Role of artificial intelligence in drug development

In the last decade, artificial intelligence (AI) has revolutionised the field of drug research. Staff abilities (55 percent), data structure (52 percent), and resources were all factors in AI deployment (49 percent ). Nearly 60% of respondents said they expected to hire more people in the next two years to assist AI usage or adoption in drug development. AI in areas like as drug research and development, drug repurposing, boosting pharmaceutical productivity, and clinical trials, among others, minimises human effort and allows for the achievement of objectives in a short amount of time. On the one hand, AI techniques used in drug development bring the drug development process and the use of various models closer to medicinal chemists, while on the other hand, AI methods used in drug development bring the drug development process and the use of various models closer to mathematicians

Techno-economic, energy, and exergy analyses of invasive weed gasification for hydrogen enriched producer gas production

This research work deals with the examination of the techno-economic, exergy, and energy analyses of biomass gasification of the invasive weed Parthenium hysterophorus (PHP) using Steam - Carbon dioxide (CO2) as a gasifying agent with the support of simulation modeling for sustainable energy conversion process. The aim of this work is to simulate the gasification process through consideration of the impacts of various operating factors on gasification. This study attains the gradual increase in hydrogen (H2) concentration from 51% to 63% along with the rise in carbon monoxide (CO) from 14.5% to 19% using Aspen Plus simulation. CO2 falls concurrently from 24% to 13.5%. The findings demonstrate significant advancements over earlier studies in terms of both gas composition and overall system performance. A computational model has been developed for the estimation of energy performance indicators such as total energy input, and energy consumed per mass of biomass gasified, which are used in the determination of the system's energy efficiency. The exergy analysis of the system is performed to assess the system's total losses in terms of efficiency gathered from the system's exergy ratios. The economic analysis evaluates the system's economies of scale by gas production at ₹.15/kg and long-term sustainability. The proposed system has been found with the potential to produce a high yield of alternative energy from PHP with increased economic efficiency and lower environmental impact

Formulation and evaluation of herbal face cream with green tea extract

Face cream is a semi-solid preparation for improving skin colour. The purposes of the present research work was to formulate and evaluate herbal face cream with green tea extract, turmeric, aloe vera gel as a skin toner. Herbal creams offer several advantages over synthetic creams. The majority of existing creams which has prepared from drugs of synthetic origin and gives extras fairness to face, but it has several side effects such as itching or several allergic reactions. Herbal creams do not have any of these side effects, without side effects it gives the nourishment to skin. Method carried out to prepare herbal cream was vanishing cream formulation. Firstly, oil phase was prepared, Secondly aqueous phase was prepared. Then aqueous phase was added into the oil phase at 700 c with continuous stirring. Now, once the transfer was completed it was allowed to come at room temperature all the while being stirred. Perfume was added at last just before the finished product was transferred to suitable container. The above prepared herbal cream was evaluated with parameters such as pH, homogeneity by visual and by touch, appearance (colour), rub out (spread ability, wetness), washability, consistency and emolliency. The study suggests that the composition of extract and the base of the cream F1 are more stable and safe

Application of nanotechnology in antimicrobial finishing of biomedical textiles

In recent years, the antimicrobial nanofinishing of biomedical textiles has become a very active, high-growth research field, assuming great importance among all available material surface modifications in the textile industry. This review offers the opportunity to update and critically discuss the latest advances and applications in this field. The survey suggests an emerging new paradigm in the production and distribution of nanoparticles for biomedical textile applications based on non-toxic renewable biopolymers such as chitosan, alginate and starch. Moreover, a relationship among metal and metal oxide nanoparticle (NP) size, its concentration on the fabric, and the antimicrobial activity exists, allowing the optimization of antimicrobial functionality.Andrea Zille (C2011-UMINHO-2C2T-01) acknowledges funding from Programa Compromisso para a Ciencia 2008, Portugal

Biosynthesis of Gold Nanoparticles by Foliar Broths: Roles of Biocompounds and Other Attributes of the Extracts

Biosynthesis of nanoparticles has arisen as a promising alternative to conventional synthetic methodologies owing to its eco-friendly advantages, and the involved bioprotocol still needs further clarification. This research, for the first time from the standpoint of statistics, confirmed an electrostatic force or ionic bond-based interaction between the chloroauric ions and the involved bioconstituents and manifested that reducing sugars and flavonoids were both important reductants responsible for conversion of Au(III) to Au(0). The result also demonstrated that the proteins were not the reducing agents, yet they might be protection agents in biosynthesis of gold nanoparticles (GNPs). Besides, a significant linear relationship was found between the anti-oxidant ability of the foliar broths and their capability to reduce Au(III) into Au(0). Furthermore, the preliminary investigation based on the boxplot on the size/shape distribution of the biosynthesized GNPs revealed that gold nanospheres with higher degree of homogeneity in size tended to be promoted by foliar broths containing higher content of reducing sugars/flavonoids and proteins. Otherwise, i.e., for those broths with lower content of the above biocompounds, sphere GNPs of wider size distribution or even gold nanotriangles tended to be fabricated

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery