Biotechnology in Healthcare, Volume 1: Technologies and Innovations

Front Cover
Biotechnology in Healthcare, Volume 1
Copyright Page
Dedication
Contents
List of contributors
About the editor
Preface
1 Overview of healthcare biotechnology
1.1 Introduction
1.2 Genomics
1.2.1 Genetic screening and testing
1.2.2 Diagnosis of genetic disorders
1.2.2.1 Polymorphism-based molecular makers
1.2.2.2 Polymerase chain reaction-based methods
1.2.2.3 Array based methods
1.2.2.4 Sequencing and its advances for genomics
1.2.2.5 Whole exome sequencing and clinical genome exome sequencing for genomic diagnostic
1.2.3 Pharmacogenomics and epigenomics
1.2.4 Personalized medicine
1.3 Transcriptomics
1.3.1 Tools of transcriptomics
1.3.1.1 Expressed sequence tag
1.3.1.2 Serial analysis of gene expression and cap analysis of gene expression
1.3.1.3 Microarrays
1.3.1.4 RNA-seq
1.3.1.5 Real-time polymerase chain reaction
1.3.2 Transcriptomics in disease diagnosis
1.3.3 Transcriptome profiling in drug discovery
1.4 Proteomics
1.4.1 Tools and techniques in the proteomics-based study
1.4.1.1 Purification of protein
1.4.1.2 Analysis of proteomes
1.4.1.3 Characterization of proteins
1.4.1.4 Sequence analysis
1.4.1.5 Quantification of proteomes
1.4.1.6 Structural analysis
1.4.1.7 Bioinformatics analysis
1.4.2 Biomarker discovery
1.4.3 Drug development
1.5 Metabolomics
1.5.1 Tools and techniques in metabolomics study
1.5.1.1 NMR spectroscopy
1.5.1.1.1 One-Dimensional-NMR
1.5.1.1.2 Two-dimensional-NMR
1.5.1.2 Mass spectrometry
1.5.2 Metabolomics in treatment of cancer, neurological, and psychiatric disorders
1.5.2.1 Metabolomics in cancer studies
1.5.2.2 Metabolomics in neurological disorders
1.5.2.3 Metabolomics in psychiatric disorders
1.5.3 Individualized metabolomics
1.6 Conclusion
Acknowledgments
References
2 Three-dimensional printing in healthcare
2.1 Introduction
2.2 Three-dimensional printing technology (hardware and software)
2.3 Materials of three-dimensional printing
2.4 Three-dimensional printing in surgical planning and medical education
2.5 Three-dimensional printing in oral and maxillofacial surgery
2.6 Three-dimensional printing in orthopedics
2.7 Three-dimensional printing in neurosurgery
2.8 Bioprinting tissue and organ fabrication
2.9 Three-dimensional printing in pharmaceutical industry
2.10 Future of three-dimensional printing
2.10.1 Limitations of three-dimensional printings
2.11 Conclusion
References
3 Synthetic biology in healthcare: technologies and applications
3.1 Introduction
3.1.1 Cell-free systems and applications
3.2 Technologies for synthetic DNA, proteins, and organisms
3.2.1 Synthetic biology-based Doggybone DNA technology and its uses in vaccines and DNA-based gene therapy products
3.2.2 Development of linear dbDNA vaccine construct
3.3 Gen9 technology—microfluidic devices and methods for gene synthesis
3.3.1 DNA synthesis and scale up (BioFab platform)
3.3.2 Technologies for synthetic genomes
3.3.3 Synthetic biology to create an artificial membrane-binding protein
3.3.4 Pathway rewiring with adapters and scaffolds
3.3.5 Synthetic DNA for developing new antibiotics
3.3.6 Synthetic DNA for amino-acid replacement
3.3.7 Synthetic proteins technologies
3.3.8 Technologies to create synthetic organisms
3.3.9 Synthetic biology applications in diagnostics
3.4 Transcriptional, posttranslational, and hybrid biosensing and applications
3.4.1 Transcriptional biosensing
3.4.2 Posttranslational biosensing
3.4.3 Hybrid biosensing
3.5 Applications
3.5.1 Paper-based diagnostic
3.5.2 Synthetic biology applications for drug discovery and therapy
3.5.3 Drug-target identification (synthetic pathways and systems)
3.5.4 Drug discovery
3.5.5 Therapeutic treatment (synthetic biology devices)
3.5.6 Therapeutic delivery
3.6 Synthetic biology for creating living systems to produce small molecules, for instance, aspirin, that characteristicall...
3.6.1 CodeEvolver-like protein-engineering synthetic-biology platform to create unique enzymes as therapeutics
3.6.2 Chimeric antigen receptor
3.6.3 Synthetic genomes and vaccine design (SARS-CoV-2 and other viruses)
3.7 Living therapies—engineering microbes and bacteriophage to treat disease
3.7.1 Engineered bacteria (such as Salmonella) to deliver vaccines
3.7.2 Understanding disease mechanism
3.7.3 Synthetic biology-based pathway engineering for pharmaceutical production
3.7.4 Constructing biosynthetic pathways
3.7.5 Optimizing pathway flux
3.7.6 Programming novel functionality and materials
3.7.7 Chemical retrosynthesis and its future applications in healthcare
3.8 Future challenges and conclusions
Acknowledgment
References
4 Nanotechnology in healthcare: nanoparticles for diagnostic and therapy
4.1 Introduction
4.2 Classification and properties of nanoparticles
4.2.1 Gold nanoparticles
4.2.2 Magnetic nanoparticles
4.2.3 Quantum dots
4.2.4 Carbon nanostructures
4.2.4.1 Carbon nanotubes
4.2.4.2 Graphene and graphene oxide
4.2.5 Polymeric nanoparticles
4.3 Nanoparticle-based biosensors for medical diagnosis
4.3.1 Plasmonic biosensors
4.3.2 QD-based biosensors
4.3.3 Carbon nanostructure-based biosensors
4.4 Nanoparticle-based therapy and imaging
4.4.1 Targeted drug delivery
4.4.2 Bioimaging and photothermal therapy
4.4.3 Nanoparticles in the clinic
4.5 Conclusion and future perspective
References
5 Analysis and applications of sequencing in healthcare
5.1 Introduction
5.2 Method of de-novo and reference-based DNA sequencing
5.3 Generation of DNA reads
5.4 Quality assessment of reads
5.5 Trimming of DNA reads
5.6 Mapping of DNA reads
5.7 Assembly
5.8 Analysis of DNA sequences for marker-based surveillance of diseases
5.9 Phylomedicine of genetic diseases
5.10 Method of de-novo and reference-based RNA sequencing
5.11 Generation of short RNA reads and quality assessment
5.12 Trimming of RNA reads
5.13 Mapping of RNA reads
5.14 Assembly of RNA reads
5.15 Analysis of differential expression of genes in diseases states and in prognosis of disease
5.16 Analysis of alternative splicing of genes and gene fusion in disease states
5.17 Analysis of long noncoding RNA and its relevance to disease
5.18 Gene coexpression analysis and annotation of TF-TFBS and gene regulatory network
5.19 Method of DAP-sequencing and genome-wide annotation of cistrome
5.20 Analysis of DAP sequences and its application in healthcare
5.21 Genome-wide mapping of TF-TFBS and visualization of gene-regulatory network
References
6 Innovative technologies in precision healthcare
6.1 Defining precision and personalized medicine
6.1.1 Assessing emerging technologies for personalized precision medicines’ clinical trials
6.1.2 Biosensors in personalized medicine
6.1.3 Omics in precision healthcare
6.1.4 Engineering precision medicine technology and platforms
6.1.4.1 Processing of digital image data
6.1.4.2 Processing of sequenced data
6.1.4.3 Processing of numerical data
6.1.4.4 Development platforms
6.2 Databases applications in precision healthcare
6.2.1 Microbiome databases
6.2.2 Databases for protein-coding genes
6.2.3 Databases for noncoding genes
6.2.4 Databases used for annotation of human genetic variants and rearrangements
6.2.5 Prediction of gene function
6.3 Bioengineering, machine learning for personalized medicine
6.3.1 Principle of machine learning
6.3.2 Why machine learning?
6.3.3 Supervised machine learning
6.3.4 Unsupervised machine learning
6.3.5 Reinforcement learning
6.3.6 Online learning
6.3.7 Recommendations in machine learning
6.3.8 Testing and verification
6.4 Application of bioinformatics machine learning and in-depth data analysis
6.4.1 Get the data
6.4.2 Explore and prepare data
6.4.3 Feature selection with decision trees
6.4.4 Feature selection by analysis
6.4.5 Analysis with edgeR or DESeq2
6.4.6 Pickup machine learning models
6.4.7 Evaluate machine learning model
6.4.8 Workflow for processing readings in RNA-seq
6.4.8.1 Preprocessing
6.4.8.2 Mapping
6.4.8.3 Analysis
6.5 BIG DATA
Acknowledgments
References
7 Omics applications in reproductive medicine
7.1 Genetic testing and molecular methods of female infertility
7.1.1 Molecular methods of transcriptome analysis in female infertility
7.1.2 Methods of metabolomics analysis of female infertility
7.1.3 Methods of proteomics analysis of female infertility
7.1.4 Molecular methods of microbial analysis of female infertility
7.1.5 Molecular methods of genomic analysis of female infertility
7.2 Genetic testing and molecular methods of male infertility
7.2.1 Molecular methods of transcriptome analysis of male infertility
7.2.2 Methods of metabolomics analysis of male infertility
7.2.3 Molecular methods of proteomic analysis of male infertility
7.2.4 Molecular methods of microbial analysis of male infertility
7.2.5 Molecular methods of genomic analysis of male infertility
7.3 Genetic testing and molecular methods of embryonic analysis and monitoring during the in vitro fertilization process
7.3.1 Invasive preimplantation genetic testing of the embryo in the in vitro fertilization process
7.3.2 Noninvasive genetic testing of embryo quality for the in vitro fertilization process from the spent blastocyst medium
7.3.3 Transcriptomic analyses in spent culture medium
7.4 Omics methods of infertility
Acknowledgment
References
8 Biotechnology approaches in developing novel drug-delivery systems
8.1 Introduction
8.1.1 Novel drug-delivery system
8.2 Drug-delivery mechanism
8.2.1 Passive and active targeting
8.3 Basic components of a drug-delivery system
8.4 Different routes of a drug-delivery system
8.4.1 Oral route
8.4.2 Nasal and intranasal drug delivery
8.4.3 Transdermal drug delivery
8.4.4 Pulmonary drug delivery
8.4.5 Colon-specific drug delivery
8.4.6 Ophthalmic drug delivery
8.4.7 Mucoadhesive drug delivery
8.4.8 Osmotically controlled drug delivery
8.5 Drug carriers
8.5.1 Liposomes
8.5.1.1 Structure of liposomes
8.5.1.2 Liposome preparation and transportation
8.5.2 Polymers
8.5.3 Nanoparticles
8.5.3.1 Different types of nanoparticles
8.5.3.1.1 Polymeric nanoparticles
8.5.3.1.2 Solid lipid nanoparticles
8.5.3.1.3 Nanostructured lipid carriers
8.5.3.1.4 Inorganic nanoparticles
8.5.3.1.5 Inorganic nonmetallic nanomaterials
8.5.3.1.6 Biopolymeric nanoparticles
8.5.3.1.6.1 Chitosan
8.5.3.1.6.2 Alginate
8.5.3.1.6.3 Xanthan gum
8.5.3.1.7 Protein and polysaccharide nanoparticles
8.5.3.1.8 Glycosylated nanoparticles
8.5.4 Micelles
8.5.4.1 Polymeric micelles
8.5.5 Protein or peptide drug-delivery system
8.5.6 Microspheres
8.5.7 Dendrimers
8.5.8 Implants
8.5.9 Emulsions
8.5.10 Microparticle-based lipids
8.5.11 Herbal phytoconstituent-based novel drugs and their delivery systems
8.6 Conclusions
References
9 Gene therapy and gene editing in healthcare
9.1 Introduction: gene therapy and gene editing
9.1.1 Gene therapy
9.1.1.1 Germinal gene therapy
9.1.1.2 Somatic gene therapy
9.1.2 Gene transfer strategy: delivery vehicle
9.1.2.1 Viral vectors: gene therapy
9.1.2.1.1 Retroviral vectors
9.1.2.1.2 Adenovirus-based vectors
9.1.2.2 Nonviral vectors
9.2 Gene-editing technologies
9.2.1 Meganucleases
9.2.2 Zinc-finger nucleases
9.2.3 Transcription activator-like effector nucleases
9.2.4 CRISPR-Cas9
9.3 Clinical trials of gene therapy and gene editing (in vivo and ex vivo): an update
9.4 Gene therapy and gene editing in diseases/disorders: current progress
9.4.1 Gene therapy and gene editing in hemophilia
9.4.2 Gene therapy and gene editing in cardiovascular disorders
9.4.2.1 Angiogenic gene therapy
9.4.3 Gene therapy and gene editing in metabolic syndrome
9.4.4 Gene therapy and gene editing in neurological disorders
9.4.4.1 Parkinson’s disease
9.4.4.2 Alzheimer’s disease
9.4.5 Gene therapy and gene editing in HIV infection
9.4.5.1 Genetic approaches to inhibit HIV replication
9.4.5.2 Trans dominant negative proteins
9.4.5.2.1 RevM10: a Rev trans dominant negative protein
9.4.5.2.2 Tat trans dominant negative proteins
9.4.5.2.3 Vif trans dominant negative proteins
9.4.5.2.4 Gag-based trans dominant negative proteins
9.4.5.3 Single-chain antibodies (intrabodies)
9.4.5.4 Endogenous cellular proteins as anti-HIV agents
9.4.5.5 Nucleic acid-based gene therapy approaches: RNA decoys
9.4.5.6 Antisense DNA and RNA
9.4.5.7 Ribozymes (catalytic antisense RNA)
9.4.5.8 DNA vaccines
9.4.5.9 HIV-specific cytotoxic T lymphocytes
9.4.6 Gene therapy and gene editing in various cancers
9.4.6.1 Hematological malignancy
9.4.6.1.1 Targeting gene fusion expression in acute lymphoblastic leukemia with chromosomal rearrangements
9.4.6.2 Oral cancer
9.4.6.2.1 Gene addition therapy
9.4.6.2.2 Antisense RNA and ribozymes-based trials
9.4.6.3 Breast cancer
9.4.6.3.1 Gene replacement strategies
9.4.6.3.2 Antisense strategy
9.4.6.3.3 RNA interference therapy
9.4.6.3.4 Growth receptors strategies
9.4.6.3.5 Suicide gene therapy
9.4.6.4 Ovarian cancer
9.4.6.4.1 Tumor suppressor gene therapy
9.4.6.4.2 Onco-factor inhibition strategies
9.4.6.4.3 Suicide gene therapy
9.4.6.4.4 Antiangiogenic gene therapy
9.4.6.4.5 Oncolytic virotherapy
9.4.6.5 Lung cancer
9.4.6.5.1 Gene therapy preclinical and clinical trials
9.4.6.6 Prostate cancer
9.4.6.6.1 Tumor suppressor gene therapy
9.4.6.6.2 Suicide gene therapy
9.4.6.6.3 Immunomodulatory gene therapy
9.4.6.6.4 Oncolytic virus therapy
9.5 Miscellaneous diseases and disorders
9.5.1 Gene therapies in ophthalmic disease
9.5.2 Gene therapy in dermatology
9.6 Obstacles and ethical concerns
9.6.1 Activation and delivery of gene
9.6.2 Controlled gene expression
9.6.3 Activation of immune response
9.6.4 Improving efficiency of nuclease editing
9.6.5 Safety issues
9.7 Conclusions and future prospective
Acknowledgments
References
10 Algae biotechnology for nutritional and pharmaceutical applications
10.1 Introduction
10.2 Food algae feature
10.2.1 Protein
10.2.2 Carbohydrates
10.2.3 Pigments
10.2.4 Polysaccharides
10.2.5 Lipids
10.2.6 Carotenoids
10.2.7 Additional nutrients
10.3 Fermenting algae
10.3.1 Dairy and probiotic products
10.4 Pharmaceutical algae feature
10.4.1 Antioxidant, antiinflammatory, and antimicrobial activities
10.4.2 Antitherapy activity
10.4.3 Microalgae anticancer property
10.4.4 Anticancer properties of macroalgae
10.5 Future perspectives
10.6 Conclusion
Acknowledgments
References
11 Phage therapy: a promising approach to counter antimicrobial drug resistance
11.1 Overview of antimicrobial drug resistance
11.2 Phage therapy to counter antibacterial resistance
11.3 Phages against antimicrobial resistance—an alternative strategy
11.4 Mode of action of phage
11.5 Journey of phage therapy
11.6 Different approaches for phage therapy
11.6.1 Single-phage therapy and polyphage therapy
11.6.2 Phage combined with antibiotics
11.6.3 Phage-derived enzymes as antimicrobials
11.6.4 Engineered phage
11.7 Strategies and recent advances in phage therapy
11.8 Options for the administration of phage therapy
11.9 Real-time use of phage therapy
11.10 Upside and flipside of phage therapy
11.11 Regulatory requirements
11.12 Outstanding challenges in phage therapy
11.13 Conclusion and future directions
Acknowledgment
References
12 Biotechnology strategies for the development of novel therapeutics and vaccines against the novel COVID-19 pandemic
12.1 Antiviral COVID-19 drugs
12.2 Monoclonal antibodies against COVID-19
12.3 Vaccines against COVID-19
12.3.1 Inactivated and attenuated viruses
12.3.2 Protein- and peptide-based vaccines
12.3.3 Viral vector-based vaccine
12.3.4 DNA-based vaccines
12.3.5 RNA-based vaccines
12.4 Conclusion
References
13 Applications of microbial omics in healthcare
13.1 Introduction to microbial omics
13.1.1 Microbial omics approaches
13.1.2 Microbial omics data types
13.1.2.1 Genomics
13.1.2.2 Transcriptomics
13.1.2.3 Proteomics
13.1.2.4 Interactomics
13.1.2.5 Metabolomics
13.2 Phylogenomics: inferring evolutionary relationships between microorganisms
13.2.1 Phylogenomics
13.2.2 Microbial evolution
13.2.3 Tools for microbial phylogenomic analysis
13.3 Metagenomics: concepts in reconstructing genomes from metagenomes
13.3.1 Significance of human microbiome
13.3.2 Metagenomic analysis
13.3.3 Phylogenetic analysis
13.3.4 Forensic analysis
13.4 Applications of microbial omics in diagnosis
13.4.1 Ribotyping
13.4.2 Multilocus sequence typing
13.4.3 Pulse-field gel electrophoresis
13.4.4 Microarrays
13.4.5 Next-generation sequencing
13.4.6 Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry
13.4.7 Protein as biomarkers
13.5 Pan-genomics: comparative genomics in the era of omics data explosion
13.5.1 Microbial pan-genome as tool to analyze pathogenic bacterial species
13.5.2 Application of comparative microbial genomics and tools
13.5.2.1 Gene identification
13.5.2.2 Regulatory motif discovery
13.5.2.3 Target-based drug design
13.5.2.4 Other applications of comparative genomics
13.5.3 Comparative microbial genomics tools
13.6 Therapeutic approaches employing microbial genomes and proteomes
13.6.1 Drug target identification
13.6.2 Vaccine development
13.6.3 Success stories
13.7 Conclusion
13.8 Future prospects
References
14 Artificial intelligence applied to healthcare and biotechnology
14.1 Introduction
14.2 Data analytics
14.3 Algorithms used in artificial intelligence applications
14.4 Supervised and unsupervised classification methods
14.5 Machine learning and deep learning
14.6 Steps needed during the application of artificial intelligence
14.6.1 Data preprocessing
14.7 Analysis and interpretation of the data
14.8 The need for validation
14.9 Outliers, overfitting, and underfitting
14.10 Interpretation
14.11 The significance of the multidisciplinary approach
14.12 Conclusion and future directions
References
15 Intellectual property rights in healthcare: an overview
15.1 Introduction
15.2 Intellectual properties
15.3 Rights protected under intellectual property laws
15.4 Intellectual property right in healthcare
15.4.1 Medical devices
15.5 Chemical products and pharmaceutical drugs
15.6 Healthcare information technology
15.6.1 Medical and surgical methods
15.6.2 Regenerative medicine
15.7 Gene patents and personalized medicines
15.8 Indian patent advanced search system
15.9 Indian pharmaceutical industries and scope of patents
15.10 Patent licensing and transfer of rights
15.11 Conclusion
References
Index
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