Public acceptability of highway safety countermeasures. Volume III: alcohol and drug research. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Interagency coordination in drug research and regulation. Hearings before the Subcommittee on Reorganization and International Organizations of the Committee on Government Operations, United States Senate, Eighty-eighth Congress, first session. Agency coordination study, pursuant to S. Res. 27, 88th Cong. Review of cooperation on drug policies among Food and Drug Administration, National Institutes of Health, Veterans' Administration, and other agencies. Mar. 20-June 26, 1963.

Mode of access: Internet.

Interagency coordination in drug research and regulation : hearings before the Subcommittee on Reorganization and International Organizations of the Committee on Government Operations, United States Senate, Eighty-seventh Congress, second session. Agency coordination study (pursuant to S. Res. 276, 87th Cong.). Review of cooperation on drug policies among Food and Drug Administration, National Institutes of Health, Veterans' Administration, and other agencies. ...

Pt. 4-5 titles vary: "Eighty-eighth Congress, first session. Agency Coordination Study (pursuant to S. Res. 27, 88th Cong., as amended). Review of cooperation on drug policies among (the) Food and Drug Administration, National Institutes of Health, Veterans' Administration, and other agencies.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

The Swiss regulatory framework for pædiatric health research

Medical research on minors entails both risks and benefits. Under Swiss law, clinical trials on children, including nontherapeutic drug trials, are permissible. However, ethics committees must systematically verify that all clinical studies have a favorable risk-benefit profile. Additional safeguards are designed to ensure that children are not unnecessarily involved in research and that proper consent is always obtained. Federal Swiss law is undergoing revision to extend these protections beyond clinical trials to a broad array of health research. The Swiss drug agency also seeks to improve the incentives for pharmaceutical firms to develop new paediatric drugs and relevant paediatric drug labels.

Molecular modeling databases: A new way in the search of protein targets for drug development

DBMODELING is a relational database of annotated comparative protein structure models and their metabolic, pathway characterization. It is focused on enzymes identified in the genomes of Mycobacterium tuberculosis and Xylella fastidiosa. The main goal of the present database is to provide structural models to be used in docking simulations and drug design. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models which show high structural quality should be used in such efforts. Molecular modeling of these genomes generated a database, in which all structural models were built using alignments presenting more than 30% of sequence identity, generating models with medium and high accuracy. All models in the database are publicly accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools. DBMODELING user interface provides users friendly menus, so that all information can be printed in one stop from any web browser. Furthermore, DBMODELING also provides a docking interface, which allows the user to carry out geometric docking simulation, against the molecular models available in the database. There are three other important homology model databases: MODBASE, SWISSMODEL, and GTOP. The main applications of these databases are described in the present article. © 2007 Bentham Science Publishers Ltd.

Amphibian secretions for drug discovery studies: A search for new antiparasitic and antifungal compounds

The antiparasitic and antifungal activities of nine amphibian skin secretions were studied in different in vitro models. Seven secretions presented a considerable antiprotozoan activity and one showed promising results against Candida sp. These results can be the basis for the development of new drugs, especially for neglected parasitic diseases. © 2007 Bentham Science Publishers Ltd.

Chorismate synthase: An attractive target for drug development against orphan diseases

The increase in incidence of infectious diseases worldwide, particularly in developing countries, is worrying. Each year, 14 million people are killed by infectious diseases, mainly HIV/AIDS, respiratory infections, malaria and tuberculosis. Despite the great burden in the poor countries, drug discovery to treat tropical diseases has come to a standstill. There is no interest by the pharmaceutical industry in drug development against the major diseases of the poor countries, since the financial return cannot be guaranteed. This has created an urgent need for new therapeutics to neglected diseases. A possible approach has been the exploitation of the inhibition of unique targets, vital to the pathogen such as the shikimate pathway enzymes, which are present in bacteria, fungi and apicomplexan parasites but are absent in mammals. The chorismate synthase (CS) catalyses the seventh step in this pathway, the conversion of 5-enolpyruvylshikimate-3-phosphate to chorismate. The strict requirement for a reduced flavin mononucleotide and the anti 1,4 elimination are both unusual aspects which make CS reaction unique among flavin-dependent enzymes, representing an important target for the chemotherapeutic agents development. In this review we present the main biochemical features of CS from bacterial and fungal sources and their difference from the apicomplexan CS. The CS mechanisms proposed are discussed and compared with structural data. The CS structures of some organisms are compared and their distinct features analyzed. Some known CS inhibitors are presented and the main characteristics are discussed. The structural and kinetics data reviewed here can be useful for the design of inhibitors. © 2007 Bentham Science Publishers Ltd.

Molecular hybridization: A useful tool in the design of new drug prototypes

Molecular hybridization is a new concept in drug design and development based on the combination of pharmacophoric moieties of different bioactive substances to produce a new hyrid compound with improved affinity and efficacy, when compared to the parent drugs. Additionally, this strategy can results in compounds presenting modified selectivity profile, different and/or dual modes of action and reduced undesired side effects. So, in this described several example of different strategies for drug design, discovery and pharmacomodulation focused on new innovative hybrid compounds presenting analgesic, anti-inflammatory, platelet anti-aggregating, anti-infections, anticancer, cardio- and neuroactive properties.

Platelet GPIb complex as a target for anti-thrombotic drug development

Specific inhibition of platelet function is a major target of anti-thrombotic drug research. Platelet receptors are both accessible and specific but have multiple functions often linked to a wide range of ligands. GPIb complex is best known as a major platelet receptor for von Willebrand factor essential for platelet adhesion under high shear conditions found in arteries and in thrombosis. Recent animal studies have supported inhibition of GPIb as a good candidate for anti-thrombotic drug development with several classes of proteins showing important specific effects and the required discrimination between roles in haemostasis and thrombosis is important to protect against bleeding complications. These include antibodies, several classes of snake venom proteins, mutant thrombin molecules and peptides affecting subunit interactions. However, due to the nature of its receptor-ligand interactions involving large protein-protein interfaces, the possibility of developing classic pharmaceutical inhibitors for long term (and perhaps oral) treatment is still unclear, and additional information about structural interactions and signalling mechanisms is essential.

Electrohydrodynamic Atomization for Improved Macromolecular Drug Delivery

With advances in drug research, the use of biological therapeutics is becoming a reality. Unfortunately, methods for processing and delivering these fragile macromolecules often limit their therapeutic potential. For this dissertation, we explore the aerosolization of macromolecules by way of electrohydrodynamic atomization (EHDA) and how this method can be used to process and deliver therapeutics. EHDA employs a high voltage to break a column of liquid into drops. It was unknown if or how the residual charge left of the resulting droplets would affect lung cells. An in vitro experiment was conducted to spray aerosolized DNA, by way of EHDA, onto human derived lungs cells to test for immunogenic and toxic effects. The lung cells displayed no immunogenic or toxic response to the DNA or high voltage. Previous researchers have used EHDA to aerosolize proteins with mixed results. This work sets forth a simplified thermodynamic theory and provides recommendations to pharmaceutical companies on how to design more stable protein formulations for aerosol processing or delivery. Finally, a new method of producing liposomes was created. It constructs the liposome one layer at a time. The inside of the liposome is sprayed by EHDA, with the lipid and drug in solution together. As the sprayed monolayer passes through a pool containing a solution of lipid in water, the second part of the bilayer attaches to the inner layer creating a complete bilayer liposome.

Network analysis and machine learning assist drug repurposing and safety assessment in neurological diseases

In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.

Bioequivalence Evaluation of Two Different Tablet Formulations of Tinidazole in Healthy Volunteers

The bioequivalence of two different tablet formulations of tirtidazole (CAS 19387-91-8) was determined in healthy volunteers after a single dose in a randomized crossover study, with a 1-week washout period between the doses. Reference and test products were administered to 24 volunteers with 240 mL water after overnight fasting. Plasma concentrations of tinidazole were monitored by a high-performance liquid chromatographic method (HPLC) over a period of 72 h after the administration. The pharmacokinetic parameters AUC(0-t), AUC(0-infinity), C(max), T(max), T((1/2)el) and beta were determined from plasma concentration time profile of both formulations and found to be in good agreement with previously reported values. The calculated pharmacokinetic parameters were compared statistically to evaluate bioequivalence between the two brands. The analysis of variance (ANOVA) did not show any significant difference between the two formulations and 90% confidence intervals for the ratio of C(max) (93.9 - 102.6%), AUC(0-t), (94.9-101.1%) and AUC(0-infinity) (94.6-100.8%) values for the test and reference products were within the 80 - 125% interval, satisfying bioequivalence criteria of the European Committee for Proprietary Medicinal Products and the US Food and Drug Administration Guidelines. These results indicate that the test and the reference products of tinidazole are bioequivalent and, thus, may be prescribed interchangeably.