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Table of Contents
Intro
Acknowledgements
Editor biographies
Piyush Pradeep Mehta
Arpana Parihar
List of contributors
Chapter Pharmaceutical implants: from concept to commercialization
1.1 Introduction
1.2 Classification of implant drug delivery system
1.2.1 Passive implants
1.2.2 Active implants
1.3 Implant manufacturing methods
1.3.1 Hot melt extrusion (HME)
1.3.2 Compression molding
1.3.3 Solvent casting
1.3.4 Injection molding
1.3.5 Three-dimensional printing (3D printing)
1.4 Drug release mechanisms from implantable delivery systems
1.4.1 Release mechanisms from biodegradable matrices
1.4.2 Release mechanisms from non-biodegradable matrices
1.5 Therapeutic applications of implantable drug delivery systems
1.5.1 Women's health
1.5.2 Ocular diseases
1.5.3 Cancer therapy
1.5.4 Central nervous system (CNS) complications
1.5.5 Other chronic diseases
1.6 Clinical trials
1.7 Current obstacles and future prospective
1.8 Conclusion
References
Chapter Green chemistry-assisted pharmaceuticals-research, revolution, and revenue
2.1 Introduction
2.2 The rise of green chemistry: a revolution
2.2.1 History and principle of green chemistry
2.2.2 Green chemistry metrics in the pharmaceutical industry
2.3 Green techniques and strategies in the pharmaceutical industry
2.4 Current status and future opportunities for green chemistry adoption in the global pharmaceutical market
2.4.1 Green chemistry drivers
2.4.2 Green chemistry barriers
2.5 Future perspective
2.6 Conclusion
Funding
Acknowledgments
Conflicts of interest
References
Chapter Ionic liquid technology for drug delivery applications
3.1 Introduction
3.2 Ionic liquids
3.2.1 Definition
3.2.2 History and perspective
3.2.3 Chemistry of ILs.
3.2.4 ILs versus deep eutectic solvents
3.2.5 Pharmaceutical applications
3.3 API-ILs
3.3.1 The need for API-ILs
3.3.2 API-ILs versus other drug forms
3.3.3 Physicochemical and pharmaceutical properties
3.3.4 Biological activity of API-ILs
3.3.5 Dual-active API-ILs
3.4 ILs as part of pharmaceutical formulation
3.4.1 IL as a solvent/vehicle
3.4.2 IL as a permeation enhancer
3.5 IL-based drug delivery systems
3.5.1 Oral drug delivery
3.5.2 Dermal and transdermal drug delivery
3.6 Commercial application and industrial viewpoint
3.6.1 Translation and production challenges
3.7 Future perspective
3.8 Conclusion
References
Chapter Advances in drug delivery systems for healthcare-from theory to practice: 3D and 4D bioprinting-promises and realities
4.1 Introduction
4.2 Additive manufacturing printing in the healthcare industry
4.2.1 3D printing
4.2.2 4D printing
4.3 History of 3D printing technology for medical applications
4.4 3D Printing techniques for medical applications
4.4.1 Fused deposition modeling
4.4.2 Stereolithography
4.4.3 Selective laser sintering
4.4.4 Laminated object manufacturing
4.5 3D and 4D bioprinting
4.5.1 Bioinks
4.5.2 Cell source
4.6 3D and 4D bioprinted drug delivery systems
4.7 Promises and realities
4.8 Current state-of-the-art and challenges in the market aspect of 3D-4D bioprinting drug delivery systems
4.9 Future remarks
4.10 Conclusions
References
Chapter Biomimicry in drug delivery: why, how, and what?
5.1 Introduction
5.2 Biomimicry in drug delivery
5.3 Why biomimicry?
5.3.1 Immunogenicity
5.4 Rationale design: how
5.5 Bio-inspired materials
5.5.1 Natural polymer
5.5.2 Cell membrane-based biomimetic
5.5.3 Biomimetic polymeric micelles
5.5.4 Biomimetic liposomes.
5.5.5 Biomimetic polymeric nanoparticles
5.5.6 Biomimetic nanohydrogel
5.5.7 Biomimetic exosome
5.5.8 Biomimetic nanorobots
5.6 Targeting ability of biomimetic drug delivery system
5.7 Conclusions
Conflict of interest
References
Chapter Personalized healthcare: advances and avenues
6.1 Introduction
6.2 Brief understanding of health and healthcare
6.3 WHO and healthcare
6.4 Healthcare status in developed and developing nations
6.5 Personalized healthcare: present status
6.5.1 DNA-based screening in personalized healthcare
6.5.2 Personalized healthcare with artificial intelligence
6.5.3 Liquid biopsy
6.5.4 Healthcare digitalization and records on family history
6.5.5 New-born screening
6.5.6 3D printing
6.5.7 Biomarkers-assisted diagnosis in relation to drug-diagnostic co-development
6.5.8 Nanocarrier therapy for treating invasive tumours
6.5.9 Digital inhaler devices
6.6 Challenges in the personalized healthcare field
6.6.1 Economical obstacles allied with personalized healthcare
6.6.2 Logistic complications associated with personalized healthcare
6.7 Personalized healthcare-futuristic possibilities
6.8 Conclusion
References
Chapter Advances and future trends in medical inhalers
7.1 Overview of medical inhalers
7.1.1 Why inhalation?
7.1.2 Where have we been and where are we going?
7.2 Pressurized metered dose inhalers (pMDIs)
7.2.1 Environmental impact
7.3 Dry powder inhalers (DPIs)
7.3.1 Passive and active DPIs
7.3.2 Essential performance attribute: da2Q
7.3.3 Essential component of DPI: dispersion engines
7.3.4 Inhaler resistance
7.3.5 Which is more important: inspiratory pressure or peak inspiratory flow rate?
7.3.6 Essential device design features: exit velocities and turbulent flows
7.3.7 Open-inhale-close DPIs.
7.3.8 High payload DPIs
7.3.9 DPIs for systemic delivery
7.3.10 Future DPI trend
7.4 Nebulizers
7.4.1 Jet, ultrasonic, and vibrating mesh nebulizers
7.4.2 Nebulizers used in critical care
7.4.3 Future nebulizer trends
7.5 Soft mist inhalers
7.6 Patient adherence
7.7 SWOT analysis
7.8 Conclusions
About the author
Acknowledgments
References
Chapter The usage of artificial intelligence in drug delivery-current trends and future outlook
8.1 Introduction
8.2 Why AI in drug delivery
8.3 Various tools and software in drug delivery
8.4 The significance of AI in formulation development
8.5 Using AI techniques for designing new medicines and delivery systems
8.5.1 Synthesis of peptides
8.5.2 Discovering new antimycobacterial medications
8.5.3 Predicting the efficacy of medication dosage and delivery techniques
8.5.4 Quick bioactive agent identification and medication release monitoring
8.5.5 Making connections between release patterns and formulation factors
8.6 AI applications in the design of drug dosage forms
8.7 Application of AI in the design of drug delivery systems
8.8 ML for in vitro optimization
8.9 ML for in vivo optimization
8.10 Future directions: how will it aid in better targeted drug formulations and future resources savings
8.11 Startups and companies working on AI dependent drug delivery
8.12 SWOT analysis
8.13 Conclusion
References
Chapter ML in drug delivery-current scenario and future trends
9.1 Digital pharmaceutical development
9.1.1 Introduction
9.1.2 Motivation and objectives of this review
9.2 Part 1: data analytics tetrahedron
9.2.1 DAT-data
9.2.2 DAT: statistics
9.2.3 DAT-ML
9.2.4 DAT: first-principles modelling
9.3 Part 2: specific barriers in data analytics
9.3.1 Data quality
9.3.2 Data quantity.
9.3.3 Bias and variance (B-V)
9.3 4 Data leakage
9.3.5 Lack of ML frameworks
9.4 Part 3: case studies
9.4.1 Chemistry, manufacturing, and control (CMC)
9.4.2 ML approach in material property investigation
9.4.3 ML in formulation development
9.4.4 ML approach in end-product testing
9.4.5 ML approach in in vitro drug release and in vivo pharmacokinetic predictions
9.4.6 ML in translational development of drug product and device
9.4.7 Advanced concepts
9.5 Challenges and outlook
9.6 Conclusion
https://doi.org/10.1016/J.JCONREL.2021.08.030
https://doi.org/10.1016/J.JCONREL.2021.08.030
Author contributions
Acknowledgments
Conflicts of interest
References
Chapter Soft mist inhaler delivery of biologics
10.1 Introduction
10.2 Towards soft mist inhalation delivery
10.3 Developing a soft mist inhaled combination product: considerations
10.3.1 Patient
10.3.2 Technical considerations: device and formulation
10.3.3 Regulatory considerations
10.4 Current research and clinical outlook
10.5 Concluding remarks
About the author
References
Chapter Computational approaches for antibody-based drug design
11.1 Introduction
11.2 Antibody structure and function
11.2.1 Antigen recognition and binding
11.2.2 Fragment crystallizable (Fc)
11.2.3 Antibody function
11.3 Computational tools for antibody design
11.3.1 Antibody databases
11.3.2 Structure prediction
11.3.3 Interface prediction
11.3.4 Antibody grafting and humanization
11.3.5 Developability
11.4 Antibodies and antibody-based structures and their applications
11.4.1 Antibody drugs
11.4.2 Nanobodies
11.4.3 Antibody-drug conjugates
11.4.4 Antibody-based PROTACs
11.5 Production cost and market value of antibodies
11.5.1 Monoclonal antibodies
11.5.2 Bispecific antibodies.
11.6 Conclusions.
Acknowledgements
Editor biographies
Piyush Pradeep Mehta
Arpana Parihar
List of contributors
Chapter Pharmaceutical implants: from concept to commercialization
1.1 Introduction
1.2 Classification of implant drug delivery system
1.2.1 Passive implants
1.2.2 Active implants
1.3 Implant manufacturing methods
1.3.1 Hot melt extrusion (HME)
1.3.2 Compression molding
1.3.3 Solvent casting
1.3.4 Injection molding
1.3.5 Three-dimensional printing (3D printing)
1.4 Drug release mechanisms from implantable delivery systems
1.4.1 Release mechanisms from biodegradable matrices
1.4.2 Release mechanisms from non-biodegradable matrices
1.5 Therapeutic applications of implantable drug delivery systems
1.5.1 Women's health
1.5.2 Ocular diseases
1.5.3 Cancer therapy
1.5.4 Central nervous system (CNS) complications
1.5.5 Other chronic diseases
1.6 Clinical trials
1.7 Current obstacles and future prospective
1.8 Conclusion
References
Chapter Green chemistry-assisted pharmaceuticals-research, revolution, and revenue
2.1 Introduction
2.2 The rise of green chemistry: a revolution
2.2.1 History and principle of green chemistry
2.2.2 Green chemistry metrics in the pharmaceutical industry
2.3 Green techniques and strategies in the pharmaceutical industry
2.4 Current status and future opportunities for green chemistry adoption in the global pharmaceutical market
2.4.1 Green chemistry drivers
2.4.2 Green chemistry barriers
2.5 Future perspective
2.6 Conclusion
Funding
Acknowledgments
Conflicts of interest
References
Chapter Ionic liquid technology for drug delivery applications
3.1 Introduction
3.2 Ionic liquids
3.2.1 Definition
3.2.2 History and perspective
3.2.3 Chemistry of ILs.
3.2.4 ILs versus deep eutectic solvents
3.2.5 Pharmaceutical applications
3.3 API-ILs
3.3.1 The need for API-ILs
3.3.2 API-ILs versus other drug forms
3.3.3 Physicochemical and pharmaceutical properties
3.3.4 Biological activity of API-ILs
3.3.5 Dual-active API-ILs
3.4 ILs as part of pharmaceutical formulation
3.4.1 IL as a solvent/vehicle
3.4.2 IL as a permeation enhancer
3.5 IL-based drug delivery systems
3.5.1 Oral drug delivery
3.5.2 Dermal and transdermal drug delivery
3.6 Commercial application and industrial viewpoint
3.6.1 Translation and production challenges
3.7 Future perspective
3.8 Conclusion
References
Chapter Advances in drug delivery systems for healthcare-from theory to practice: 3D and 4D bioprinting-promises and realities
4.1 Introduction
4.2 Additive manufacturing printing in the healthcare industry
4.2.1 3D printing
4.2.2 4D printing
4.3 History of 3D printing technology for medical applications
4.4 3D Printing techniques for medical applications
4.4.1 Fused deposition modeling
4.4.2 Stereolithography
4.4.3 Selective laser sintering
4.4.4 Laminated object manufacturing
4.5 3D and 4D bioprinting
4.5.1 Bioinks
4.5.2 Cell source
4.6 3D and 4D bioprinted drug delivery systems
4.7 Promises and realities
4.8 Current state-of-the-art and challenges in the market aspect of 3D-4D bioprinting drug delivery systems
4.9 Future remarks
4.10 Conclusions
References
Chapter Biomimicry in drug delivery: why, how, and what?
5.1 Introduction
5.2 Biomimicry in drug delivery
5.3 Why biomimicry?
5.3.1 Immunogenicity
5.4 Rationale design: how
5.5 Bio-inspired materials
5.5.1 Natural polymer
5.5.2 Cell membrane-based biomimetic
5.5.3 Biomimetic polymeric micelles
5.5.4 Biomimetic liposomes.
5.5.5 Biomimetic polymeric nanoparticles
5.5.6 Biomimetic nanohydrogel
5.5.7 Biomimetic exosome
5.5.8 Biomimetic nanorobots
5.6 Targeting ability of biomimetic drug delivery system
5.7 Conclusions
Conflict of interest
References
Chapter Personalized healthcare: advances and avenues
6.1 Introduction
6.2 Brief understanding of health and healthcare
6.3 WHO and healthcare
6.4 Healthcare status in developed and developing nations
6.5 Personalized healthcare: present status
6.5.1 DNA-based screening in personalized healthcare
6.5.2 Personalized healthcare with artificial intelligence
6.5.3 Liquid biopsy
6.5.4 Healthcare digitalization and records on family history
6.5.5 New-born screening
6.5.6 3D printing
6.5.7 Biomarkers-assisted diagnosis in relation to drug-diagnostic co-development
6.5.8 Nanocarrier therapy for treating invasive tumours
6.5.9 Digital inhaler devices
6.6 Challenges in the personalized healthcare field
6.6.1 Economical obstacles allied with personalized healthcare
6.6.2 Logistic complications associated with personalized healthcare
6.7 Personalized healthcare-futuristic possibilities
6.8 Conclusion
References
Chapter Advances and future trends in medical inhalers
7.1 Overview of medical inhalers
7.1.1 Why inhalation?
7.1.2 Where have we been and where are we going?
7.2 Pressurized metered dose inhalers (pMDIs)
7.2.1 Environmental impact
7.3 Dry powder inhalers (DPIs)
7.3.1 Passive and active DPIs
7.3.2 Essential performance attribute: da2Q
7.3.3 Essential component of DPI: dispersion engines
7.3.4 Inhaler resistance
7.3.5 Which is more important: inspiratory pressure or peak inspiratory flow rate?
7.3.6 Essential device design features: exit velocities and turbulent flows
7.3.7 Open-inhale-close DPIs.
7.3.8 High payload DPIs
7.3.9 DPIs for systemic delivery
7.3.10 Future DPI trend
7.4 Nebulizers
7.4.1 Jet, ultrasonic, and vibrating mesh nebulizers
7.4.2 Nebulizers used in critical care
7.4.3 Future nebulizer trends
7.5 Soft mist inhalers
7.6 Patient adherence
7.7 SWOT analysis
7.8 Conclusions
About the author
Acknowledgments
References
Chapter The usage of artificial intelligence in drug delivery-current trends and future outlook
8.1 Introduction
8.2 Why AI in drug delivery
8.3 Various tools and software in drug delivery
8.4 The significance of AI in formulation development
8.5 Using AI techniques for designing new medicines and delivery systems
8.5.1 Synthesis of peptides
8.5.2 Discovering new antimycobacterial medications
8.5.3 Predicting the efficacy of medication dosage and delivery techniques
8.5.4 Quick bioactive agent identification and medication release monitoring
8.5.5 Making connections between release patterns and formulation factors
8.6 AI applications in the design of drug dosage forms
8.7 Application of AI in the design of drug delivery systems
8.8 ML for in vitro optimization
8.9 ML for in vivo optimization
8.10 Future directions: how will it aid in better targeted drug formulations and future resources savings
8.11 Startups and companies working on AI dependent drug delivery
8.12 SWOT analysis
8.13 Conclusion
References
Chapter ML in drug delivery-current scenario and future trends
9.1 Digital pharmaceutical development
9.1.1 Introduction
9.1.2 Motivation and objectives of this review
9.2 Part 1: data analytics tetrahedron
9.2.1 DAT-data
9.2.2 DAT: statistics
9.2.3 DAT-ML
9.2.4 DAT: first-principles modelling
9.3 Part 2: specific barriers in data analytics
9.3.1 Data quality
9.3.2 Data quantity.
9.3.3 Bias and variance (B-V)
9.3 4 Data leakage
9.3.5 Lack of ML frameworks
9.4 Part 3: case studies
9.4.1 Chemistry, manufacturing, and control (CMC)
9.4.2 ML approach in material property investigation
9.4.3 ML in formulation development
9.4.4 ML approach in end-product testing
9.4.5 ML approach in in vitro drug release and in vivo pharmacokinetic predictions
9.4.6 ML in translational development of drug product and device
9.4.7 Advanced concepts
9.5 Challenges and outlook
9.6 Conclusion
https://doi.org/10.1016/J.JCONREL.2021.08.030
https://doi.org/10.1016/J.JCONREL.2021.08.030
Author contributions
Acknowledgments
Conflicts of interest
References
Chapter Soft mist inhaler delivery of biologics
10.1 Introduction
10.2 Towards soft mist inhalation delivery
10.3 Developing a soft mist inhaled combination product: considerations
10.3.1 Patient
10.3.2 Technical considerations: device and formulation
10.3.3 Regulatory considerations
10.4 Current research and clinical outlook
10.5 Concluding remarks
About the author
References
Chapter Computational approaches for antibody-based drug design
11.1 Introduction
11.2 Antibody structure and function
11.2.1 Antigen recognition and binding
11.2.2 Fragment crystallizable (Fc)
11.2.3 Antibody function
11.3 Computational tools for antibody design
11.3.1 Antibody databases
11.3.2 Structure prediction
11.3.3 Interface prediction
11.3.4 Antibody grafting and humanization
11.3.5 Developability
11.4 Antibodies and antibody-based structures and their applications
11.4.1 Antibody drugs
11.4.2 Nanobodies
11.4.3 Antibody-drug conjugates
11.4.4 Antibody-based PROTACs
11.5 Production cost and market value of antibodies
11.5.1 Monoclonal antibodies
11.5.2 Bispecific antibodies.
11.6 Conclusions.