Translational Biotechnology: A Journey from Laboratory to Clinics

By Yasha Hasija

Translational Biotechnology: A Journey from Laboratory to Clinics presents an integrative and multidisciplinary approach to biotechnology to help readers bridge the gaps between fundamental and functional research. The book provides state-of-the-art and integrative views of translational biotechnology by covering topics from basic concepts to novel methodologies. Topics discussed include biotechnology-based therapeutics, pathway and target discovery, biological therapeutic modalities, translational bioinformatics, and system and synthetic biology. Additional sections cover drug discovery, precision medicine and the socioeconomic impact of translational biotechnology. This book is valuable for bioinformaticians, biotechnologists, and members of the biomedical field who are interested in learning more about this promising field.

• Explains biotechnology in a different light by using an application-oriented approach
• Discusses practical approaches in the development of precision medicine tools, systems and dynamical medicine approaches
• Promotes research in the field of biotechnology that is translational in nature, cost-effective and readily available to the community

• Language: English
• Publisher: Academic Press
• Release date: Jan 17, 2021
• ISBN: 9780128219737

Book preview

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Preface

Yasha Hasija

The advancements in the field of biotechnology have been monumental and the pace thereof, exponential. However, the same is not paralleled in the clinical setting. The lack of adequate translation of basic biomedical research into clinical applications has been a matter of huge concern for the entire clinical scientific community. Therefore, there is a need to achieve congruence in both, so that the work done in research laboratories gets percolated into the real-time medical practice.

This void has led to the emergence of an exciting field of bench to bedside translational research, so that the last man in the queue, that is, the patient, gets benefitted. This book Translational Biotechnology: A journey from laboratory to the clinics is a sincere effort toward understanding the steps involved in translating path-breaking innovative research and emerging scientific insights to reaching the patients, and in the process, creating new therapies, preventing, diagnosing and treating diseases, and improving health and living.

The book, inter alia, is aimed at transferring fundamental biological discoveries and technologies from the research laboratories into patient care, in the quest for effective healthcare. It attempts to traverse the long journey from bench work to healthcare reforms and also tries to address the obstacles, low success rates, failures, and challenges in the complex voyage.

In this book, we string together contributions from internationally acclaimed authors from various domains of biotechnology to offer unique insights in their respective fields of expertise. It will take the readers through several facets of translational research in biotechnology with illustrative examples. The introductory sections of the book introduce advanced biotechnology principles and processes in disease studies. This section emphasizes technologies that lead to or assist in the discovery of better clinical outcomes. It is hoped that it will shape the understanding of critical processes in the flow from basic sciences to practical applications in the clinical setting, via translational studies and clinical trials. The book also discusses the advancements in devices, biologics, vaccines, and several biological modalities, as an introduction to biotechnology products that are being used in therapy.

The subsequent sections deal with translational approaches in newer disciplines of biotechnology, like bioinformatics, systems biology, and synthetic biology. It discusses practical approaches in the development of personalized medicine, clinical systems, and translational medicine. It also outlines future research prospects of the bench to bedside approach.

The conclusion section is one of its kind that gives the readers a birds-eye view of the socioeconomic aspects associated with translational biotechnology. The goal is to make the readers aware of the feasibility of carrying out translational research, its availability to the public, and the impact caused by discoveries made in the laboratory. It discusses the technological and monetary challenges faced in developing and underdeveloped countries in carrying out translational research, and ways to overcome them. It also deals with the legal and ethical aspects of translational biotechnology.

The goal of the book is to provide in a lucid form, the research in the field of biotechnology that is translational in nature, is cost-effective, and readily available for use. I sincerely hope that the readers will benefit from this comprehensive book, which will further inspire and encourage them to adopt such practices in their research work, oriented toward clinical applications.

Every book is an embodiment of collective effort. I express my gratitude to all the contributors for delivering such insightful compilations of their respective areas of research, and the valuable input provided by the reviewers. I am indebted to the entire team at Elsevier for being in close collaboration at various stages for bringing out this book and ensuring a smooth sailing publication process.

Section 1

Introduction to translational biotechnology

Outline

Chapter 1 Translational biotechnology: A transition from basic biology to evidence-based research

Chapter 1

Translational biotechnology: A transition from basic biology to evidence-based research

Debleena Guin¹, ², Sarita Thakran¹, ³, Pooja Singh¹, ³, S. Ramachandran², ³, Yasha Hasija⁴ and Ritushree Kukreti¹, ³,    ¹1Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology (IGIB), Council of Scientific and Industrial Research (CSIR), Delhi, India,    ²2G N Ramachandran Knowledge Centre, Council of Scientific and Industrial Research (CSIR)—Institute of Genomics and Integrative Biology (IGIB), Delhi, India,    ³3Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India,    ⁴4Department of Bioinformatics, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi, India

Abstract

With the advent of DNA sequencing technology that led to the human genome project, there was an explosion of big data in the field of biomedical sciences. The successful completion of the human genome project led to the emergence of numerous fields for data-driven discovery like genomics, proteomics, and bioinformatics per se. It was expected that the human genome information would reveal essential insights into the disease biology and revolutionize the field of medical sciences. It has been more than a decade since this important project. However, the impact of fundamental biological discoveries made in the laboratories is not reaching the clinical setting at a pace that was expected. Ever since, scientists have made innumerable attempts to decode the accumulated genetic information but are encountered with new challenges like complex disorders, epigenetics, and multifactorial diseases. So in order to bridge this gap, the focus of biomedical researchers has shifted from trying to decode the human genome in its entirety to translating only clinically relevant biological information. The change in focus has redirected the field of biotechnology toward what we call translational research, which is the buzzword of the era. By definition, it is an interdisciplinary branch of the biomedical field supported by three main pillars: bench-side, bedside, and community, that is, to analyze fundamental biological data with an explicit goal of affecting clinical care and ultimately the community as a whole. Stemming from translational biotechnology came system biology, biological engineering, pharmacogenomics, cheminformatics, molecular medicine, and so on. This chapter begins with a conceptual overview of this field and then introduces some of the key methods for translational research, its different stages implemented in integrative biology, overcoming its challenges with solutions, and the applications of multiomics platforms. Combining such biomedical information from different layers of omics data can ultimately help us in revealing the landscape of molecular mechanisms involved in highly prevalent complex diseases like cancer, cardiovascular, and metabolic diseases.

Keywords

Translational biotechnology; integrative biology; translational research; evidence-based medicine; implementation; knowledge translation

Outline

Outline

1.1 Introduction 4

1.1.1 Background and emergence of the field 4

1.2 The phases of translational research 5

1.3 Challenges to solutions 6

1.4 Applications 9

1.4.1 Drug development 12

1.4.2 Nanomedicine 16

1.4.3 Gene therapy 17

1.4.4 Precision medicine and biomarker development 19

1.4.5 Microbial engineering for bio-therapeutics 19

1.4.6 Application of big data and translational bioinformatics 19

1.5 Conclusion and future directions 21

1.6 Highlights 21

Acknowledgment 22

Conflict of Interest 22

References 22

1.1 Introduction

1.1.1 Background and emergence of the field

Biotechnology is an advanced field of biology that exploits technology to make and disseminate biological discoveries for human benefit. Biotechnology has a broad spectrum of applications, spanning from industry to agriculture, manufacturing of food, chemicals, probiotics, pharmaceuticals, and the list goes on. One of the primary focuses of biotechnology has been improving healthcare, and we have come a long way in that endeavor. Like, for instance, from microbial bioconversions for therapeutic use to vaccine development, drug discovery and development, clinical trial design, community medicine, personalized therapy, clinical informatics, etc. Through the course of time and with the accumulation of substantial biological information, biotechnology has progressed toward specific application-based research, which is the need of the decade. It has made a gateway for a new approach to research called translational research. The word translation as defined by the National Institute of Health funded National Center for Advancing Translational Sciences (NCATS), is the process of turning observations in the laboratory, clinic, and community into interventions that improve the health of individuals and the public—from diagnostics and therapeutics to medical procedures and behavioral changes (US Department of Health & Human Service, 2020). Moreover, the emerging field of translational science is focused on investigating the scientific and operational principles underlying each step of the translational process. Through the basic knowledge of human physiology in disease and how the intervention (say, a drug or a therapy) is affecting the diseases will expedite the translational process toward a focused science-driven, predictive, and effective drug development for the prevention and treatment of all diseases.

With the availability of unlimited human biological data, this new subsidiary field of translational biotechnology is focused, distinct, and unique in operation, application, and implementation. While unique challenges in different territories hover, this field also provides us with unprecedented opportunities to widen the spectrum of biomedical enterprise. Comprising many disciplines of science and operations, including biology, chemistry, informatics, pharmaceutical, engineering, medicine, and public health management, translational biotechnology defines the scientific and operational relationships among these fields, builds bridges, and creates a transdisciplinary network for active development and deployment of interventions that benefit public health (Westfall, Mold, & Lyle, 2007).

In this chapter, we introduce the key threads of translational research. We, first, provide a conceptual overview of the understanding in this field, the different stages in the broad spectrum of the translational research pipeline, followed by the numerous scientific and regulatory roadblocks in this field and their potential solution to speed up the process. Finally, summing up the varied applications of translational biotechnology in clinical sciences and public health. From the translational application in drug discovery and development, precision medicine and biomarker discovery, gene therapy, bio-therapeutic, and application of artificial intelligence (AI) in disease diagnosis and other clinical research. With an effective integrated network of robust multidisciplinary effort between patients, researchers, and healthcare providers within a system, can yield well-rounded and competent teamwork who can ultimately commit to improved community health and healthcare costs.

1.2 The phases of translational research

The broad spectrum of translational research has been categorized into different phases for a convenient transition from basic research finding to its application mode for clinical implementation. This integrative research effort has been designated into four steps: T1, T2, T3, and T4 (Lorenzi, 2011). The steps in outcome-based clinical research follow: from basic scientific laboratory work based on understanding the human physiology and application of medicinal chemistry to preclinical studies to validate the clinical finding in vitro/in vivo model systems followed by clinical trial studies for implication for practice and its overall effect. Ultimately, the research findings are used for implications in community-based health benefits in clinical use. The final crucial step in clinical research is the delivery of recommended care to the right patient at the right time, resulting in improved patient health. It may be with improved prognosis, diagnostic tests, therapy or therapy adherence, and treatment outcome for use in clinical practice. At each of the transitions between each stage, there is a step for translational output. The spectrum of translational research is not linear or unidirectional; each stage builds upon each other and moves upward in the pyramid with a larger impact and greater population coverage. At all stages of the spectrum, according to NCATS, new approaches are developed, demonstrating their usefulness and disseminating the findings.

Every stage of the translational research spectrum is based on research findings that derive from basic sciences. At T1, insights gained from the fundamental scientific discovery are accumulated that gives a proof of concept study with controlled experimental conditions and, therefore, their outcome. T2 provides clinical insights from study findings. From the previous stage, where researchers develop models to test interventions to understand the pathophysiology of the disease and, ultimately, its treatment. Such testing/data is used to elaborate clinical/physiological insights. Such testing is performed using in vitro models (animal tissue-specific cell lines) or in vivo model organisms like mouse, rat, drosophila, zebrafish, etc. and in silico-based computer-assisted simulation models of drug, device, or diagnostic interactions within living systems. This step includes preclinical validation studies, early phase I, and II trials. Subsequently, practice-based research includes testing interventions for human safety and effectiveness in patients with or without the disease, behavioral, and observational studies and outcomes and health services research at the T3 phase. The confirmed evidence from human subjects is introduced and disseminated into a patient care setting for implementation and deployment of clinical discovery. This step is called T4, and it is the final achievable goal, where the developed intervention is used for improving public health (Choi, Tubbs, & Oskouian, 2018). In this stage of translation, researchers validate the clinical outcome findings in an entire population to determine the burden of the diseases and clinical efforts to prevent it, diagnose, and treat them (US Department of Health & Human Service, 2020). These steps have been elaborated in Fig. 1.1. Detailed phases and their translational steps in the pipeline for biomarker development for precision medicine in warfarin dosing have been described as an example in Table 1.1.

Figure 1.1 Phases of translational research.

Table 1.1

CYP2C9, Cytochrome P450 family two subfamily C member 9; CYP4F2, cytochrome P450 family four subfamily F member 2; INR, international normalized ratio; PGx, pharmacogenomics; PK/PD, pharmacokinetic/pharmacodynamic; US FDA, the United States Food and Drug Administration; VKORC1, vitamin K epoxide reductase complex subunit 1.

1.3 Challenges to solutions

Translation of basic scientific discoveries to clinical applications, and finally to improvements of public health, has emerged as an important objective in biomedical research, and its essential role has been emphasized for more than three decades. During this period, much advancement was made, but despite these efforts, we are unable to create the balance between the advances made in biomedical sciences and its translatability into tangible health benefits. Basic scientific discoveries made in laboratory settings and its clinical implementation are like a bank of a vast river, a swimmer had to swim all the way through it to reach the other side facing many hurdles. To bridge this gap, there is a need to understand the issues in translational research better and to look for potential solutions (Harvard Catalyst Clinical Research Center, 2020) (Fig. 1.2).

Figure 1.2 A glance at translational research on cancer in the past 5 years.

The vast majority of studies that give exciting and impressive results in preclinical studies usually fail at its nascent stage of rigorous target validation and do not reach up to clinical development. Issues and challenges that might account for differences between marked success in deciphering the mechanism, pathogenesis, and treatment of diseases in preclinical studies, and limiting success rate for translating most of these discoveries from bench to bedside include lack of proper validation of published findings, reproducibility problem, and lack of predictive efficacy and safety (Yoichi, 2019). The main causes of these issues include fewer studies conducted to support any research finding for application and lack of replicability of data between different studies due to different study designs. Other factors like sampling criteria, genetically diverse subjects included in studies, controlled experimental conditions, and recruitment of samples with specific phenotypic characteristics, pitfalls in animal experimentation, different statistical methods used, and overinterpretation of data (Collins & Tabak, 2014). Generally, academic clinical trial units conduct innumerable clinical studies on human subjects but report only the most promising results from studies that have favorable outcomes, and this leads to a lack of reproducibility of results. To enhance reproducibility and transparency of studies conducted, there is a need to discuss such challenges plaguing preclinical research across the globe in different populations to provide constructive guidance for therapy and recommend reporting standard clinical design. Potential solutions to tackle this problem include calls for random assignment of animals, blinding of preclinical treatment groups, more rigorous sample and effect size calculations, and formal rules for the handling of data involving outliers, prespecified primary and secondary endpoints, and replication of key experimental findings, development of novel methods to predict safety, conduction of Phase 0, and investigational exploratory trials to confirm the mode of action, validate biomarkers (Landis et al., 2012).

The major non-scientific challenges that need to be addressed are to minimize the gaps between scientific discovery and their application in the clinical setting, which should be prioritized in advance by funders/research organizations. Other non-scientific factors include cultural differences between clinicians and basic scientists as scientists involved in basic science research have less exposure to the clinical environment and the lack of laboratory research experience in clinicians. Additionally, communication gap, the difference in work attitude and reward system of both groups, like academic researchers involved in translational research generally do not have proper incentives to channelize the movement of science, as their career trajectory is dependent on high-impact publications, funding, and patents, also add to the problem. This gap needs to be filled by coupling of hospitals and research-oriented scientific institutes, to define a separate field of translational research with a multidisciplinary viewpoint, and institutions should ensure and make new guidelines to properly evaluate and recognize the contributions made by scientists in translational research (Homer-Vanniasinkam & Tsui, 2012).

The financing gap for translational research is also widening. Traditional investors involved in translational research are becoming increasingly risk-averse in the face of escalating challenges in the early stages of the drug development process. To counteract this trend, the medical research field needs to increase the field of promising research ventures that also attract investment opportunities by modifying both the research management process as well as current financing methods (MIL Report, 2012). Besides this lack of resources and scattered infrastructure, lack of skilled investigators with specific expertise and well-aware participants for the study, time taking, and costly phases of translational research, lack of collaborations and partnerships between clinics, researchers, and industries, conflict of interest, ethical, and various regulatory issues, right to privacy and incompatible databases adds to the challenges which slow down the pace of bench to bedside research. Potential solutions for these challenges include building national-level clinical and translational research capability, collaborative efforts, like a coherent partnership between academic and industrial research, where academia delivers skilled and trained researchers and industry exploits those human resource for the upliftment of translational activities for mankind. Cost reduction in clinical investigations, proper scrutiny of ethical and social issues should be looked into prior to the study as per the clinical set-up, and study design. An overview of obstacles and their potential solutions relevant to translational research are presented in Table 1.2.

Table 1.2

BMCTR, Brown's Masters in Clinical and Translational Research; CAHSS, Canadian Academic Health Science Systems; GTAC, Gene Therapy Advisory Committee; IRAS, Integrated Research Application System; MCGS, Mayo Clinic Graduate School; MHRA, Medicines and Healthcare Regulatory Agency; NIGB, the National Information Governance Board; NIH, National Institute of Health; NIHR, National Institute of Health Research; THSTI, Translational Health Science and Technology Institute.

1.4 Applications

Regardless of many gaps in translating every research avenue to clinical importance, there have been several successful attempts. Biotechnology has a significant hand in translating clinical research. Initially, biotechnology was thought of being limited to the development of recombinant DNA (rDNA) technology and the production of recombinant proteins such as insulin. With advancements in technology, this field has evolved from the synthesis of proteins to biopharmaceutical discovery. Now, biotechnology has contributed to the development of gene therapy, immunotherapy, and personalized medicine. It includes synthesis of monoclonal antibodies (mAb), antisense strands, enzymes, cancer vaccines, novel drug discovery, biochips, microarray, and so on (Avidor, Mabjeesh, & Matzkin, 2003). With the emergence of these biotechnological products, there has been a rapid pace of development in healthcare. The Food and drug administration (FDA) has approved many of these drugs and therapies for diagnostic purposes. Products yielded from research in this field have been successful in meeting the demands of the pharmaceutical industry and healthcare like products based on ligand–receptor interaction, signal transduction, and cell signaling in healthy and diseased states. Hence, research in biotechnology leads to the development of therapeutics and a better understanding of genomics, proteomics, or rather the broader multiomics landscape for physiological advancements. Glimpses of applications of translational biotechnology are in varied fields as represented in Fig. 1.3 and are detailed below. Glimpse of applications of translational biotechnology are in varied fields as represented in Fig. 1.2 and are detailed below.

Figure 1.3 Translational biotechnology in human healthcare.

1.4.1 Drug development

Drug development is one of the foremost and most extensive applications of translational biotechnology, which requires three important steps. First is, identification of protein target, followed by the generation of compounds that react with the target site in the desired manner, and last is the innovative delivery mechanism of a drug into target tissue or cell. It is a strenuous and time-consuming process. In order to escalate the process of drug discovery, in silco approach has been used. Various software and tools are used for identification of a target, selection, and optimization of a lead molecule and to analyze the pharmacokinetic and pharmacodynamics properties like absorption, distribution, metabolism, excretion, and toxicity of a lead molecule (Goyal, Jamal, Grover, & Shanker, 2018). For example, to study the dissolution and disintegration rate of drug, DDDPlus (Dose Disintegration and Dissolution Plus) software is used, and to simulate the pharmacokinetics and pharmacodynamics properties in humans and animals, GastroPlus software is used. For the prediction of ligand interaction and molecular dynamics, Autodock, Schrodinger, and GOLD software are used. For building molecular models and predicting structural activity relationships, Maestro, Sanjeevini, and ArgusLab software are used. Discovery Studio Visualizer, and QSARPro software are used for viewing and analyzing protein data. MARS (Multimodal Animal Rotation System) software is used for tracking nanoparticle, delivery, and enzyme activity study. Hence, these softwares are used to assist the drug designing and development process (Jamkhande, Ghante, & Ajgunde, 2017).

Biotechnology advancement has been going on all of these fronts, and new genes and new protein targets are being investigated for therapeutic purposes. This field has flourished more after the completion of the human genome project. However, the human genome project provided insights on genetic makeup and can be used for understanding protein architecture for identifying novel drug targets leading to the generation of new protein target intervention. In the past, mostly peptides were used as drugs that could block specific pathways underlying a disease. Nowadays, different classes of drugs have emerged in addition to protein drugs, like therapeutic enzymes, hormones, mAb, cytokines, gene therapy, and antisense drugs that are discussed in detailed in the following sections.

1.4.1.1 Protein drugs

Protein drugs are classified based on the mode of action. Some of the most common proteins are recombinant human proteins (for instance, insulin, growth hormone, and erythropoietin), and several others are mAb [for instance, Remicade (infliximab; Johnson & Johnson, Kenilworth, NJ, United States), Rituxan (rituximab; Genentech; S. San Francisco, United States), and Erbitux (cetuximab; ImClone, New York, United States)]. Many others that are primarily manufactured are viral or bacterial proteins used as vaccines to elicit a specific immune response (Tomlinson, 2004).

1.4.1.2 Hormones

rDNA technology has been used for the production of various biopharmaceutical products; hormones are one of them. Before the advent of biotechnology, porcine insulin and bovine insulin were used for the treatment of diabetes, which also caused allergic reactions in the human body. In 1978, rDNA technology was used for insulin synthesis using Escherichia coli. (Humulin, Novolin, Velosulin). In 1982, the FDA-approved recombinant human insulin for the treatment of diabetic patients. Now, recombinant human insulin is manufactured in different doses for therapeutic action (insulin lispro, insulin aspart, insulin glargine—with very fast, fast, long-acting, respectively) and for different modes of administration (intramuscular, subcutaneous, etc.). Other than insulin, recombinant growth hormone is used to treat growth disorders. Somatropin, a widely used recombinant human growth hormone, is marketed under various brand names such as Saizen, Nutropin, etc. Recombinant follicle-stimulating hormone and recombinant luteinizing hormone were made successful in enhancing ovulation and pregnancy. Hence, assisted reproduction treatment through stimulating follicular development is an achievement of rDNA technology (Khan et al., 2016).

1.4.1.3 Monoclonal antibodies

Since the inception of hybridoma technology in 1975, significant advances have been made for the production of mAb and its derivatives to recognize an individual molecular target for their application in research, immunological investigations, and personal healthcare. mAb enables the antigenic profiling and visualization of macromolecular surfaces when used in combination with epitope mapping and molecular modeling techniques. They also play a keystone role in a vast array of clinical laboratory diagnostic tests in detecting and identifying cell markers and serum analytes. Apart from these applications, mAb are also used in various bio-techniques such as magnetic cell sorting, flow cytometry, immunoassays, and also for therapeutic purposes. Up to a certain level, mAb have replaced small molecules in pharmaceutical companies due to their exquisite target selectivity and less toxicity. To date, the United States Food and drug administration (US FDA) has approved mAb therapeutics for 33 targets in more than 37 distinct diseases, most commonly in cancer (27 approvals; Shepard, Phillips, Thanos, & Feldmann, 2017). New applications of mAbs are being tested with approval in hypercholesterolemia and bone metabolism. Now efforts for designing mAb, which simultaneously targets more than one antigen, is underway. The table given below is a comprehensive list of approved antibody used in therapeutics in 2019–20 with their indications and brand names (Table 1.3).

Table 1.3

ADC, Antibody–drug conjugate; CD, cluster of differentiation; CGRP, calcitonin gene-related peptide; C5, complement component 5; HER2, human epidermal growth factor receptor-2; IGF-1R, insulin-like growth factor-1 receptor; IgG1, immunoglobulin G; IL-23p19, interleukin-23 p19 peptide; PD-1, programmed cell death 1 protein; scFv, single-chain fragment variable; VEGF-A, vascular endothelial growth factor-A.

1.4.1.4 Cytokines

Cytokines are potent chemicals that play a pivotal role in regulating lymphocytes, macrophages, monocytes, etc. in immune response and inflammation. It encompasses lymphokines, monokines, interleukins (IL), colony-stimulating factors (CSFs), interferons (IFNs), tumor necrosis factor, and chemokines. Currently, a number of cytokines are used for therapeutics, and some have entered clinical trials for patients with cancer such as Granulocyte-Macrophage Colony-Stimulating Factor (GM-CSF) and common IL like IL-7, IL-12, IL-15, IL-18, and IL-21. Recombinant IL-2 for metastatic melanoma and renal cell carcinoma and IFN-α for the adjuvant therapy of stage III melanoma and recombinant IFN for patients with human immunodeficiency virus (HIV)-related Kaposi's sarcoma, genital warts, hairy cell leukemia, and hepatitis B and C have already achieved FDA approval (Lee & Margolin, 2011). Recombinant versions of CSF, including GM-CSF, granulocyte CSF, and erythropoietin, have revolutionized the ability to treat myelosuppression.

1.4.1.5 Vaccines

The emerging knowledge in molecular biology and immunology resulted in a revolution in vaccine development. These upcoming technologies in vaccine development, like reverse vaccinology, structural vaccinology, and synthetic vaccines, have revolutionized this field, resulting in marked progress in the vaccine development. Currently, DNA vaccine and mRNA vaccines are also emerging, but no commercial production of these vaccines are available for human use. Nowadays, vaccines are also used for noninfectious diseases such as cancer, Alzheimer's disease, cardiovascular disease, and allergic reactions. Sipuleucel-T is the first therapeutic cancer vaccine approved by the FDA in 2010 (Kesik-Brodacka, 2018). Only because of vaccines, diseases like smallpox have been wholly eradicated globally, whereas polio, measles, and tetanus have been significantly controlled. Despite rapid development in this field, vaccines for infections like HIV, hepatitis C virus, severe acute respiratory syndrome, middle east respiratory syndrome and Zika virus, and Coronavirus disease are under research, and there are no effective vaccines available yet (Chen, Cheng, Yang, & Yeh, 2017) (Table 1.4).

Table 1.4

HBV, Hepatitis B virus; HPV, human papilloma virus.

1.4.2 Nanomedicine

Nanomedicine is defined as the development of nanoscale (1–100 nm) or nanostructured objects/nano-robots/skin patches and their use in medicine for diagnostic and therapeutic purposes based on the use of their structure, which has unique medical effects. These nanostructured particles have revolutionized the medical field in drug delivery, diagnostic devices, imaging technology and agents, in tissue engineering, regenerative medicine, and also in implants by improving the electrode charge transfer at the electrode–tissue interface in retina implant. Different applications of nanoscale particles in medicine are: (1) drug therapy and delivery: Nanoscale particles/molecules differ from traditional small molecules having unique medical effects such as fullerenes and dendrimers (nanomaterial) based drugs. Nanomaterials are developed to improve pharmacodynamics and pharmacokinetics of drugs because their small size, large surface area to mass ratio, can carry a high dose of therapeutic load resulting in more devastating effects at the target tumor site. These nanoparticles encapsulate drugs and modify their surface, which overcomes solubility and stability issues of drugs and enables more precise targeting with a controlled release. Nanoparticles are used to deliver drugs through the blood–brain barrier for targeting brain tumors, which is one of the positive outcomes of nanomedicine. Nanoparticle-based different drug delivery platforms such as liposomes, gold, and silver nanoparticles target cancer are used. Nano spheres target asthma and polymeric nanoparticles are used in HIV. Thus nanoparticle overcomes the drug delivery limitation, which includes a short plasma half-life, poor stability, and potential immunogenicity (Wang & Mullett, 2013). (2) In vivo imaging: Nanoparticle (iron oxide) contrast agents provide improved contrast and favorable bio-distribution and are used for magnetic resonance imaging (MRI) and ultrasound. The nanoparticle is coated with a peptide that binds to a cancer tumor, after binding to the tumor, nanoparticle magnetic property enhances the images of the MRI scan. Magnetic particle imaging is used for cell imaging for the spatial distribution, visualization, and quantification of magnetic nanoparticles. It is highly sensitive, provides good spatial and temporal resolution, and is free from the background noise of the surrounding tissue (Hendrik et al., 2020). (3) In vitro diagnostics: Nanoparticle-based diagnostics provide rapid and earlier stage detection of the disease. Novel sensor concepts based on nanotubes, nano-pore, nanowires, nano-flares cantilevers, or atomic force microscopy are applied to diagnostic devices/sensors (Hawk's Perch Technical Writing, LLC, 2013). For example, the Nano mix (Emeryville, CA, United States) develops carbon nanotube-based sensors for monitoring respiratory functions, and Nanopore with AI can identify a single virus particle. For the detection of whole viruses for early diagnosis of viral infections, Bioforce's Virichip (Ames, IA, United States) are used, which are based on atomic force microscopy (Wagner, Bock, & Zweck, 2006).

1.4.3 Gene therapy

Gene therapy is the incorporation of genetic material in an organism either directly or by using vectors (such as viruses) or by using an ex vivo approach to inhibit or initiate the cellular processes by means of correcting the altered gene or by modification of specific site that can act as a therapeutic target for the treatment that underlies disease. Gene therapy is used in treating patients with enzyme deficiencies, classic Mendelian gene disorders (cystic fibrosis, hemophilia, muscular dystrophy, and sickle cell anemia), cancer, and certain viral infections such as AIDS. Various strategies are used to perform gene therapy, such as rDNA technology, genome editing. For performing gene therapy, specific cell types have identified that need to be treated. Based on the target cell, gene therapy is divided into two types: germline therapy in which a functional gene is integrated into stem cells, that is, sperm or egg cells genome, which is hereditary. In somatic gene therapy, therapeutic genes are transferred in somatic cells, and their effect is restricted to a patient only and is not pass on to the future generations. A few gene therapies using the rDNA approach have been published and approved for clinical use. Various techniques are being used for successful gene editing like zinc finger nucleases, transcription activator-like effector nucleases, and gene targeting. These technologies have proven efficient in the treatment of childhood cancer through the engineering of immune cells, inactivation of the gene that encodes HIV coreceptor C–C chemokine receptor type 5 and also alleviates the HBB gene mutation in hematopoietic stem cells. Genome editing using clustered regularly interspaced short palindromic repeats (CRISPR) Cas-9: With the advancement in biotechnology, CRISPR–Cas-9 is setting a remarkable development due to its ability to modify the genome rapidly with high specificity and in an efficient way. CRISPR technique utilizes three molecules: one nuclease (generally Cas-9 of Streptococcus pyogenes) is a protein that assembles with the single guided RNA and then binds and makes a cut at 20-base-pair DNA sequence complementary to the guide RNA, single guide RNA, and target DNA. Recognition sites in DNA must be adjacent to the proto-spacer adjacent motif or PAM that triggers Cas-9 to make a double-stranded DNA break-in target sequence. Genetic editing is performed by knockout of the gene and integration of exogenous sequences and allele