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ADVANCEMENT IN VACCINE DEVELOPMENT AND DELIVERY
(M/S Academic Publishers & Distributors/ZENODO, 2025) Yasmeen Bano, Pushpendra Soni, Alisha Bano, Asiya Fatima, Noor Jameel, Riya Yadav, Mohammad Irfan Khan
The field of vaccinology is undergoing rapid scientific advancements and an urgent need for faster, more effective immunization strategies. Traditional vaccines, including live attenuated, inactivated, toxoid and subunit vaccines, have played a crucial role in controlling infectious diseases for over a century. This chapter explores cutting-edge vaccine technologies, including nucleic acid based platforms (mRNA and DNA vaccines), peptide vaccines and protein-based formulations, highlighting their mechanisms, advantages and clinical implications. Recent breakthroughs in reverse vaccinology, CRISPR-based gene editing and nanoparticle-based delivery systems have revolutionized antigen discovery and vaccine development, enabling precision-targeted immunization strategies. The success of mRNA vaccines against COVID-19 has underscored the transformative potential of synthetic biology and genomics in accelerating vaccine production. Despite these advancements, challenges persist, including cold chain logistics, immune response variability, and global accessibility. This chapter critically examines these emerging technologies, offering a comprehensive perspective on the future of vaccines, where personalized immunization, rapid deployment and enhanced efficacy
will define the next generation of disease prevention.
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN DRUG DESIGN
(M/S Academic Publishers & Distributors/ZENODO, 2025) Aleena, Pushpendra Soni, Ahsan Ahmed Khan, Mohammad Ahmad
Artificial Intelligence (AI) and Machine Learning (ML) have transformed drug discovery, significantly improving efficiency, accuracy and speed in drug research and development. Compared to the older, time-consuming, and expensive traditional approach, AI-driven methodologies optimize molecular design, predict drug-target interactions and streamline clinical trial processesto the potential saving of both costs and timelines. AI-powered computational tools, such as virtual screening, de novo drug design, and structure-based drug development, have also helped enhance the selection of more accurate drug candidates to be brought to development, improving success in drug development. AI has also affected prediction in Drug-Drug Interactions (DDIs) and adverse drug reactions (ADRs), enhancing safety due to patient improvements from advanced techniques indata analysis like National Language Processing (NLP) and network-based modeling. Optimistic to this notion, clinical trials have become improved through AI: better patient selection, adaptive design and constant monitoring, maximizing efficiency while trimming costs. Currently, challenges encountered encompass data quality model interpretability along with ethical debates, yet research in pharmaceutical fields continues with momentum. Quantum Computing, automated laboratories and more such drugs repurposing by AI make it all work the faster way it is meant. This advancement of AI will continue to shape health care, hasten drug development, and enhance patients’ outcomes and therefore, is essential in modern medicine.
Nanotechnology in Drug Delivery Systems
(M/S Academic Publishers & Distributors/ZENODO, 2025) Pushpendra Soni, Aleena, Alisha Bano, Samman, Asiya Fatima, Yasmeen Bano, Badruddeen
Nanotechnology has revolutionized drug delivery systems; now, therapeutic intervention can be targeted, efficient, and controlled. Traditional methods of administration of drugs often suffer from multiple disadvantages, such as poor bioavailability, non-specific distribution, and systemic toxicity. Nanocarriers such as nanoparticles, liposomes and dendrimers offer solutions to enhance the solubility and stability of drugs through selective targeting, thus improving the efficacy of drug therapy while reducing adverse effects. The main goals of nanotechnology-based drug delivery include optimizing the kinetic release of the drug, enhancing bioavailability, and allowing for sitespecific delivery. The delivery is facilitated through the exploitation of both passive and active targeting mechanisms, namely the Enhanced Permeability and Retention (EPR) effect and ligandmediated targeting, respectively. The strategies of controlled release, such as pH-sensitive, temperature-sensitive, enzyme-sensitive and redox-sensitive systems, enable the accurate delivery of drugs to diseased tissues while maintaining exposure as low as possible in the systemic circulation. Nanocarriers are promising in clinical applications, especially in cancer therapeutics, where they enhance the accumulation of drugs into the tumor. They reduce multidrug resistance and allow combination therapies. They permeate the blood-brain barrier in neurological disorders and improve drug delivery efficiency in conditions like Alzheimer’s and Parkinson’s disease. As such, they are emerging as promising tools for gene therapy, infectious disease management and regenerative medicine, too. Its large-scale production challenges the very issues of nanomedicine itself because of stability issues, regulatory aspects and eventual long-term toxicities. Future outlooks may include multifunctional and stimuli-responsive nanocarriers, self-assembling systems, and personalized medicine approaches tailored to the patient’s specific profile. Nanotechnology-driven perspectives ensure that nanotechnology will soon take over the future of drug delivery, especially in terms of effectiveness, precision and compliance with patients on treatment. Modern medicine will be completely transformed by innovative nanocarriers through new advancements in material science and bioengineering, making treatments safer and more effective in handling the disease.
Unveiling the Chemistry: Herb Drug Interaction
(Bentham Science, 2025) Pushpendra Soni, Shom Prakash Kushwaha, Syed Misbahul Hasan, Abdul Hafeez, Akash Ved
Herb-drug Interactions have been of concern in the area of pharmaceutical chemistry, as most people nowadays use herbs and drugs together. This chapter explores the mechanisms of herb-drug interactions and their critical impact on drug efficacy, safety, and personalized treatment outcomes. Although herbs are natural, they do contain active ingredients such as terpenoids, alkaloids, and flavonoids. These substances can significantly alter drug metabolism, affecting the speed and effectiveness of medications. The major chemical compounds found in the herbs may alter the pharmacokinetics and pharmacodynamics of the related drugs. It focuses on the primary mechanisms of these interactions, including the effects on enzymes, primarily cytochrome P450 inhibition or induction, as well as interference with transporter proteins involved in drug distribution, metabolism, and excretion. Due to this new tactic, analytical merits are essential for exploring these interactions, and designing LC-MS/MS, HPLC, and NMR spectrometry is important for better understanding. These methods are necessary for the effective identification of different herbal components and their potential interactions with drug actions. However, there is still an extensive research deficit, especially regarding the use of multiple herbs in a given formulation and the variation in the composition of the active compounds. This chapter fills these gaps with the current data and emphasizes the need for a more thorough analysis and the development of prognosis models. All such advancements are crucial for precisely predicting interactions and formulating procedures for safely using herbal supplements with pharmaceutical products. Its primary goal is to enhance the safety and effectiveness of combined treatments, thereby improving clinical practice and advancing individualized medicine. From this chapter, we should be able to understand the chemical processes involved in most herbal drug interactions and their effect on patients' health.
Circular economy, life cycle assessment, and sustainability of waste derived catalysts
(Elsevier, 2026) Shom Prakash Kushwaha, Syed Misbahul Hasan, Kuldeep Singh, Arun Kumar, Poonam Kushwaha, Abdul Hafeez, Manisha Pandey, Munendra Mohan Varshney, Hemendra Mishra, Pushpendra Soni
With the advent of artificial intelligence and machine learning technologies, the integration of emerging AI-assisted design methodologies offers a transformative pathway to optimize catalyst performance and accelerate innovation. With these advancements waste-derived catalysts have potential to drive the transition towards a zero-waste economy and foster sustainable industrial, agricultural and waste disposal practices. Waste-derived catalysts have emerged as an important tool in addressing the environmental, economic, and social challenges associated with conventional chemical processes. These catalysts can be sourced from agricultural dumps, municipal waste, and industrial runoffs and derived as catalysts using advanced thermochemical and hydrothermal techniques. Waste-derived catalysts offer a great example of a system which follows the principles of the circular economy which helps to convert discarded materials into high-value, functional catalysts.
Waste-derived catalysts have demonstrated enhanced surface properties and reactivity. The catalysts can chemically be classified as carbon-based, transition metal-based, calcium-based catalysts based on the final chemical composition of the catalyst. Comprehensive life cycle assessments of these waste-derived catalysts have shown to substantially reduce greenhouse gas emissions, energy consumption, and waste generation and thus help in mitigating environmental impacts while bolstering economic efficiencies.