Pharmaceutics and Drug Design Commons^™

Innovative Development Of Synthetic Biology Industry From Perspective Of Deep Integration Of Four Chains, Qin Guo, Chao Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Future industries represent the development direction of technological innovation and emerging industries, and are the main path to accelerate the formation of new quality productivity. As an important subsector of the future industry, synthetic biology industry is becoming a new track and new format for new quality productivity, and various regions are making cutting-edge directions such as synthetic biology industry a hot topic for future industrial layout. Based on the analysis of typical cities such as Shenzhen, Beijing, Tianjin, Shanghai, Hangzhou, and Changzhou, the current integration of the Four Chains in the synthetic biology industry is facing a four-dimensional dilemma …

Ai-Driven Drug Innovation Research: Trends, Challenges, And Countermeasures, Tian Miao, Qi Zhou, Lianzheng Zhou, Weijun Xu, Siyuan Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI) is profoundly transforming the innovation paradigm, industrial ecosystem, and business model of drug research and development. In recent years, the global AI-driven pharmaceutical market has grown rapidly. Major economies, multinational pharmaceutical enterprises, and technology giants are accelerating their strategic deployment. AI pharmaceutical industry has entered a critical stage of transitioning from proof-of-concept to commercial-application. China attaches great importance to the integrated development of AI and the biopharmaceutical industry, but it still faces challenges, including data scarcity, talent shortages, algorithmic black-boxes, regulatory lag, and weak foundations. This study proposes measures from the aspects of data supply, talent cultivation, …

Synthesis And Characterization Of Succinate Dehydrogenase Inhibitors H2/Z14 And C6/Z96 In Order To Combat Small Cell Lung Cancer, Lauren M. Graves

Honors Undergraduate Theses

The use of ubiquinone inhibitors to combat cancer is a recent development in medicinal science and procedures to efficiently synthesize these drugs remain limited. C6/Z96 and H2/Z14, two succinate dehydrogenase inhibitors, have been previously tested in vitro against NSCLC with positive results. Their similarity to ubiquinone is what makes them a strong candidate for a succinate dehydrogenase inhibitor at the ubiquinone binding site. The heterocyclic scaffolds and substituents are proposed to bind strongly through a combination of electronics, hydrogen-bonding, and fit, allowing them to bind well and prove to be more favorable than ubiquinone when competing for the Q-site. By …

Selenium Nanoparticles As Versatile Delivery Tools, Amir Nasrolahi Shirazi, Rajesh Vadlapatla, Ajoy Koomer, Kyle Yep, Keykavous Parang

Pharmacy Faculty Articles and Research

Selenium nanoparticles (SeNPs) have emerged as promising metal-based nanoparticles for drug delivery due to their unique physicochemical properties, intrinsic bioactivity, and biocompatibility. SeNPs offer a lower toxicity, higher bioavailability, and flexibility to be customized for surface chemistry compared to traditional selenium compounds. Advances in synthetic strategies, including chemical reduction, green biosynthesis, and surface functionalization with polymers, peptides, or ligands, have improved their stability, targeting capability, and circulation time. SeNP-based systems have demonstrated unique anticancer, antimicrobial, and anti-inflammatory activities, as they can function as drug carriers and active therapeutic agents. The surface of SeNPs has been functionalized with ligands such as …

Gramseq-Dta: A Grammar-Based Drug-Target Affinity Prediction Approach Fusing Gene Expression Information, Kasul Debnath, Pratip Rana, Preetam Ghosh

Computer Science Faculty Publications

Drug–target affinity (DTA) prediction is a critical aspect of drug discovery. The meaningful representation of drugs and targets is crucial for accurate prediction. Using 1D string-based representations for drugs and targets is a common approach that has demonstrated good results in drug–target affinity prediction. However, these approach lacks information on the relative position of the atoms and bonds. To address this limitation, graph-based representations have been used to some extent. However, solely considering the structural aspect of drugs and targets may be insufficient for accurate DTA prediction. Integrating the functional aspect of these drugs at the genetic level can enhance …

Rwanda's Natural Remedies: A Fresh Look At The Fight Against Malaria, Leandre Nsabimana Ndisanze

Pomona Senior Theses

Malaria remains one of the most devastating parasitic diseases globally, disproportionately affecting sub-Saharan Africa, where Rwanda continues to face high transmission rates and rising resistance to conventional interventions. Despite decades of control efforts, the emergence of drug-resistant Plasmodium falciparum and insecticide-resistant Anopheles mosquitoes threatens to reverse recent gains. This research responds to the urgent need for sustainable and culturally relevant alternatives by exploring the therapeutic potential of Rwandan traditional medicinal plants. These indigenous remedies, long used by local healers, offer an underexplored reservoir of bioactive compounds that may provide the basis for novel antimalarial drugs.

The central hypothesis of this …

The Future Of Ai Regulation In Drug Development: A Comparative Analysis, Gabriela Lenarczyk, Timo Minssen, Nicholson Price, Arti Rai

Faculty Scholarship

As artificial intelligence (AI) transforms drug development, regulatory frameworks are evolving to oversee its implementation, particularly at the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). This paper makes three contributions to understanding emerging regulatory approaches. First, we offer a comparative analysis of how these agencies have responded to AI-driven advances, incorporating new US executive orders and the European Union (EU)’s AI Act. Second, we propose a novel analytical framework to understand regulatory divergence: the FDA’s flexible, dialog-driven model contrasts with the EMA’s structured, risk-tiered approach, reflecting broader institutional and political-economic differences. While the former encourages …

Rational Design Of Small Molecules Targeting Mitochondrial Redox Proteins, Matheus Barbosa Belchior

Graduate Theses, Dissertations, and Problem Reports (ETD)

Reactive oxygen species play a crucial role in many cellular processes. Despite being a natural byproduct of cellular metabolism, overexpression of these species causes damage to the cell, leading to cell dysfunction. Central to the regulation of these highly reactive molecule is the mitochondria. Impairment in its function has been associated with oxidative stress within the cell. Herein, a ligand-based and structure-based approach to design new small molecules to inhibit mitochondrial redox proteins associated with oxidative stress and reactive oxygen species. In the first project two molecules were synthesized and characterized as potential monoamine oxidase B inhibitors. Results showed two …

Advancing Continuous Manufacturing: The Role Of Process Analytical Technology In Process Development, Samuel R. Henson

Electronic Theses and Dissertations

The pharmaceutical industry is actively pursuing technologies which improve manufacturing processes with the goal of producing high-quality pharmaceutical products for patients, manifesting in an industry-wide investment in continuous manufacturing (CM). Process analytical technology (PAT) has been recognized for its successful monitoring of critical quality attributes during routine production and is often cited alongside CM due to its ability to make timely, in-line measurements of intermediate materials. Various PAT tools are valuable in process development, particularly as continuous wet granulation processes are developed for use within pharmaceutical manufacturing. This work applied PAT and chemometric modeling during CM process development to enhance …

Efficient Development Of Density-Insensitive Near-Infrared Methods For In-Line Drug Content Monitoring In Continuous Powder Streams, Natasha L. Velez-Silva

Electronic Theses and Dissertations

A well-defined action plan to respond effectively to sudden changes in product demand is critical for preventing drug shortages within the pharmaceutical industry. An effective way to increase the output of a continuous manufacturing (CM) process is through flow rate adjustments. However, robust analytical methods must be in place to ensure consistent analytical performance across varying flow rates. Existing approaches for mitigating the physical effects of flow rate on Near-Infrared (NIR) measurements are often burdensome. Thus, efficient robust modeling strategies that reduce the current calibration burden and ensure model insensitivity to the physical variations in CM systems are needed. In …

Design, Synthesis, And Nmr-Guided Characterization Of A Targeted Covalent Inhibitor-Like Molecule Against Ivyp1 From P. Aeruginosa, Samuel Taylor Moore

Master's Theses

Multi-drug resistance poses a serious threat to future generations and historical antibiotic pipelines; consequently, the medical and economic burdens associated with treating multidrug-resistant bacteria are substantiated. In this context, P. aeruginosa (PA) emerges as one of the most significant healthcare challenges, being a leading cause of resistance-associated mortality worldwide. Despite modern efforts to combat these poor outcomes, drug-resistant cases continue to rise, and the need for novel antibiotic treatment is apparent. To this end, we investigated relevant resistance mechanisms and past antibiotic targets within PA, and in doing so, we identified relationships between peptidoglycan biology and a periplasmic protein, Inhibitor …

Computational Logp Calculations And Determination Of Lipophilicity Values Of Fluorinated Morphine Derivatives, Mirabella Romano, Allison Vu, Emily Chen

Student Scholar Symposium Abstracts and Posters

The addictive effect of opioids impacted 60 million people globally in 2023. This opioid crisis necessitates the development of opioid derivatives that maintain analgesic efficacy while minimizing addictive effects from opioid use. The present work focuses on morphine, a commonly prescribed opioid with high affinity to the mu-opioid receptor (MOR). Morphine binds non-selectively within both healthy and inflamed tissue. By modifying morphine’s structure through fluorination to counteract its non-selective binding, the drug’s pharmacological ability to provide effective pain relief comes with a lower risk of addiction. Specifically, the addition of fluorine to differing beta positions of the main binding site …

Synthesis Of Photocleavable Molecules For Neurological Applications, Nishal Madujith Egodawaththa Arachchilage Don

Theses and Dissertations

In recent biomedical research, the precise control of molecular dynamics through light activation has emerged as a powerful tool, particularly in the field of neurobiology. This approach involves the use of photocleavable cages or photoprotective groups (PPGs) that are chemically tethered to biologically active molecules such as neurotransmitters or calcium chelators. These cages remain inert until exposed to specific wavelengths of light, typically in the visible range, triggering the release of the active compound with high spatiotemporal precision.

For neurotransmitter systems, such as glutamate (Glu), which plays a critical role in synaptic transmission and memory formation, researchers have developed novel …

Incorporating Solvation Thermodynamic Mapping In Computer-Aided Drug Design, Yeonji Ji

Dissertations, Theses, and Capstone Projects

Advancements in computational techniques have revolutionized structure-based drug design, substantially improving the efficiency and effectiveness of the drug discovery process by reducing time, costs, and labor requirements. These advancements include various methods, such as investigating small molecule ligands binding to proteins, exploring alternative protein conformations, and solvation mapping on the protein surfaces. Among these methods, understanding the correlation between protein-ligand binding and the role of solvation is important.

A fundamental concept in protein-ligand binding is shape and electrostatic complementarity, which is complicated by the inherent flexibility of proteins. In the absence of small molecule ligands, proteins are complementary to surface …

Microencapsulation Of Cosmos Caudatus Kunth Extract Using Sodium Alginate And In Vitro Antioxidant Activity Test, Safina Samara Nur Fadlila, Oktavia Eka Puspita, Zubaidah Ningsih, Anna Safitri

Makara Journal of Science

This study aims to encapsulate Cosmos caudatus K. leaf extract in sodium alginate crosslinked with calcium chloride (CaCl₂) as coating materials through freeze-drying. Antioxidant assays were performed to evaluate the applicability of the microcapsules as antidiabetic medicines. Their characteristics, antioxidant activity, and encapsulation efficiency (EE) were also examined. Results indicated that the concentration of sodium alginate and pH influenced the manufacturing process of the microcapsules. The highest EE was obtained at pH 6 and alginate concentration of 2% (w/v). The IC₅₀ for the antioxidant activity of the microcapsules was 139.96 ± 1.094 μg/mL. Scanning electron microscopy confirmed …

Electrochemical Modulation Of Surface Plasmon Wave To Investigate Dna-Based Sensing Platforms And Detection Of Sars-Cov2., Anil Sharma

Electronic Theses and Dissertations

This study offers a thorough comparative analysis of optical and electrical signaling strategies for assessing the electrochemical properties of different redox-labeled DNA-based biosensing platforms. In addition, it illustrates the development of an optical interrogation technique with electrochemical modulation of surface plasmon waves (ECM-SPW) as a route for analyzing and implementing DNA-based hybridization sensors. For those quantitative analyses, we chose a model sensing platform composed of a methylene blue (MB)-modified single-stranded DNA (ssDNA) signaling probe and an unlabeled capture ssDNA probe that complements the signaling probe. Two types of signaling probes were employed in this work: one with MB attached to …

Synthesis Of Thermoresponsive Poly(N-Isopropyl Acrylamide) Based Core-Shell And Hollow Shell Nanogel With Tunable Core And Shell Thickness, Mohamad Hijazi, Molla R. Islam

Student Scholar Symposium Abstracts and Posters

Nanogels have emerged as a notably safer and more effective means for drug delivery, primarily due to their adjustable drug-loading capabilities. Hollow-core nanoparticles offer some unique properties that are desirable for drug delivery applications. Initially, silica core nanoparticles were synthesized using the Stöber process at different temperatures where Tetraethoxysilane (TEOS) undergoes hydrolysis in the presence of ethanol and then a condensation reaction to form silica nanoparticles. Scanning Electron Microscopy (SEM) and Optical Microscopy (OM) analysis revealed that the size of silica core particles varied with the synthesis temperature (300 nm at 30°C to 150 at 60°C). The core silica particles …

Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin

Research Symposium

Carbon–carbon (C–C) bond activation has gained increased attention as a direct method for the synthesis of pharmaceuticals. Due to the thermodynamic stability and kinetic inaccessibility of the C–C bonds, however, activation of C–C bonds by homogeneous transition-metal catalysts under mild homogeneous conditions is still a challenge. Most of the systems in which the activation occurs either have aromatization or relief of ring strain as the primary driving force. The activation of unstrained C–C bonds of phosphaalkynes does not have this advantage. This study employs Density Functional Theory (DFT) calculations to elucidate Pt(0)-mediated C–CP bond activation mechanisms in phosphaalkynes. Investigating the …

Use Of Artificial Intelligence In Drug Development, Louise C. Druedahl, Nicholson Price, Timo Minssen, Dipl Jur, Ameet Sarpatwari

Articles

Considerable focus has been placed on the health care applications of artificial intelligence (AI). Already, machine learning, a subset of AI that involves “the use of data and algorithms to imitate the way that humans learn” has been used to predict diseases, while AI-powered smartphone apps have been developed to promote mental health and weight loss. Owing in part to such successes, the market for AI in health care has been forecasted to increase more than 1000% between 2022 and 2029, from $13.8 billion to $164.1 billion. One area of substantial promise is drug development, which is poised to benefit …

Enhancing 21 U.S.C. §§ 355, 356, And 360 To Encompass Artificial Intelligence-Based Drug Design And Manufacturing Methods, Aj Tsang

Michigan Technology Law Review

Despite newfound attention to how artificial intelligence (AI) may accelerate pharmaceutical development, federal regulators may find that current statutes are ambiguous or silent about their applicability to AI-based drug design and manufacturing methods. This poses a serious problem in the era of Loper Bright and the Major Questions Doctrine. As federal agencies struggle to adjust to courts’ growing demand for Congress to craft clear, explicit, and express delegations of authority, this note develops a statutory framework in which the Food and Drug Administration (FDA) would have more flexibility to regulate the use of AI in advanced drug manufacturing. Guided by …

Design Of Kappa Opioid Receptor Agonists For Potential Treatment Of Multiple Sclerosis, Lindsay Kornberger

Theses and Dissertations--Pharmacy

Multiple Sclerosis (MS) is a neurodegenerative disease of the central nervous system characterized by demyelination and neuroinflammation. There is currently no cure for MS. There is a critically unmet need for the development of pharmacotherapies that can induce remyelination promoting both repair and recovery. The kappa opioid receptor (KOR) has been identified as a potential target for the development of remyelinating pharmacotherapies. KOR activation has been shown to promote functional recovery and remyelination preclinically. However, typical KOR agonists like U50,488 have limitations such as sedation and dysphoria limiting their use. This necessitates further development of new KOR agonists that maintain …

Equine In Vivo Metabolite Profiling Of The Selective Androgen Receptor Modulator Lgd-3303 For Doping Control, Malin Nilsson Broberg, Heather Knych, Ulf Bondesson, Curt Pettersson, Börje Tidstedt, Scott Stanley, Mario Thevis, Mikael Hedeland

UK CARES Faculty Publications

LGD-3303 is a Selective Androgen Receptor Modulator (SARM) that is prohibited in both equine and human sports due to its anabolic properties. The aim of this study was to investigate the equine in vivo metabolite profile of LGD-3303 and identify drug metabolites that can be suitable as new and improved analytical targets for equine doping control. This was performed by an oral administration of 0.05 mg⋅kg 1 LGD-3303 to horses, where blood and urine samples were collected up to 96 h after administration. The in vivo samples consisting of plasma, urine and hydrolyzed urine were analyzed utilizing ultra-high performance liquid …

Development Of Novel Hybrid Structures For Fast Dissolution Of Hydrophobic Drugs, Mohammad Saiful Islam

Dissertations

Nanomaterials have proven to be highly effective in the design and development of biomedicine. Complementary nanostructured hybrid particles show great promise in drug delivery applications. By improving functionalization, the physicochemical properties of the particles can be enhanced resulting in a high surface area, tunable hydrophilicity and porosity. These characteristics can provide a suitable environment for drug encapsulation, biocompatibility, high drug loading, and customizable release capabilities.

The formulation of drugs with poor water solubility faces multiple challenges, such as insufficient dissolution and inconsistent therapeutic efficacy, particularly when administered orally over an extended period. To overcome these challenges, some of the beneficial …

Computer-Aided Drug Design Of Bakuchiol-Inspired Lxrα Modulators Against Acute Lymphoblastic Leukemia, Dillon P. Cao

LSU Master's Theses

Acute lymphoblastic leukemia (ALL) is the most common type of cancer in children, accounting for approximately 25% of pediatric malignancies. Although glucocorticoids are commonly used to treat ALL, prolonged use can lead to steroid resistance, rendering the drug regimen ineffective. Therefore, alternative treatment avenues are needed for high- risk pediatric patients that do not respond well to traditional regimens.

Liver X Receptor α (LXRα) is presented as a potential alternative drug target for pediatric patients that exhibit suboptimal response to glucocorticoids. Limitations of the current LXRα modulators such as indiscriminate isoform selectivity between LXRα and LXRβ and consequent adverse effects …

Virtual And In Vitro Screening Of Natural Products Identifies Indole And Benzene Derivatives As Inhibitors Of Sars-Cov-2 Main Protease (MPro), Dony Ang, Riley Kendall, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The rapid spread of the coronavirus disease 2019 (COVID-19) resulted in serious health, social, and economic consequences. While the development of effective vaccines substantially reduced the severity of symptoms and the associated deaths, we still urgently need effective drugs to further reduce the number of casualties associated with SARS-CoV-2 infections. Machine learning methods both improved and sped up all the different stages of the drug discovery processes by performing complex analyses with enormous datasets. Natural products (NPs) have been used for treating diseases and infections for thousands of years and represent a valuable resource for drug discovery when combined with …

The Science Of Oral Carbapenems, Landon Olsen, Daniel J. Yang, Aiyi Chen, Thahn-Liem Vu, H. Stephen Lee

Annual Research Symposium

No abstract provided.

Development Of A Chemical Biology Approach To Uncover The Influence Of Sequence Variations On Ces1 Activity In Live Cells, Samuel James Knebel

Masters Theses

Drug metabolism is the biochemical process of modifying drugs to detoxify and remove them through enzymatic transformations. These biotransformation’s occur primarily in the liver and are critical to understanding how pharmaceutical compounds are chemically altered inside the human body. Human carboxylesterases (CESs) catalyze the hydrolysis of esters, amides, thioesters, and carbamates. CES-mediated hydrolysis plays an important role in the metabolism of many drugs including the first FDA approved antiviral treatment for COVID-19, remdesivir (Veklury), the seizure control medication rufinamide (Banzel), and the flu antiviral drug oseltamivir (Tamiflu). CES activity is known to be influenced by a variety of factors including …

Designing And Synthesizing A Warhead-Fragment Inhibitory Ligand For Ivyp1 Through Fragment-Based Drug Discovery, Samuel Moore

Symposium of Student Scholars

Fragment-based drug discovery (FBDD) is a powerful tool for developing anticancer and antimicrobial agents. Within this, magnetic resonance spectroscopy (NMR) provides a comprehensive qualitative and quantitative approach to screening and validating weak and robust binders with targeted proteins, making NMR among the most attractive strategies in FBDD. Inhibitor of vertebrate lysozyme (Ivyp1) of P. aeruginosa serves as an excellent target because of its active cellular location and implications in clinical prognosis for cystic fibrosis and immunocompromised patients. This study uses current NMR and biophysical techniques to develop a covalent, fragment-linked warhead inhibitor for Ivyp1 through synthetic methods, warhead linking, and …

Perturbation Modeling For Molecular Design Of Protein Tyrosine Kinase Inhibitors Using Unsupervised Machine Learning, Keerthi Krishnan

Computational and Data Sciences (MS) Theses

The field of computational drug discovery and development has grown, with the aid of new computational tools for novel molecule discovery. In specific, generative deep learning models have excelled as tools to aid in navigating the large space of known molecules and in the creation of new molecules. These models are fed various representations of molecules as inputs and learn to perform a variety of things, such as the optimization of these molecules towards a targeted property. Ultimately, these generative learning models allow us to build bridges between chemical and continuous spaces to understand the compromise between invoking small incremental …

The Development Of Inhibitors For Sars-Cov-2 Orf8, My Thanh Thao Nguyen

CSB and SJU Distinguished Thesis

An unexpected outbreak of SARS-CoV-2 caused a worldwide pandemic in 2020. Many repurposed drugs were tested, but there are currently only three FDA approved antivirals (Merck’s antiviral Molnupiravir, Pfizer’s antiviral Paxlovid, and Remdisivir).1 Most of the antiviral drugs tested SARS-CoV-2 main protease and RNA-dependent RNA polymerase. However, it is important to explore different drug targets of SARS-CoV-2 to prepare for the virus mutations of the future. This research looks at an alternative approach in which SARSCoV- 2 Open Reading Frame 8 (ORF8), which has been shown to be a rapidly evolving hypervariable gene, was chosen to be the protein of …