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Experimental study evaluates radioprotective drugs administered before exposure either orally or intravenously. Specifically studied are the sources of radiation, choice of radiation dose, choice of animals, administration of drugs, the toxicity of protective agents and types of protective drug.
The results of a series of antimotion sickness drug evaluations indicates that drugs with central anticholinergic actions and drugs that increase central sympathetic activity are effective against motion sickness. The combination of these actions produces a synergistic effect against motion sickness. The effect of these medications on central acetylcholine or on norepinephrine could alter a balance between the neurons in the vestibular and reticular areas which influence motion sickness and also sympathetic and parasympathetic reactions. It is suggested that this could be their mechanism of action in preventing motion sickness.
The effect of environmental temperature on the toxicity of cyclizine, trimethobenzamide, and Aspirin were studied in mice. LD-50s were compared at 30 C, 22 C, and 15 C. At 30 C the toxicity of all three drugs increased, with that to Aspirin being affected most. Cooling decreased the toxicity of cyclizine and had no significant effect on that of trimethobenzamide or aspirin. These findings indicate that alterations in environmental temperature markedly affect drug toxicity. They emphasize that such alterations, and particularly increases in temperature, do not have to be particularly drastic, but that 'mild' variations in the environment are effective in altering an animal's sensitivity to a drug.
The new drug, AHR 5645B, together with other drugs was evaluated in tests, conducted with eight male subjects, concerning its ability to prevent motion sickness. It was found that AHR 5645B, used in doses of 20, 50, and 100 mg, was not efficacious in preventing experimental motion sickness. A combination of 50 mg meclizine and 25 mg ephedrine sulfate produced the best results. Favorable results were also obtained with a combination of 12.5 mg promethazine hydrochloride and 12.5 mg ephedrine sulfate. The findings in the reported experiment point to the difficulty of identifying a highly efficacious antimotion sickness drug for everyone.
NBOD2, a program developed at Goddard Space Flight Center to solve equations of motion coupled N-body systems is used by E.I. DuPont de Nemours & Co. to model potential drugs as a series of elements. The program analyses the vibrational and static motions of independent components in drugs. Information generated from this process is used to design specific drugs to interact with enzymes in designated ways.
Haploid and diploid cell suspensions of Taxus spp. were examined for their adaptive plasticity in response to simulated microgravity, unit gravity, and hypergravity. Cell suspensions produced the taxane, paclitaxel, (TAXOL (R)), which is useful for the treatment of various cancers. Amyloplasts contributed to taxane ring biosynthesis and to drug release at the cell wall. Drug-producing cells reacted as gravisensing osmotic tensiometers. In stressed cells, amyloplasts docked and fused in clusters to sites on the plasmalemma before taxane discharge into the culture medium. In simulated microgravity and compared to all other treatments, taxane production was reduced nearly 100-fold. The percent paclitaxel of total taxanes remained 3-to 6-fold greater, and biomass doubled. When p53-independent programmed cell death was induced, taxanes were released into the culture medium as free molecules (soluble and insoluble) or bound to membranes, nuclear fragments, xylan residues, and other particulate materials. Unit gravity and especially hypergravity promoted xylogenesis and significant drug overproduction. A model relating families of >touch = (TCH), taxane early response (TER), nuclear cycling, and apoptosis-regulating genes to gravisensing, cell wall modifications, and to taxane recovery accounted for most but not all of the observations.
Dan Carter carefully layered the sheets of tracing paper on the light box. On each sheet were renderings of the atomic components of an essential human protein, one whose structure had long been a mystery. With each layer Carter laid down, a never-before-seen image became clearer. Carter joined NASA s Marshall Space Flight Center in 1985 and began exploring processes of protein crystal growth in space. By bouncing intense X-rays off the crystals, researchers can determine the electron densities around the thousands of atoms forming the protein molecules, unveiling their atomic structures. Cultivating crystals of sufficient quality on Earth was problematic; the microgravity conditions of space were far more accommodating. At the time, only a few hundred protein structures had been mapped, and the methods were time consuming and tedious. Carter hoped his work would help reveal the structure of human serum albumin, a major protein in the human circulatory system responsible for ferrying numerous small molecules in the blood. More was at stake than scientific curiosity. Albumin has a high affinity for most of the world s pharmaceuticals, Carter explains, and its interaction with drugs can change their safety and efficacy. When a medication enters the bloodstream a cancer chemotherapy drug, for example a majority of it can bind with albumin, leaving only a small percentage active for treatment. How a drug interacts with albumin can influence considerations like the necessary effective dosage, playing a significant role in the design and application of therapeutic measures. In spite of numerous difficulties, including having no access to microgravity following the 1986 Space Shuttle Challenger disaster, the image Carter had hoped to see was finally clarifying. In 1988, his lab had acquired specialized X-ray and detection equipment a tipping point. Carter and his colleagues began to piece together albumin s portrait, the formation of its electron densities coalescing on the sheets of tracing paper he arranged on the light box. While space-grown crystals were ultimately not involved in the achievement, a year later, Carter says, we were on the cover of Science magazine, having determined the atomic structure of albumin.
Aims The potential of mechanistic biomarkers to improve prediction of drug‐induced liver injury (DILI) and hepatic regeneration is widely acknowledged. We sought to determine reference intervals for new biomarkers of DILI and regeneration, as well as to characterize their natural variability and impact of diurnal variation. Methods Serum samples from 227 healthy volunteers were recruited as part of a cross‐sectional study; of these, 25 subjects had weekly serial sampling over 3 weeks, while 23 had intensive blood sampling over a 24h period. Alanine aminotransferase (ALT), MicroRNA‐122 (miR‐122), High Mobility Group Box‐1 (HMGB1), total Keratin‐18 (K18), caspase‐cleaved Keratin‐18 (ccK18), Glutamate Dehydrogenase (GLDH) and Macrophage Colony‐Stimulating Factor‐1 (CSF‐1) were assayed. Results Reference intervals were established for each biomarker based on the 97.5% quantile (90% CI) following the assessment of fixed effects in univariate and multivariable models. Intra‐individual variability was found to be non‐significant, and there was no significant impact of diurnal variation. Conclusion Reference intervals for novel DILI biomarkers have been described. An upper limit of a reference range might represent the most appropriate mechanism to utilize these data. These data can now be used to interpret data from exploratory clinical DILI studies and to assist their further qualification as required by regulatory authorities.
This study demonstrates ion focusing at ambient pressure and increased ion signal by creating a voltage gradient from a field-free region to a detector, thereby improving the detection of chemicals, such as explosives and drugs. At ambient pressure, ion loss and resulting signal reduction pose challenges that limit detection sensitivity in analytical instruments. Techniques to increase sensitivity, such as atmospheric flow tube-mass spectrometry (AFT-MS), extend ion-molecule reaction times but result in significant overall ion loss due to diffusion. Ion manipulation techniques, though challenging at ambient pressure, can mitigate these losses by concentrating ions toward the detector inlet. Using SIMION, ion trajectories were modeled with a voltage gradient applied between a flow tube and a detector, revealing ion focusing at ambient pressure. Experimental verification with an atmospheric flow tube employed both mass spectrometry and Faraday plate detectors to measure ion beam profiles across varying flow rates, tube diameters, and voltage gradients. Application of a voltage gradient effectively directed ions to the axial center of the flow tube, narrowed ion beam width, and increased signal intensity by 5 to 10 times compared to conditions without a voltage gradient. This ion focusing approach shows promise for improving sensitivity in ambient-pressure instruments. This technique has the potential to enhance detection levels in security and forensic applications, with particular benefits for field-portable devices used at checkpoints to identify explosives and drugs.
Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.
Medications have been a part of space travel dating back as far as the Apollo missions. Currently, medical kits aboard the ISS contain medications and supplies to help crew members cope with a variety of possible medical events. NASA reported that 1,867 medical events occurred from 1981 to 1998 on space shuttle flights, STS-1 to STS-89; 498 out of the 508 crewmembers on those flights reported experiencing a medical event other than space motion sickness. In 2000, the Institute of Medicine (IOM) convened a committee of experts, Committee on Creating a Vision for Space Medicine during Travel beyond Earth Orbit, to examine the issues surrounding astronaut health and safety for long duration space missions. The primary theme of the committee’s final report is that there is not enough known about the risks to human health during long-duration missions beyond Earth’s orbit and ways to effectively mitigate those risks in an environment of deep space. In 2014, the IOM convened the Committee on Ethics Principles and Guidelines for Health Standards for Long Duration and Exploration Spaceflights and released a report emphasizing the importance of prevention, mitigation, and treatment of major risks to human health during exploration spaceflight. NASA’s Human Research Program has organized five distinct categories of spaceflight hazards summarized by the acronym “RIDGE” (Space Radiation, Isolation and Confinement, Distance from Earth, Gravity fields, and Hostile/Closed Environments) that astronauts may encounter during exploration spaceflight. From those hazards, NASA further derived 30 of the most critical human health and performance risks, including limits to medical care resulting from pharmaceutical degradation. As we prepare for more distant exploration missions to Mars and beyond, risk management planning for astronaut healthcare should include the assembly of a medication formulary that is comprehensive enough to prevent or treat anticipated medical events, remains safe and chemically stable, and retains sufficient potency to last for the duration of the mission. The present editorial will summarize the current state of knowledge regarding innovative formulary optimization strategies, pharmaceutical stability assessment techniques, and storage and packaging solutions that could enhance drug safety and efficacy for future exploration spaceflight missions.
The sensitivity of LC-MS in quantifying target proteins in plasma/tissues is significantly hindered by co-eluted matrix interferences. While antibody-based immuno-enrichment effectively reduces interferences, developing and optimizing antibodies are often time-consuming and costly. Here, in this study, by leveraging the orthogonal separation capability of Field Asymmetric Ion Mobility Spectrometry (FAIMS), we developed a FAIMS/differential-compensation-voltage (FAIMS/dCV) method for antibody-free, robust, and ultra-sensitive quantification of target proteins directly from plasma/tissue digests. By comparing the intensity-CV profiles of the target vs. co-eluted endogenous interferences, the FAIMS/dCV approach identifies the optimal CV for quantification of each target protein, thus maximizing the signal-to-noise ratio (S/N). Compared to quantification without FAIMS, this technique dramatically reduces endogenous interferences, showing a median improvement of the S/N by 14.8-fold for the quantification of 17 representative protein drugs and biomarkers in plasma or tissues and a 5.2-fold median increase in S/N over conventional FAIMS approach, which uses the peak CV of each target. We also discovered that the established CV parameters remain consistent over months and are matrix-independent, affirming the robustness of the developed FAIMS/dCV method and the transferability of the method across matrices. The developed method was successfully demonstrated in three applications: the quantification of monoclonal antibodies with sub-ng/mL LOQ in plasma, an investigation of the time courses of evolocumab and its target PCSK9 in a preclinical setting, and a clinical investigation of low abundance obesity-related biomarkers. This innovative and easy-to-use method has extensive potential in clinical and pharmaceutical research, particularly where sensitive and high-throughput quantification of protein drugs and biomarkers is required.
Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel Na V 1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to Na V 1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.
ABSTRACT Introduction Extensive trauma, commonly seen in wounded military Service Members, often leads to a severe sterile inflammation termed systemic inflammatory response syndrome (SIRS), which can progress to multiple organ dysfunction syndrome (MODS) and death. MODS is a serious threat to wounded Service Members, historically causing 10% of all deaths in trauma admissions at a forward deployed combat hospital. The importance of this problem will be exacerbated in large-scale combat operations, in which evacuation will be delayed and care of complex injuries at lower echelons of care may be prolonged. The main goal of this study was to optimize an existing mouse model of lethal SIRS/MODS as a therapeutic screening platform for the evaluation of immunomodulatory drugs. Materials and Methods Male C57BL/6 mice were euthanized, and the bones and muscles were collected and blended into a paste termed tissue–bone matrix (TBX). The TBX at 12.5%–20% relative to body weight of each recipient mouse was implanted into subcutaneous pouches created on the dorsum of anesthetized animals. Mice were observed for clinical scores for up to 48 hours postimplantation and euthanized at the preset point of moribundity. To test effects of anesthetics on TBX-induced mortality, animals received isoflurane or ketamine/xylazine (K/X). In a separate set of studies, mice received TBX followed by intraperitoneal injection with 20 mg/kg or 40 mg/kg Eritoran or a placebo carrier. All Eritoran studies were performed in a blinded fashion. Results We observed that K/X anesthesia significantly increased the lethality of the implanted TBX in comparison to inhaled anesthetics. Although all the mice anesthetized with isoflurane and implanted with 12.5% TBX survived for 24 hours, 60% of mice anesthetized with K/X were moribund by 24 hours postimplantation. To mimic more closely the timing of lethal SIRS/MODS following polytrauma in human patients, we extended observation to 48 hours. We performed TBX dose–response studies and found that as low as 15%, 17.5%, and 20% TBX caused moribundity/mortality in 50%, 80%, and 100% mice, respectively, over a 48-hour time period. With 17.5% TBX, we tested if moribundity/mortality could be rescued by anti-inflammatory drug Eritoran, a toll-like receptor 4 antagonist. Neither 20 mg/kg nor 40 mg/kg doses of Eritoran were found to be effective in this model. Conclusions We optimized a TBX mouse model of SIRS/MODS for the purpose of evaluating novel therapeutic interventions to prevent trauma-related pathophysiologies in wounded Service Members. Negative effects of K/X on lethality of TBX should be further evaluated, particularly in the light of widespread use of ketamine in treatment of pain. By mimicking muscle crush, bone fracture, and necrosis, the TBX model has pleiotropic effects on physiology and immunology that make it uniquely valuable as a screening tool for the evaluation of novel therapeutics against trauma-induced SIRS/MODS.
The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we plan to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We also plan to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task to identify pan-coronavirus protease inhibitors such as SARS-CoV-2. While the overall goals and milestones remain consistent with the original proposal, certain technical details have been modified, which we will describe in this report.
This report documents results assessing the presence of Naturally Occurring Radioactive Material (NORM) in illicit drugs using high-resolution gamma spectroscopy. Specifically, high-purity germanium (HPGe) measurements were conducted at the Drug Enforcement Administration (DEA) South Central Laboratory on 11 samples (referred to as exhibits) including cocaine, fentanyl, heroin, ketamine, LSD, marijuana, methamphetamines, psilocybin mushrooms, and synthetic cannabinoids.
The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.
The statutory standards underlying the activities of the FDA, and the problems the Agency faces in decision making are discussed from a legal point of view. The premarketing clearance of new drugs and of food additives, the two most publicized and criticized areas of FDA activity, are used as illustrations. The importance of statutory standards in technology assessment in a regulatory setting is developed. The difficulties inherent in the formulation of meaningful standards are recognized. For foods, the words of the statute are inadequate, and for drugs, a statutory recognition of the various other objectives would be useful to the regulator and the regulated.