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E-raamat: Biotechnology in Healthcare, Volume 1: Technologies and Innovations

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  • Ilmumisaeg: 30-Mar-2022
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  • ISBN-13: 9780323898782
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Biotechnology in Healthcare, Volume 1: Technologies and InnovationsSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 30-Mar-2022
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780323898782
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Biotechnology in Healthcare, Technologies and Innovations, Volume One presents up-to-date knowledge on the emerging field of biotechnology as applied to the healthcare industry. Sections cover 3D printing, tissue engineering, synthetic biology, nano-biotechnology, omics, precision medicine, gene therapy, vaccine development, predictive healthcare, entrepreneurship, financing, business models, product development and marketing in the sector. This is a valuable source for biotechnologists, bioinformaticians, clinicians and members of biomedical and healthcare fields who need to understand more about the promising developments of the emerging field of biotechnology in healthcare.
  • Presents the progress and innovations that biotechnology has accomplished in the field of healthcare
  • Discusses the impact of healthcare biotechnology in global economics and business prospects
  • Explains how biotechnology revolutionizes future healthcare approaches
List of contributors
xiii
About the editor xvii
Preface xix
1 Overview of healthcare biotechnology
1(26)
Aiman Tanveer
Kanchan Yadav
Shruti Dwivedi
Supriya Gupta
Pramod K. Yadav
Dinesh Yadav
1.1 Introduction
1(1)
1.2 Genomics
1(6)
1.2.1 Genetic screening and testing
3(1)
1.2.2 Diagnosis of genetic disorders
3(3)
1.2.3 Pharmacogenomics and epigenomics
6(1)
1.2.4 Personalized medicine
6(1)
1.3 Transcriptomics
7(3)
1.3.1 Tools of transcriptomics
7(2)
1.3.2 Transcriptomics in disease diagnosis
9(1)
1.3.3 Transcriptome profiling in drug discovery
10(1)
1.4 Proteomics
10(4)
1.4.1 Tools and techniques in the proteomics-based study
10(3)
1.4.2 Biomarker discovery
13(1)
1.4.3 Drug development
13(1)
1.5 Metabolomics
14(6)
1.5.1 Tools and techniques in metabolomics study
16(2)
1.5.2 Metabolomics in treatment of cancer, neurological, and psychiatric disorders
18(2)
1.5.3 Individualized metabolomics
20(1)
1.6 Conclusion
20(1)
Acknowledgments
20(1)
References
20(7)
2 Three-dimensional printing in healthcare
27(14)
Yusuf Izci
2.1 Introduction
27(1)
2.2 Three-dimensional printing technology (hardware and software)
27(3)
2.3 Materials of three-dimensional printing
30(1)
2.4 Three-dimensional printing in surgical planning and medical education
31(1)
2.5 Three-dimensional printing in oral and maxillofacial surgery
32(1)
2.6 Three-dimensional printing in orthopedics
33(1)
2.7 Three-dimensional printing in neurosurgery
33(2)
2.8 Bioprinting tissue and organ fabrication
35(1)
2.9 Three-dimensional printing in pharmaceutical industry
36(1)
2.10 Future of three-dimensional printing
36(1)
2.10.1 Limitations of three-dimensional printings
37(1)
2.11 Conclusion
37(1)
References
37(4)
3 Synthetic biology in healthcare: technologies and applications
41(14)
Mubashir Hassan
Anam Naz
Ammara Siddique
Saba Shahzadi
Salah ud Din
Zainab Yaseen
Sawaira Naqvi
Qinza Ali
Faryal Mehwish Awan
Aqsa Ikram
3.1 Introduction
41(1)
3.1.1 Cell-free systems and applications
41(1)
3.2 Technologies for synthetic DNA, proteins, and organisms
41(1)
3.2.1 Synthetic biology-based Doggybone DNA technology and its uses in vaccines and DNA-based gene therapy products
41(1)
3.2.2 Development of linear dbDNA vaccine construct
42(1)
3.3 Gen9 technology---microfluidic devices and methods for gene synthesis
42(4)
3.3.1 DNA synthesis and scale up (BioFab platform)
42(1)
3.3.2 Technologies for synthetic genomes
43(1)
3.3.3 Synthetic biology to create an artificial membrane-binding protein
43(1)
3.3.4 Pathway rewiring with adapters and scaffolds
44(1)
3.3.5 Synthetic DNA for developing new antibiotics
44(1)
3.3.6 Synthetic DNA for amino-acid replacement
44(1)
3.3.7 Synthetic proteins technologies
45(1)
3.3.8 Technologies to create synthetic organisms
45(1)
3.3.9 Synthetic biology applications in diagnostics
46(1)
3.4 Transcriptional, posttranslational, and hybrid biosensing and applications
46(1)
3.4.1 Transcriptional biosensing
46(1)
3.4.2 Posttranslational biosensing
46(1)
3.4.3 Hybrid biosensing
46(1)
3.5 Applications
46(3)
3.5.1 Paper-based diagnostic
47(1)
3.5.2 Synthetic biology applications for drug discovery and therapy
47(1)
3.5.3 Drug-target identification (synthetic pathways and systems)
48(1)
3.5.4 Drug discovery
48(1)
3.5.5 Therapeutic treatment (synthetic biology devices)
48(1)
3.5.6 Therapeutic delivery
48(1)
3.6 Synthetic biology for creating living systems to produce small molecules, for instance, aspirin, that characteristically come from chemical rather than the biological processes
49(1)
3.6.1 CodeEvolver-like protein-engineering synthetic-biology platform to create unique enzymes as therapeutics
49(1)
3.6.2 Chimeric antigen receptor
49(1)
3.6.3 Synthetic genomes and vaccine design (SARS-CoV-2 and other viruses)
49(1)
3.7 Living therapies---engineering microbes and bacteriophage to treat disease
50(1)
3.7.1 Engineered bacteria (such as Salmonella) to deliver vaccines
50(1)
3.7.2 Understanding disease mechanism
50(1)
3.7.3 Synthetic biology-based pathway engineering for pharmaceutical production
50(1)
3.7.4 Constructing biosynthetic pathways
50(1)
3.7.5 Optimizing pathway flux
51(1)
3.7.6 Programming novel functionality and materials
51(1)
3.7.7 Chemical retrosynthesis and its future applications in healthcare
51(1)
3.8 Future challenges and conclusions
51(1)
Acknowledgment
52(1)
References
52(3)
4 Nanotechnology in healthcare: nanoparticles for diagnostic and therapy
55(16)
Tugba Tezcan
Chia-Hsien Hsu
4.1 Introduction
55(1)
4.2 Classification and properties of nanoparticles
56(3)
4.2.1 Gold nanoparticles
56(1)
4.2.2 Magnetic nanoparticles
57(1)
4.2.3 Quantum dots
57(1)
4.2.4 Carbon nanostructures
58(1)
4.2.5 Polymeric nanoparticles
58(1)
4.3 Nanoparticle-based biosensors for medical diagnosis
59(2)
4.3.1 Plasmonic biosensors
59(1)
4.3.2 QD-based biosensors
60(1)
4.3.3 Carbon nanostructure-based biosensors
61(1)
4.4 Nanoparticle-based therapy and imaging
61(4)
4.4.1 Targeted drug delivery
62(1)
4.4.2 Bioimaging and photothermal therapy
63(1)
4.4.3 Nanoparticles in the clinic
64(1)
4.5 Conclusion and future perspective
65(1)
References
65(6)
5 Analysis and applications of sequencing in healthcare
71(12)
Maloyjo Joyraj Bhattacharjee
Basant K. Tiwary
5.1 Introduction
71(1)
5.2 Method of de-novo and reference-based DNA sequencing
71(1)
5.3 Generation of DNA reads
72(1)
5.4 Quality assessment of reads
73(1)
5.5 Trimming of DNA reads
74(1)
5.6 Mapping of DNA reads
74(1)
5.7 Assembly
75(1)
5.8 Analysis of DNA sequences for marker-based surveillance of diseases
75(1)
5.9 Phylomedicine of genetic diseases
76(1)
5.10 Method of de-novo and reference-based RNA sequencing
76(1)
5.11 Generation of short RNA reads and quality assessment
77(1)
5.12 Trimming of RNA reads
77(1)
5.13 Mapping of RNA reads
77(1)
5.14 Assembly of RNA reads
77(1)
5.15 Analysis of differential expression of genes in diseases states and in prognosis of disease
78(1)
5.16 Analysis of alternative splicing of genes and gene fusion in disease states
78(1)
5.17 Analysis of long noncoding RNA and its relevance to disease
78(1)
5.18 Gene coexpression analysis and annotation of TF-TFBS and gene regulatory network
79(1)
5.19 Method of DAP-sequencing and genome-wide annotation of cistrome
79(2)
5.20 Analysis of DAP sequences and its application in healthcare
81(1)
5.21 Genome-wide mapping of TF-TFBS and visualization of gene-regulatory network
81(1)
References
81(2)
6 Innovative technologies in precision healthcare
83(20)
Soltys Katarina
Kloc Marek
Rabajdova Miroslava
Marekova Maria
6.1 Defining precision and personalized medicine
83(2)
6.1.1 Assessing emerging technologies for personalized precision medicines' clinical trials
83(1)
6.1.2 Biosensors in personalized medicine
84(1)
6.1.3 Omics in precision healthcare
84(1)
6.1.4 Engineering precision medicine technology and platforms
84(1)
6.2 Databases applications in precision healthcare
85(2)
6.2.1 Microbiome databases
85(1)
6.2.2 Databases for protein-coding genes
86(1)
6.2.3 Databases for noncoding genes
86(1)
6.2.4 Databases used for annotation of human genetic variants and rearrangements
86(1)
6.2.5 Prediction of gene function
87(1)
6.3 Bioengineering, machine learning for personalized medicine
87(3)
6.3.1 Principle of machine learning
87(1)
6.3.2 Why machine learning?
88(1)
6.3.3 Supervised machine learning
89(1)
6.3.4 Unsupervised machine learning
89(1)
6.3.5 Reinforcement learning
89(1)
6.3.6 Online learning
90(1)
6.3.7 Recommendations in machine learning
90(1)
6.3.8 Testing and verification
90(1)
6.4 Application of bioinformatics machine learning and in-depth data analysis
90(10)
6.4.1 Get the data
91(1)
6.4.2 Explore and prepare data
91(1)
6.4.3 Feature selection with decision trees
92(2)
6.4.4 Feature selection by analysis
94(1)
6.4.5 Analysis with edgeR or DESeq2
94(2)
6.4.6 Pickup machine learning models
96(1)
6.4.7 Evaluate machine learning model
96(2)
6.4.8 Workflow for processing readings in RNA-seq
98(2)
6.5 BIG DATA
100(1)
Acknowledgments
101(1)
References
101(2)
7 Omics applications in reproductive medicine
103(22)
Rabajdova Miroslava
Soltys Katarina
Spakova Ivana
Urdzik Peter
7.1 Genetic testing and molecular methods of female infertility
103(6)
7.1.1 Molecular methods of transcriptome analysis in female infertility
103(1)
7.1.2 Methods of metabolomics analysis of female infertility
104(2)
7.1.3 Methods of proteomics analysis of female infertility
106(1)
7.1.4 Molecular methods of microbial analysis of female infertility
107(1)
7.1.5 Molecular methods of genomic analysis of female infertility
108(1)
7.2 Genetic testing and molecular methods of male infertility
109(6)
7.2.1 Molecular methods of transcriptome analysis of male infertility
110(1)
7.2.2 Methods of metabolomics analysis of male infertility
111(1)
7.2.3 Molecular methods of proteomic analysis of male infertility
111(1)
7.2.4 Molecular methods of microbial anafysis of male infertility
112(1)
7.2.5 Molecular methods of genomic analysis of male infertility
113(2)
7.3 Genetic testing and molecular methods of embryonic analysis and monitoring during the in vitro fertilization process
115(3)
7.3.1 Invasive preimplantation genetic testing of the embryo in the in vitro fertilization process
115(1)
7.3.2 Noninvasive genetic testing of embryo quality for the in vitro fertilization process from the spent blastocyst medium
115(1)
7.3.3 Transcriptomic analyses in spent culture medium
116(2)
7.4 Omics methods of infertility
118(1)
Acknowledgment
119(1)
References
119(6)
8 Biotechnology approaches in developing novel drug-delivery systems
125(22)
Nisha Yadav
Neelam Sangwan
8.1 Introduction
125(1)
8.1.1 Novel drug-delivery system
125(1)
8.2 Drug-delivery mechanism
126(1)
8.2.1 Passive and active targeting
126(1)
8.3 Basic components of a drug-delivery system
127(1)
8.4 Different routes of a drug-delivery system
128(3)
8.4.1 Oral route
128(1)
8.4.2 Nasal and intranasal drug delivery
128(1)
8.4.3 Transdermal drug delivery
129(1)
8.4.4 Pulmonary drug delivery
130(1)
8.4.5 Colon-specific drug delivery
130(1)
8.4.6 Ophthalmic drug delivery
130(1)
8.4.7 Mucoadhesive drug delivery
130(1)
8.4.8 Osmotically controlled drug delivery
131(1)
8.5 Drug carriers
131(12)
8.5.1 Liposomes
132(1)
8.5.2 Polymers
133(1)
8.5.3 Nanoparticles
134(4)
8.5.4 Micelles
138(1)
8.5.5 Protein or peptide drug-delivery system
139(1)
8.5.6 Microspheres
140(1)
8.5.7 Dendrimers
140(1)
8.5.8 Implants
141(1)
8.5.9 Emulsions
141(1)
8.5.10 Microparticle-based lipids
142(1)
8.5.11 Herbal phytoconstituent-based novel drugs and their delivery systems
142(1)
8.6 Conclusions
143(1)
References
143(4)
9 Gene therapy and gene editing in healthcare
147(30)
Shailendra Dwivedi
Purvi Purohit
Abhimanyu Vasudeva
Manish Kumar
Ruchika Agrawal
Nishat Ahmed Sheikh
Radhieka Misra
Surekha Kishore
Sanjeev Misra
9.1 Introduction: gene therapy and gene editing
147(3)
9.1.1 Gene therapy
147(1)
9.1.2 Gene transfer strategy: delivery vehicle
148(2)
9.2 Gene-editing technologies
150(2)
9.2.1 Meganucleases
150(1)
9.2.2 Zinc-finger nucleases
150(1)
9.2.3 Transcription activator-like effector nucleases
150(1)
9.2.4 CRISPR-Cas9
151(1)
9.3 Clinical trials of gene therapy and gene editing (in vivo and ex vivo): an update
152(1)
9.4 Gene therapy and gene editing in diseases/disorders: current progress
152(15)
9.4.1 Gene therapy and gene editing in hemophilia
153(1)
9.4.2 Gene therapy and gene editing in cardiovascular disorders
153(1)
9.4.3 Gene therapy and gene editing in metabolic syndrome
154(1)
9.4.4 Gene therapy and gene editing in neurological disorders
154(1)
9.4.5 Gene therapy and gene editing in HIV infection
155(5)
9.4.6 Gene therapy and gene editing in various cancers
160(7)
9.5 Miscellaneous diseases and disorders
167(1)
9.5.1 Gene therapies in ophthalmic disease
168(1)
9.5.2 Gene therapy in dermatology
168(1)
9.6 Obstacles and ethical concerns
168(2)
9.6.1 Activation and delivery of gene
169(1)
9.6.2 Controlled gene expression
169(1)
9.6.3 Activation of immune response
169(1)
9.6.4 Improving efficiency of nuclease editing
169(1)
9.6.5 Safety issues
170(1)
9.7 Conclusions and future prospective
170(1)
Acknowledgments
170(1)
References
170(7)
10 Algae biotechnology for nutritional and pharmaceutical applications
177(18)
Mathiyazhagan Narayanan
Sabariswaran Kandasamy
Zhixia He
Shanmugam Hemaiswarya
Rathinam Raja
Isabel S. Carvalho
10.1 Introduction
177(2)
10.2 Food algae feature
179(3)
10.2.1 Protein
179(1)
10.2.2 Carbohydrates
179(2)
10.2.3 Pigments
181(1)
10.2.4 Polysaccharides
181(1)
10.2.5 Lipids
182(1)
10.2.6 Carotenoids
182(1)
10.2.7 Additional nutrients
182(1)
10.3 Fermenting algae
182(2)
10.3.1 Dairy and probiotic products
184(1)
10.4 Pharmaceutical algae feature
184(6)
10.4.1 Antioxidant, antiinflammatory, and antimicrobial activities
184(5)
10.4.2 Antitherapy activity
189(1)
10.4.3 Microalgae anticancer property
190(1)
10.4.4 Anticancer properties of macroalgae
190(1)
10.5 Future perspectives
190(1)
10.6 Conclusion
190(1)
Acknowledgments
191(1)
References
191(4)
11 Phage therapy: a promising approach to counter antimicrobial drug resistance
195(10)
Juliet Roshini Mohan Raj
Pallavi Bhat Ajakkala
Ballamoole Krishna Kumar
Vijaya Kumar Deekshit
Praveen Rai
11.1 Overview of antimicrobial drug resistance
195(1)
11.2 Phage therapy to counter antibacterial resistance
195(1)
11.3 Phages against antimicrobial resistance---an alternative strategy
196(1)
11.4 Mode of action of phage
196(1)
11.5 Journey of phage therapy
197(1)
11.6 Different approaches for phage therapy
198(1)
11.6.1 Single-phage therapy and polyphage therapy
198(1)
11.6.2 Phage combined with antibiotics
199(1)
11.6.3 Phage-derived enzymes as antimicrobials
199(1)
11.6.4 Engineered phage
199(1)
11.7 Strategies and recent advances in phage therapy
199(1)
11.8 Options for the administration of phage therapy
200(1)
11.9 Real-time use of phage therapy
200(1)
11.10 Upside and flipside of phage therapy
200(1)
11.11 Regulatory requirements
201(1)
11.12 Outstanding challenges in phage therapy
202(1)
11.13 Conclusion and future directions
202(1)
Acknowledgment
202(1)
References
202(3)
12 Biotechnology strategies for the development of novel therapeutics and vaccines against the novel COVID-19 pandemic
205(22)
Kenneth Lundstrom
12.1 Antiviral COVID-19 drugs
205(4)
12.2 Monoclonal antibodies against COVID-19
209(2)
12.3 Vaccines against COVID-19
211(9)
12.3.1 Inactivated and attenuated viruses
211(4)
12.3.2 Protein-and peptide-based vaccines
215(2)
12.3.3 Viral vector-based vaccine
217(1)
12.3.4 DNA-based vaccines
218(1)
12.3.5 RNA-based vaccines
219(1)
12.4 Conclusion
220(1)
References
220(7)
13 Applications of microbial omics in healthcare
227(22)
Fatima Shahid
Tahreem Zaheer
Hayeqa Shahwar Awan
Maaz Waseem
Amina Basheer
Amjad Ali
13.1 Introduction to microbial omics
227(2)
13.1.1 Microbial omics approaches
227(1)
13.1.2 Microbial omics data types
228(1)
13.2 Phylogenomics: inferring evolutionary relationships between microorganisms
229(2)
13.2.1 Phylogenomics
229(1)
13.2.2 Microbial evolution
230(1)
13.2.3 Tools for microbial phylogenomic analysis
230(1)
13.3 Metagenomics: concepts in reconstructing genomes from metagenomes
231(2)
13.3.1 Significance of human microbiome
231(1)
13.3.2 Metagenomic analysis
232(1)
13.3.3 Phylogenetic analysis
232(1)
13.3.4 Forensic analysis
232(1)
13.4 Applications of microbial omics in diagnosis
233(3)
13.4.1 Ribotyping
233(1)
13.4.2 Multilocus sequence typing
234(1)
13.4.3 Pulse-field gel electrophoresis
235(1)
13.4.4 Microarrays
235(1)
13.4.5 Next-generation sequencing
236(1)
13.4.6 Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry
236(1)
13.4.7 Protein as biomarkers
236(1)
13.5 Pan-genomics: comparative genomics in the era of omics data explosion
236(3)
13.5.1 Microbial pan-genome as tool to analyze pathogenic bacterial species
236(1)
13.5.2 Application of comparative microbial genomics and tools
237(1)
13.5.3 Comparative microbial genomics tools
238(1)
13.6 Therapeutic approaches employing microbial genomes and proteomes
239(2)
13.6.1 Drug target identification
239(1)
13.6.2 Vaccine development
240(1)
13.6.3 Success stories
240(1)
13.7 Conclusion
241(1)
13.8 Future prospects
241(1)
References
241(8)
14 Artificial intelligence applied to healthcare and biotechnology
249(10)
James Chapman
Vi Khanh Truong
Daniel Cozzolino
14.1 Introduction
249(1)
14.2 Data analytics
250(1)
14.3 Algorithms used in artificial intelligence applications
251(1)
14.4 Supervised and unsupervised classification methods
251(1)
14.5 Machine learning and deep learning
251(1)
14.6 Steps needed during the application of artificial intelligence
252(1)
14.6.1 Data preprocessing
252(1)
14.7 Analysis and interpretation of the data
252(1)
14.8 The need for validation
253(1)
14.9 Outliers, overfitting, and underfitting
254(1)
14.10 Interpretation
254(1)
14.11 The significance of the multidisciplinary approach
255(1)
14.12 Conclusion and future directions
255(1)
References
256(3)
15 Intellectual property rights in healthcare: an overview
259(6)
Shruti Dwivedi
Gautam Anand
Dinesh Yadav
15.1 Introduction
259(1)
15.2 Intellectual properties
260(1)
15.3 Rights protected under intellectual property laws
261(1)
15.4 Intellectual property right in healthcare
262(1)
15.4.1 Medical devices
263(1)
15.5 Chemical products and pharmaceutical drugs
263(1)
15.6 Healthcare information technology
263(1)
15.6.1 Medical and surgical methods
263(1)
15.6.2 Regenerative medicine
263(1)
15.7 Gene patents and personalized medicines
264(1)
15.8 Indian patent advanced search system
264(1)
15.9 Indian pharmaceutical industries and scope of patents
264(1)
15.10 Patent licensing and transfer of rights
265(1)
15.11 Conclusion
265(1)
References 265(2)
Index 267
Dr. Debmalya Barh is currently a Visiting Full Professor (Titular, Grade-E) in Bioinformatics and Precision Health at the Department of Genetics, Ecology, and Evolution, ICB, Federal University of Minas Gerais, Brazil and honorary scientist of the Institute of Integrative Omics and Applied Biotechnology (IIOAB), India. With over 20 years of experience, he has led academic, healthcare, molecular diagnostic, and bioinformatics industry endeavors. He works with more than 400 scientists from 100+ top ranked organizations across 40+ countries and has 220+ publications and a branded editor for 10+ cutting-edge omics related reference books. He is an expert in in precision/personalized health and integrative omics-based biomarker and target discovery in infectious and complex lifestyle diseases.
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