Title: Pharmacological Effects of Cannabinoids Extracted from Industrial hemp on Epilepsy
Epilepsy is a disease caused by abnormal brain activity due to disturbed nerve cell activity. It is the fourth most common neurological disorder. Only about 7 out of 10 individuals with epilepsy are successfully treated using anti-epileptic drugs. In the pharmaceutical industry, there has been a growing demand for cannabinoids from Cannabis sativa, commonly known as marijuana, for therapeutic, clinical, and nutraceutical supplements. More recently, the legalization of marijuana for clinical research has allowed to further explore the efficacy in the treatment of several neurological disorders like epilepsy. Unlike opioids, cannabinoids are not psychoactive, making it a potentially more favorable therapeutic drug. Most studies showing the efficacy of Cannabis as a treatment strategy point to the pain management associated with the binding of endocannabinoid G coupled protein receptors CB1 and CB2. Though there are cannabinoid therapeutic drugs like Epidiolex approved by the Food and Drug Administration (FDA), plant-based natural compounds are safer, and effective with no side effects. more »« less
Czuppon, Peter; Débarre, Florence; Gonçalves, Antonio; Tenaillon, Olivier; Perelson, Alan S.; Guedj, Jérémie; Blanquart, François
(, PLOS Computational Biology)
Faeder, James R.
(Ed.)
Repurposed drugs that are safe and immediately available constitute a first line of defense against new viral infections. Despite limited antiviral activity against SARS-CoV-2, several drugs are being tested as medication or as prophylaxis to prevent infection. Using a stochastic model of early phase infection, we evaluate the success of prophylactic treatment with different drug types to prevent viral infection. We find that there exists a critical efficacy that a treatment must reach in order to block viral establishment. Treatment by a combination of drugs reduces the critical efficacy, most effectively by the combination of a drug blocking viral entry into cells and a drug increasing viral clearance. Below the critical efficacy, the risk of infection can nonetheless be reduced. Drugs blocking viral entry into cells or enhancing viral clearance reduce the risk of infection more than drugs that reduce viral production in infected cells. The larger the initial inoculum of infectious virus, the less likely is prevention of an infection. In our model, we find that as long as the viral inoculum is smaller than 10 infectious virus particles, viral infection can be prevented almost certainly with drugs of 90% efficacy (or more). Even when a viral infection cannot be prevented, antivirals delay the time to detectable viral loads. The largest delay of viral infection is achieved by drugs reducing viral production in infected cells. A delay of virus infection flattens the within-host viral dynamic curve, possibly reducing transmission and symptom severity. Thus, antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk.
Abstract Most diseases disrupt multiple proteins, and drugs treat such diseases by restoring the functions of the disrupted proteins. How drugs restore these functions, however, is often unknown as a drug’s therapeutic effects are not limited to the proteins that the drug directly targets. Here, we develop the multiscale interactome, a powerful approach to explain disease treatment. We integrate disease-perturbed proteins, drug targets, and biological functions into a multiscale interactome network. We then develop a random walk-based method that captures how drug effects propagate through a hierarchy of biological functions and physical protein-protein interactions. On three key pharmacological tasks, the multiscale interactome predicts drug-disease treatment, identifies proteins and biological functions related to treatment, and predicts genes that alter a treatment’s efficacy and adverse reactions. Our results indicate that physical interactions between proteins alone cannot explain treatment since many drugs treat diseases by affecting the biological functions disrupted by the disease rather than directly targeting disease proteins or their regulators. We provide a general framework for explaining treatment, even when drugs seem unrelated to the diseases they are recommended for.
Evans S.R.; Follmann D.; Liu Y.; Holland T.; Doernberg S.B.; Rouphael N.; Hamasaki T.; Jiang Y.; Lok J.J.; Tran T.T.T.; et al
(, Clinical infectious diseases)
Patient management is not based on a single decision. Rather, it is dynamic: based on a sequence of decisions, with therapeutic adjustments made over time. Adjustments are personalized: tailored to individual patients as new information becomes available. However, strategies allowing for such adjustments are infrequently studied. Traditional antibiotic trials are often nonpragmatic, comparing drugs for definitive therapy when drug susceptibilities are known. COMparing Personalized Antibiotic StrategieS (COMPASS) is a trial design that compares strategies consistent with clinical practice. Strategies are decision rules that guide empiric and definitive therapy decisions. Sequential, multiple-assignment, randomized (SMART) COMPASS allows evaluation when there are multiple, definitive therapy options. SMART COMPASS is pragmatic, mirroring clinical, antibiotic-treatment decision-making and addressing the most relevant issue for treating patients: identification of the patient-management strategy that optimizes the ultimate patient outcomes. SMART COMPASS is valuable in the setting of antibiotic resistance, when therapeutic adjustments may be necessary due to resistance.
Finley, Sheree J; Javan, Gulnaz T; Green, Robert L.
(, Frontiers in microbiology)
null
(Ed.)
Forensic laboratories are required to have analytical tools to confidently differentiate illegal substances such as marijuana from legal products (i.e., industrial hemp). The Achilles heel of industrial hemp is its association with marijuana. Industrial hemp from the Cannabis sativa L. plant is reported to be one of the strongest natural multipurpose fibers on earth. The Cannabis plant is a vigorous annual crop broadly separated into two classes: industrial hemp and marijuana. Up until the eighteenth century, hemp was one of the major fibers in the United States. The decline of its cultivation and applications is largely due to burgeoning manufacture of synthetic fibers. Traditional composite materials such as concrete, fiberglass insulation, and lumber are environmentally unfavorable. Industrial hemp exhibits environmental sustainability, low maintenance, and high local and national economic impacts. The 2018 Farm Bill made way for the legalization of hemp by categorizing it as an ordinary agricultural commodity. Unlike marijuana, hemp contains less than 0.3% of the cannabinoid, Δ9-tetrahydrocannabinol, the psychoactive compound which gives users psychotropic effects and confers illegality in some locations. On the other hand, industrial hemp contains cannabidiol found in the resinous flower of Cannabis and is purported to have multiple advantageous uses. There is a paucity of investigations of the identity, microbial diversity, and biochemical characterizations of industrial hemp. This review provides background on important topics regarding hemp and the quantification of total tetrahydrocannabinol in hemp products. It will also serve as an overview of emergent microbiological studies regarding hemp inflorescences. Further, we examine challenges in using forensic analytical methodologies tasked to distinguish legal fiber-type material from illegal drug-types.
Song, L.; Pathipaka, S.B.; Leese, J.D.; Chao, M.; Collins, T.; Westein, J.P.
(, 2020 American Academy of Forensic Sciences Annual Scientific Meeting)
After attending this presentation, attendees will gain knowledge in the strategy to achieve high-throughput and simultaneous analysis of cannabinoids and appreciate a validated LC-UV method for analysis of twelve cannabinoids in hemp oil. This presentation will first impact the forensic science community by introducing three fast LC separations of twelve cannabinoids that can be used with either UV or mass spectrometric (MS) detection. It will further impact the forensic science community by introducing a validated LC-UV method for high-throughput and simultaneous analysis of twelve cannabinoids in hemp oil, which can be routinely used by cannabis testing labs. In recent years, the use of products of Cannabis sativa L. for medicinal purposes has been in a rapid growth, although their preparation procedure has not been clearly standardized and their quality has not been well regulated. To analyze the therapeutic components, i.e. cannabinoids, in products of Cannabis sativa L., LC-UV has been frequently used, because LC-UV is commonly available and usually appropriate for routine analysis by the cannabis growers and commercial suppliers. In the literature, a few validated LC-UV methods have been described. However, so far, all validated LC-UV methods only focused in the quantification of eleven or less cannabinoids. Therefore, a method able to simultaneously analyze more cannabinoids in a shorter run time is still in high demand, because more and more cannabinoids have been isolated and many of them have shown medicinal properties. In this study, the LC separation of twelve cannabinoids, including cannabichromene (CBC), cannabidiolic acid (CBDA), cannabidiol (CBD), cannabidivarinic acid (CBDVA), cannabidivarin (CBDV), cannabigerolic acid (CBGA), cannabigerol (CBG), cannabinol (CBN), delta-8 tetrahydrocannabinol (Δ8-THC), delta-9 tetrahydrocannabinolic acid A (Δ9-THCA A), delta-9 tetrahydrocannabinol (Δ9-THC), and tetrahydrocannabivarin (THCV), has been systematically optimized using a Phenomenex Luna Omega 3 µm Polar C18 150 mm × 4.6 mm column with regard to the effects of the type of organic solvent, i.e. methanol and acetonitrile, the content of the organic solvent, and the pH of the mobile phase. The optimization has resulted in three LC conditions at 1.0 mL/minute able to separate the twelve cannabinoids: 1) a mobile phase consisting of water and methanol, both containing 0.1% formic acid (pH 2.69), with a gradient elution at 75% methanol for the first 3 minutes and then linearly increase to 100% methanol at 12.5 minutes; 2) a mobile phase consisting of water and 90% (v/v) acetonitrile in water, both containing 0.1% formic acid and 20 mM ammonium formate (pH 3.69), with an isocratic elution at 75% acetonitrile for 14 minutes; and 3) a mobile phase consisting of water and 90% (v/v) acetonitrile in water, both containing 0.03% formic acid and 20 mM ammonium formate (pH 4.20), with an isocratic elution at 75% acetonitrile for 14 minutes. In order to demonstrate the effectiveness of the achieved LC separations, a LC-UV method is further validated for the high-throughput and simultaneous analysis of twelve cannabinoids. The method used the mobile phase at pH 3.69, which resulted in significant improvement in throughput compared to other validated LC-UV methods published so far. The method used flurbiprofen as the internal standard. The linear calibration range of all the cannabinoids were between 0.1 to 25 ppm with R2≥0.9993. The LOQ (S/N=10) of the cannabinoids was between 17.8 and 74.2 ppb. The validation used a hemp oil containing 3.2 wt% CBD and no other cannabinoids, which was reported by the vendor with a certificate of analysis, as the matrix to prepare control samples: the hemp oil was first extracted using liquid-liquid extraction (LLE) with methanol; cannabinoids were then spiked into the extract at both 0.5 ppm and 5 ppm level. Afterwards, the recovery, precision (%RSD) and accuracy (%Error) of the control samples were assessed and the results met the requirements by the ISO/IEC 17025 and ASTM E2549-14 guidelines.
Patel, Aayushi, Agili-Shaban, Ruba, Patel, Shrina, Proano, Renata, Riarh, Fatima, Hasan, Eman, Potlakayala, Shobha, and Rudrabhatla, Sairam. Pharmacological Effects of Cannabinoids Extracted from Industrial hemp on Epilepsy. Retrieved from https://par.nsf.gov/biblio/10557713. . Journal of Pharmacy and Pharmacology Research .6
Patel, Aayushi, Agili-Shaban, Ruba, Patel, Shrina, Proano, Renata, Riarh, Fatima, Hasan, Eman, Potlakayala, Shobha, and Rudrabhatla, Sairam.
"Pharmacological Effects of Cannabinoids Extracted from Industrial hemp on Epilepsy". . Journal of Pharmacy and Pharmacology Research (6). Country unknown/Code not available: Oxford Academic. https://par.nsf.gov/biblio/10557713.
@article{osti_10557713,
place = {Country unknown/Code not available},
title = {Pharmacological Effects of Cannabinoids Extracted from Industrial hemp on Epilepsy},
url = {https://par.nsf.gov/biblio/10557713},
abstractNote = {Epilepsy is a disease caused by abnormal brain activity due to disturbed nerve cell activity. It is the fourth most common neurological disorder. Only about 7 out of 10 individuals with epilepsy are successfully treated using anti-epileptic drugs. In the pharmaceutical industry, there has been a growing demand for cannabinoids from Cannabis sativa, commonly known as marijuana, for therapeutic, clinical, and nutraceutical supplements. More recently, the legalization of marijuana for clinical research has allowed to further explore the efficacy in the treatment of several neurological disorders like epilepsy. Unlike opioids, cannabinoids are not psychoactive, making it a potentially more favorable therapeutic drug. Most studies showing the efficacy of Cannabis as a treatment strategy point to the pain management associated with the binding of endocannabinoid G coupled protein receptors CB1 and CB2. Though there are cannabinoid therapeutic drugs like Epidiolex approved by the Food and Drug Administration (FDA), plant-based natural compounds are safer, and effective with no side effects.},
journal = {. Journal of Pharmacy and Pharmacology Research},
number = {6},
publisher = {Oxford Academic},
author = {Patel, Aayushi and Agili-Shaban, Ruba and Patel, Shrina and Proano, Renata and Riarh, Fatima and Hasan, Eman and Potlakayala, Shobha and Rudrabhatla, Sairam},
}
Warning: Leaving National Science Foundation Website
You are now leaving the National Science Foundation website to go to a non-government website.
Website:
NSF takes no responsibility for and exercises no control over the views expressed or the accuracy of
the information contained on this site. Also be aware that NSF's privacy policy does not apply to this site.