................................85
Fabrizio Bezzo, FedericoGalvanin
1. Introduction...................................................................................85
2. TheConcept ofIdentifiability......................................................87
3. Identifiability Tests.......................................................................88
3.1. APriori Testsfor Parametric Identifiability........................88
3.2. APosteriori Tests for ParametricIdentifiability.................89
3.3. Practical IdentifiabilityofParametric Models.....................92
4. Identifiability inthe Developmentof Compartmental
Models...........................................................................................93
5. Optimal Design of ClinicalTests for Guaranteed
Identifiability.................................................................................95
6. Case Study: Identification ofPhysiologicalModels
ofVWD.........................................................................................97
6.1. StructuralIdentifiabilityofCandidate
VWD Models......................................................................101
6.2. Practical IdentifiabilityFrom Clinical Tests
andInformation Analysis...................................................103
7. Conclusions.................................................................................107
References........................................................................................108
CHAPTER 5 Bayesian Hierarchical Modeling of Gabapentin
Absorption and Disposition with Application
to Dosing Regimen Assessment.......................................111
Stephen D. Stamatis, LinasMockus, Lee E.Kirsch,
Gintaras V. Reklaitis
1. Introduction.................................................................................111
2. Methods.......................................................................................113
3. Model Description......................................................................115
3.1. Absorption Model...............................................................116
3.2. Disposition Model..............................................................118
3.3. Initial Conditions................................................................121
3.4. Statistical Model.................................................................121
4. Implementation...........................................................................125
5. Results and Discussion...............................................................128
6. Conclusions.................................................................................133
7. Future Directions........................................................................134
References........................................................................................134
viii Contents
CHAPTER 6 Computational Tools in the Assistance
of Personalized Healthcare...............................................139
Maria M. Papathanasiou,Melis Onel, Ioana Nascu,
EfstratiosN. Pistikopoulos
1. Introduction.................................................................................139
1.1. DiseaseDynamics...............................................................139
1.2. Patient Variability...............................................................140
1.3. Data Availability.................................................................141
2. Mathematical Approaches inBiomedical
Systems.......................................................................................142
2.1. Big Data Analytics.............................................................142
2.2. Metabolic Networks andOther Modeling
Approaches.........................................................................145
2.3. Dynamic,Quantitative Mathematical
Modeling.............................................................................146
3. ControlinBiomedical Systems..................................................153
4. The PAROC Framework andSoftware Platform......................157
4.1. High-Fidelity Modelingand Analysis................................158
4.2. Model Approximation........................................................158
4.3. Multiparametric Programming andControl.......................159
4.4. Moving Horizon Estimation (MHE)..................................159
5. PAROC ApplicationtoBiomedical Systems.............................161
5.1. AML....................................................................................161
5.2. The AnesthesiaProcess......................................................170
5.3. Diabetes..............................................................................180
6. Conclusions.................................................................................187
Acknowledgments...........................................................................188
Appendix A.1. Mathematical Model for AML...................................................188
A.1.1. Treatment Inflow............................................................188
A.1.2. Pharmacokinetic Model..................................................188
A.1.3. PharmacodynamicModel...............................................189
A.1.4. Cancer Cell Cycle Model...............................................189
A.1.5. Normal CellCycle Model..............................................190
A.1.6. Drug Subcutaneous Route..............................................191
Appendix A.2. Mathematical Model for Intravenous
Anesthesia...................................................................................191
Appendix A.3. Mathematical Model for Volatile
Anesthesia...................................................................................193
Appendix A.4. Mathematical Model for Diabetes..............................................195
References........................................................................................198
Contents ix
SECTION 3 TRANSPORT AND DISTRIBUTION
OF DRUGS TO TARGET SITES
CHAPTER 7 Multiscale Models for Transport and
Biodistribution of Therapeutics in Cancer...................209
Arturas Ziemys,Milos Kojic, Miljan Milosevic,
Bernhard Schrefler,Mauro Ferrari
1. Introduction.................................................................................209
2. Computational Modelsof Payload Release From
Drug Vectors...............................................................................210
3. Computational Modelsof Biodistributionin Tissue
Microenvironment.......................................................................217
4. BiodistributionModelsfor the Entire Tumor............................221
4.1. Pipe 1D Vessel Network....................................................224
4.2. Smeared 3D Model Data....................................................224
4.3. Time Steps..........................................................................224
5. Tumor ResponseModel..............................................................227
6. Concluding Remarks...................................................................233
Acknowledgement...........................................................................233
References........................................................................................234
CHAPTER 8 Quantitative Systems Pharmacology on Cancer
Drug Delivery to Target Sites: Application of
Chemical Engineering Tools.............................................239
Roberto A.Abbiati,JessieL.-S. Au
1. Introduction.................................................................................240
1.1. Purposeof QuantitativeSystems Pharmacology...............240
1.2. Unique Challenges for Cancer Therapeutics.....................240
1.3. ApplicationofChemical Engineering Tools inQSP........241
1.4. ContentOverview...............................................................241
2. Kinetic Processes inDelivering Therapeutics toTheir
Intended Targets.........................................................................242
2.1. Transport From the Injection Siteto the Tumor
Interstitium..........................................................................242
2.2. Transport From the Interstitial Space toMolecular
Targets on Cell Membrane orInside the Cell...................242
3. Transport Barriers.......................................................................244
3.1. Reduced Transport Due to Abnormality inTumor
Blood and Lymphatic Systems...........................................244
3.2. Extravasation......................................................................245
3.3. Interstitial Transport...........................................................245