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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Comparison of efficacy of ginger with various antimotion sickness drugs

Ginger and several other medications were compared with scopolamine and d-amphetamine for effectiveness in prevention of motion sickness. Methods: Double-blind techniques were used. The subjects were given the medications two hours before they were rotated in a chair making head movements until a symptom total short of vomiting was reached. Standardized N.A.S.A. techniques were used for speed of rotation and end-point of motion sickness. Results: The three doses of ginger were all at the placebo level of efficacy. Amitriptyline, ethopropazine and trihexyphenidyl increased the tolerated head movements but the increase was not statistically significant. Significant levels of protection were produced by dimenhydrinate, promethazine, scopolamine and d-amphetamine. Protection was further increased by combination of these latter drugs with d-amphetamine. Efficacy was greatest as the dose was increased. Conclusions: The medication of choice in this study was scopolamine 0.6 mg with d-amphetamine 10 mg. This combination provided good protection with acceptable side effects.

Non-NASA Center↗
NASA NTRS2005

Discovering New Drugs on the Cellular Level

With the Vision for Space Exploration calling for a sustained human presence in space, astronauts will need to grow plants, while in orbit, for nourishment that they will not receive from only consuming dehydrated foods. As a potential source of food for long-duration missions, space-grown plants could also give astronauts an important psychological boost, as fresh vegetables could serve as a welcomed change from monotonous meals consisting of reconstituted foods in plastic bags. Even more, these plants could likely aid in the recycling of air and wastewater on spacecraft. With a helping hand from a company by the name of Biolog, Inc., NASA is studying the impacts of decreased gravity and spaceborne bacteria on the plants being grown for food in space. With a helping hand from NASA, this very same company is creating powerful new cell- and bacteria-analysis tools for use in discovering and developing new drugs on Earth.

Source record↗
NASA NTRS2010

Effectiveness of Needleless Vial Adaptors and Blunt Cannulas for Drug Administration in a Microgravity Environment

Fluid Isolation in the medication vial: Air/ fluid isolation maneuvers were used to move the medication to the septum end of vial. This isolation may be achieved in multiple ways based on the experience of the astronaut with fluid management in microgravity. If vial adaptors/blunt cannula or syringe assembly is inserted into the to vial before fluid isolation commences, the stability of this assembly should be considered in an effort to limit the risk of "slinging off" of the vial during isolation. Alternatively, fluid isolation can be performed prior to attaching the syringe/vial adaptor assembly. Terrestrial practices for medication withdrawal from a nonvented vial require injection of an equivalent amount of air as the expected medication volume prior to withdrawing liquid. In microgravity, this action is still valid, however the injection of additional air into the vial creates a multitude of micro bubbles and increases the volume of medication mixed with air that then must be withdrawn to achieve the desired drug volume in syringe. This practice is more likely to be required when using vials >30ml in size and injection volumes >10mL. It is felt that based on the microgravity flight, the practice of air injection is more of a hindrance than help.

Hailey, M.↗
NASA NTRSDate not supplied

ExMC Ground-Based Space Radiation Analog Pilot Drug Stability Studay: Final Data Review

Uncertainty regarding space radiation effects on medication degradation and potency remains high, though early data suggest that space radiation may affect the potency and quality of some pharmaceuticals. In the absence of empirical spaceflight measurements to characterize this risk area for long-duration planetary missions, high-fidelity ground-based targeted radiation analogs could provide valuable insights. The NASA Human Research Program's (HRP) Exploration Medical Capability (ExMC) Element conducted a pilot study to characterize the chemical stability of four selected medications exposed to rapid switching, mixed-species simulated galactic cosmic radiation (GCR) beams at the NASA Space Radiation Laboratory (NSRL), at Brookhaven National Laboratory (BNL). The research objective was to compare the effects of simulated GCR beam exposures on drug stability to those previously observed following spaceflight.

Vernie R Daniels↗
DOE OSTI2020

DNA-functionalized scaffolds for drug capture applications

This disclosure is directed to structured compositions, including DNA-functionalized scaffolds, for drug capture, and methods and devices for sequestering chemotherapeutics from physiological fluids using the functionalized scaffolds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Advanced drug development and manufacturing

X-ray fluorescence (XRF) spectrometry has been used for detecting binding events and measuring binding selectivities between chemicals and receptors. XRF may also be used for estimating the therapeutic index of a chemical. For estimating the binding selectivities of a chemical versus chemical analogs, for measuring post translational modification of proteins, and for drug manufacturing.

Birnbaum, Eva R.↗
DOE OSTI2021

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. Here, the framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure --- this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Y↗
DOE OSTI2023

HIV-1 protease inhibitors with a P1 phosphonate modification maintain potency against drug-resistant variants by increased interactions with flap residues

Protease inhibitors are the most potent antivirals against HIV-1, but they still lose efficacy against resistant variants. Improving the resistance profile is key to developing more robust inhibitors, which may be promising candidates for simplified next-generation antiretroviral therapies. Here, in this study, we explored analogs of darunavir with a P1 phosphonate modification in combination with increasing size of the P1′ hydrophobic group and various P2′ moieties to improve potency against resistant variants. The phosphonate moiety substantially improved potency against highly mutated and resistant HIV-1 protease variants, but only when combined with more hydrophobic moieties at the P1′ and P2′ positions. Phosphonate analogs with a larger hydrophobic P1′ moiety maintained excellent antiviral potency against a panel of highly resistant HIV-1 variants, with significantly improved resistance profiles. The cocrystal structures indicate that the phosphonate moiety makes extensive hydrophobic interactions with the protease, especially with the flap residues. Many residues involved in these protease-inhibitor interactions are conserved, enabling the inhibitors to maintain potency against highly resistant variants. These results highlight the need to balance inhibitor physicochemical properties by simultaneous modification of chemical groups to further improve resistance profiles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Optimization of key energy and performance metrics for drug product manufacturing

During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors, this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. Here, the results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.

59 BASIC BIOLOGICAL SCIENCES↗