Test Animals Research Articles

Biofabricated 3D Intestinal Models as an Alternative to Animal-Based Approaches for Drug Toxicity Assays.

The main challenge in new drug development is accurately predicting the human response in preclinical models. In this study, we developed three different intestinal barrier models using advanced biofabrication techniques: (i) a manual model containing Caco-2 and HT-29 cells on a collagen bed, (ii) a manual model with a Caco-2/HT-29 layer on a HDFn-laden collagen layer, and (iii) a 3D bioprinted model incorporating both cellular layers. Each model was rigorously tested for its ability to simulate a functional intestinal membrane. All models successfully replicated the structural and functional aspects of the intestinal barrier. The 3D bioprinted intestinal model, however, demonstrated superior epithelial barrier integrity enhanced tight junction formation, microvilli development, and increased mucus production. When subjected to Ibuprofen, the 3D bioprinted model provided a more predictive response, underscoring its potential as a reliable in vitro tool for drug toxicity testing. Our 3D bioprinted intestinal model presents a robust and predictive platform for drug toxicity assessments, significantly reducing the need for animal testing. This model not only aligns with ethical testing protocols but also offers enhanced accuracy in predicting human responses, thereby advancing the field of drug development.

Potentially probiotic NPL 1334 strain of Enterococcus durans benefits rats with diet-induced hypercholesterolemia

PurposeTo study the potential of a candidate probiotic strain belonging to the Enterococcus durans species in alleviating hypercholesterolemia and improving the microbial milieu of rat gut.MethodsA previously isolated and characterized E. durans strain NPL 1334 was further screened in vitro for its bile salt hydrolyzation and cholesterol assimilation ability. An in vivo trial using diet-induced hypercholesterolemic rats was conducted to evaluate the effects of the administered test probiotic strain on the animal’s blood biochemical parameters such as total cholesterol (TC), high-density lipopolysaccharides (HDL), low-density lipopolysaccharides (LDL), triglycerides (TG), on body weight, oxidative stress markers, and its impact on intestinal and fecal microbiota as well as a histopathological examination of the test animal’s livers.ResultsE. durans strain showed good bile salt hydrolyzing ability and ample cholesterol assimilation in vitro. Probiotic-fed hypercholesterolemic rats showed significantly lowered cholesterol, triglyceride and LDL levels. The body weight of probiotic-fed rats was reduced as compared to the control. E. durans also stimulated the growth of beneficial LAB in the intestine of experimental rats and did not harm the liver of the experimental rats.ConclusionE. durans can be a natural therapeutic alternative to manage diet-induced hypercholesterolemia and may eventually enhance anti-cholesterolemic therapies.

Comparison of in vitro transcriptomic points of departure with fish acute and chronic toxicity values: A case study of rainbow trout cells exposed to pesticides.

There is growing interest in transcriptomic points of departure (tPOD) values from in vitro experiments as an alternative to animal test method. The study objective was to calculate tPODs in rainbow trout gill cells (RTgill-W1 following OECD 249) exposed to pesticides, and to evaluate how these values compare to fish acute and chronic toxicity data. Cells were exposed to one fungicide (chlorothalonil), ten herbicides (atrazine, glyphosate, imazethapyr, metolachlor, diquat, s-metolachlor, AMPA, dicamba, dimethenamid-P, metribuzin), eight insecticides (chlorpyrifos, diazinon, permethrin, carbaryl, clothianidin, imidacloprid, thiamethoxam, chlorantraniliprole), and OECD 249 positive control 3,4-dichloroaniline. Pesticide concentrations in wells were modeled with IV-MBM EQP v2.1. Sequencing libraries were prepared with UPXome, and tPODs calculated with ExpressAnalyst. The method identified 14,449 unique genes, with 1,115 genes having >5 counts in the 576 samples sequenced. For all chemicals, tPODs were derived and tPOD mode values ranged from 0.0004 to 125µM with an average of 36µM. There were significant correlations between tPOD mode values (x-value) and EC50s from RTgill-W1 cells (y = 0.92x+1.2, R2=0.9, p < 0.00001; n = 11), rainbow trout acute toxicity LC50s (y = 0.81x+0.8, R2=0.63, p < 0.0001; n = 20), fish chronic sub-lethal effect concentrations (y = 0.53x-0.2, R2=0.4, p = 0.009; n = 16) and fish chronic lethal effect concentrations (y = 0.64x-0.023, R2=0.59, p = 0.0013; n = 14). Bland-Altman plot analyses of these comparisons also showed good agreement. Pathway-level benchmark doses were calculated when statistical requirements were met, and only possible for four pesticides. These findings support the notion that tPODs from short-term in vitro studies may be comparable to effect concentration data from in vivo studies of fish exposed for chronic durations.

Smart Polymeric 3D Microscaffolds Hosting Spheroids for Neuronal Research via Quantum Metrology.

Toward the aim of reducing animal testing, innovative in vitro models are required. Here, this study proposes a novel smart polymeric microscaffold to establish an advanced 3D model of dopaminergic neurons. These scaffolds are fabricated with Ormocomp via Two-Photon Polymerization. The scaffolds are further enhanced by functionalization with fluorescent nanodiamonds (FNDs), which can serve as quantum nanosensors for both magnetic and temperature sensing.The material biocompatibility is tested using two different cell lines, SH-SY5Y and A431, with cell viability over 98%. A total of 69% of the FNDs are grafted on the structure compared to those that remained on the glass surface. Cells are tested with the scaffolds in several microenvironments, and the final assembly required for 3D quantum metrology experiments achieved 91% biocompatibility. Subsequently, embryoid bodies containing dopaminergic neurons, the cell type affected by Parkinson's disease (PD), are integrated with FND-functionalized scaffolds. This 3D model is successfully established, demonstrated by strong interactions between dopaminergic neurons and the scaffold, with the directional growth of neurites along the 3D scaffold. Ultimately, this study have developed a 3D platform that enables the readout of signaling in a model that holds great potential for future PD research.

Artificial Intelligence in Computer-Aided Drug Design (CADD) Tools for the Finding of Potent Biologically Active Small Molecules: Traditional to Modern Approach.

Computer-Aided Drug Design (CADD) entails designing molecules that could potentially interact with a specific biomolecular target and promising their potential binding. The stereo- arrangement and stereo-selectivity of small molecules (SMs)--based chemotherapeutic agents significantly influence their therapeutic potential and enhance their therapeutic advantages. CADD has been a well-established field for decades, but recent years have observed a significant shift toward acceptance of computational approaches in both academia and the pharmaceutical industry. Recently, artificial intelligence (AI), bioinformatics, and data science have played a significant role in drug discovery to accelerate the development of effective treatments, reduce expenses, and eliminate the need for animal testing. This shift can be attributed to the availability of extensive data on molecular properties, binding to therapeutic targets, and their 3D structures. Increasing interest from legislators, pharmaceutical companies, and academic and industrial scientists is evidence that AI is reshaping the drug discovery industry. To achieve success in drug discovery, it is necessary to optimize pharmacodynamic, pharmacokinetic, and clinical outcome-related properties. Moreover, the advent of on-demand virtual libraries containing billions of drug-like SMs, coupled with abundant computing capacities, has further facilitated this transition. To fully capitalize on these resources, rapid computational methods are needed for effective ligand screening. This includes structure-based virtual screening (SBVS) of vast chemical spaces, aided by fast iterative screening approaches. At the same time, advances in deep learning (DL) predictions of ligand properties and target activities have become very helpful, as they no longer need information about the structure of the receptor. This study examines recent progress in the drug discovery and development (DDD) approach, their potential to reshape the entire DDD process, and the challenges they face. This review examines the role of artificial intelligence as a fundamental component in drug discovery, particularly focusing on small molecules. It also discusses how AI-driven approaches can expedite the identification of diverse, potent, target-specific, and drug-like ligands for protein targets. This advancement has the potential to make drug discovery more efficient and cost-effective, ultimately facilitating the development of safer and more effective therapeutics.

Industrial Automation using Artificial Intelligence

The pharmaceutical and consumer healthcare industries have been greatly impacted by artificial intelligence and machine learning. A subfield of computer science called artificial intelligence is able to analyze intricate medical data. The goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem solving, and decision making. AI is becoming more and more significant in many areas of pharmacy, including drug discovery and formulation of drug delivery, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies growth. This review focuses on the significant applications of AI in various pharmaceutical domains, including drug development and discovery, Many studies are being conducted to enhance the AI technology that is currently available in order to increase the efficiency of the pharmacy profession. Artificial intelligence and system mastery have seen a significant upsurge in recent years. It has lessened the effort required of humans to advance in their extraordinary lives. Numerous drug discovery implementations have been examined, demonstrating the technology's effectiveness in quantitative structure-property relationships (QSPR) and quantitative structure-activity relationships (QSAR). Additionally, they are employed in clinical trials to generate and interpret data gathered from patient information. The pharmaceutical industry is currently having trouble maintaining its drug development programs due to rising R&amp;D expenses and declining productivity. In addition to helping with experimental design, machine learning algorithms can forecast the toxicity and pharmacokinetics of potential drugs. This capability lessens the need for extensive and expensive animal testing by enabling the prioritization and optimization of lead compounds. Artificial intelligence (AI) algorithms that examine actual patient data can support personalized medicine strategies, improving patient adherence and treatment outcomes

Development Validation of UV Spectrophoto Meter Method for Determination of Polyherbal Powder

The pharmaceutical and consumer healthcare industries have been greatly impacted by artificial intelligence and machine learning. A subfield of computer science called artificial intelligence is able to analyze intricate medical data. The goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem solving, and decision making. AI is becoming more and more significant in many areas of pharmacy, including drug discovery and formulation of drug delivery, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies growth. This review focuses on the significant applications of AI in various pharmaceutical domains, including drug development and discovery, Many studies are being conducted to enhance the AI technology that is currently available in order to increase the efficiency of the pharmacy profession. Artificial intelligence and system mastery have seen a significant upsurge in recent years. It has lessened the effort required of humans to advance in their extraordinary lives. Numerous drug discovery implementations have been examined, demonstrating the technology's effectiveness in quantitative structure-property relationships (QSPR) and quantitative structure-activity relationships (QSAR). Additionally, they are employed in clinical trials to generate and interpret data gathered from patient information. The pharmaceutical industry is currently having trouble maintaining its drug development programs due to rising R&amp;D expenses and declining productivity. In addition to helping with experimental design, machine learning algorithms can forecast the toxicity and pharmacokinetics of potential drugs. This capability lessens the need for extensive and expensive animal testing by enabling the prioritization and optimization of lead compounds. Artificial intelligence (AI) algorithms that examine actual patient data can support personalized medicine strategies, improving patient adherence and treatment outcomes

Dynamics in zebrafish development define transcriptomic specificity after angiogenesis inhibitor exposure.

Testing for developmental toxicity is an integral partof chemical regulations. The applied tests are laborious and costly and require a large number of vertebrate test animals. To reduce animal numbers and associated costs, the zebrafish embryo was proposed as an alternative model. In this study, we investigated the potential of transcriptome analysis in the zebrafish embryo model to support the identification of potential biomarkers for key events in developmental toxicity, using the inhibition of angiogenesis as a proof of principle. Therefore, the effects on the zebrafish transcriptome after exposure to the tyrosine kinase inhibitors, sorafenib (1.3µM and 2.4µM) and SU4312 (1µM, 2µM, and 5µM), and the putative vascular disruptor compound rotenone (25nM and 50nM) were analyzed. An early (2hpf-hours post fertilization) and a late (24hpf) exposure start with a time resolved transcriptome analysis was performed to compare the specificity and sensitivity of the responses with respect to anti-angiogenesis. We also showed that toxicodynamic responses were related to the course of the internal concentrations. To identify differentially expressed genes (DEGs) the time series data were compared by applying generalized additive models (GAMs). We observed mainly unspecific developmental toxicity in the early exposure scenario, while a specific repression of vascular related genes was only partially observed. In contrast, differential expression of vascular-related genes could be identified clearly in the late exposure scenario. Rotenone did not show angiogenesis-specific response on a transcriptomic level, indicating that the observed mild phenotype of angiogenesis inhibition may represent a secondary effect.

Comparative glucocorticoid receptor agonism: In silico, in vitro, and in vivo and identification of potential biomarkers for synthetic glucocorticoid exposure

Abstract The glucocorticoid receptor (GR) is present in almost every vertebrate cell and is utilized in many biological processes. Despite an abundance of mammalian data, the structural conservation of the receptor and cross-species susceptibility, particularly for aquatic species, has not been well defined. Efforts to reduce, refine, and/or replace animal testing have increased, driving the impetus to advance development of new approach methodologies (NAMs). Here we used in silico, in vitro, and in vivo methods to elucidate a greater understanding of receptor-mediated effects of synthetic glucocorticoid exposure in teleost fish. Evolutionary conservation of amino acid residues critical for transcriptional activation was confirmed in silico using sequence alignment to predict across species susceptibility. Subsequent in vitro assays using zebrafish and human GR provided evidence of physiological congruence of GR agonism. Finally, adult fathead minnows (Pimephales promelas) were exposed in vivo to the synthetic glucocorticoids, dexamethasone (0.04, 400, 4,000 µg/L) and beclomethasone dipropionate (130 µg/L), and GR agonism confirmed via digital polymerase chain reaction; in addition, EcoToxChip analyses identified potential mRNA biomarkers following glucocorticoid exposure. These findings support the use of NAMs to potentially reduce multispecies in vivo experimentation while providing empirical evidence that expands the taxonomic domain of applicability for the GR agonism molecular initiating event within the broader GR agonism adverse outcome pathway network.

A new pharmacological strategy against treatment-resistant depression

Major depressive disorder affects more than 50 million people in the world. However, 50% of patients don't respond to two or more drugs or psychotherapeutic treatments, named treatment-resistant depression (TRD). In this work, we propose a new augmentation treatment against TRD based on combining Fluoxetine (FLX) and the N-terminal fragment Galanin, GAL(1–15). In Wistar Kyoto (WKY) rats, akin to endogenous depression genetically, we evaluate GAL(1–15)’s impact on FLX-induced behaviours on tests measuring despair and anhedonia. We explored GALR2 involvement using the antagonist M871 and an in vivo model with siRNA 5-HT1A knockdown. Also, the 5-HT1AR was analyzed by autoradiography binding in several brain regions. We analyze the corticosterone levels and a dexamethasone-suppressed corticotropin-releasing hormone stimulation to study the HPA axis regulation. Our results shows that only the combination of FLX + GAL(1–15) induced antidepressant effects in the WKY animals in Behavioural tests related to despair. This combination also reduced corticosterone levels in the WKY animals and modulated the functional characteristics of the serotoninergic receptor 5-HT1A in the prefrontal cortex. These novel results suggest combining GAL(1–15) with FLX is a new potentiation strategy in TRD cases. It shows the innovative potential of the interactions between the galaninergic and serotonergic systems to find new strategies and drugs against resistant depression.

Challenges and opportunities for validation of AI-based new approach methods.

The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-resents a paradigm shift in chemical safety assessment. Harnessing AI appropriately has enormous potential to streamline validation efforts. This review explores the challenges, opportunities, and future directions for validating AI-based NAMs, highlighting their transformative potential while acknowledging the complexities involved in their implementation and acceptance. We discuss key hurdles such as data quality, model interpretability, and regulatory acceptance, alongside opportunities including enhanced predictive power and efficient data integration. The concept of e-validation, an AI-powered framework for streamlining NAM validation, is presented as a comprehensive strategy to overcome limitations of traditional validation approaches, leveraging AI-powered modules for reference chemical selection, study simulation, mechanistic validation, and model training and evaluation. We propose robust validation strategies, including tiered approaches, performance benchmarking, uncertainty quantification, and cross-validation across diverse datasets. The importance of ongoing monitoring and refinement post-implementation is emphasized, addressing the dynamic nature of AI models. We consider ethical implications and the need for human oversight in AI-driven toxicology and outline the impact of trends in AI devel-opment, research priorities, and a vision for the integration of AI-based NAMs in toxicological practice, calling for collaboration among researchers, regulators, and industry stakeholders. We describe the vision of companion AI post-validation agents to keep methods and their validity status current. By addressing these challenges and opportunities, the scientific community can harness the potential of AI to enhance predictive toxicology while reducing reliance on traditional animal testing and increasing human relevance and translational capabilities.

Rapid determination of chemical losses in a microplate bioassay using fluorescence spectroscopy.

The increase in production and innovation of chemicals that humans interface with has enhanced the need for rapid toxicity testing of new and existing chemicals. This need, along with efforts to reduce animal testing, has led to the development of high-throughput bioassays typically conducted in microplates. These bioassays offer time and resource advantages over traditional animal models; however, significant chemical losses can occur in microplates. Current methods for measuring chemical losses in microplates require extensive sample preparation and highly sensitive instruments. We propose the use of fluorescence spectroscopy to measure chemical losses in high-throughput bioassays as a low resource alternative to the existing methods. A fluorescent plate reader was used to develop methods for quantifying the aqueous concentrations of two chemicals, 2-hydroxynaphthalene and acridine, in microwells of a 96-well microplate. A high-throughput, 5 day embryonic zebrafish bioassay was used as the model bioassay for method development. Chemical losses were attributed to a combination of photodegradation, sorption, and uptake by the zebrafish embryos, kinetics of which were derived from a pseudo-first order model. Chemical uptake amount was calculated to be approximately 50% and 21% of the total chemical amount added for 2-hydroxynaphthalene and acridine, respectively. Unexpected cranial deformities were observed in the embryonic zebrafish, suggesting further investigation of potential additive toxicity of the ultraviolet radiation exposure from fluorescence measurements and chemical exposure is needed. Nonetheless, this novel method provides a rapid, low resource approach to measuring chemical losses in microplates that can be extended to a variety of autofluorescent chemicals and microplate-based bioassays.

Safety and efficacy assessments using human iPS cell-derived cardiomyocytes

The delay and loss of drugs are serious problems in Japan. To overcome this issue, it is important to strengthen drug development capabilities. For drug development, the establishment and advancement of non-clinical testing methods are necessary for safe and effective clinical trials. Recently, the movement toward alternatives to animal testing has accelerated internationally. New Approach Methodologies (NAMs), such as human inducible pluripotent stem cell (hiPSC) technology and in silico modeling & simulation, are considered valuable for drug development. It has been demonstrated that hiPSC-derived cardiomyocytes (hiPSC-CMs) are useful tools to assess drug-induced cardiotoxicity, including arrhythmia and cardiac contractile dysfunction, leading to the use of hiPSC-CMs in the drug review process. Advancing hiPSC technologies have enabled the generation of mature hiPSC-CMs and engineered heart tissues, which are expected to provide novel information in drug safety and efficacy evaluation. Furthermore, it would be possible to establish the non-clinical evaluation that takes into account individual differences by developing hiPSCs bearing characteristics specific to certain populations, such as pediatrics or rare disease patients. Here, we present the recent findings and future perspectives on non-clinical evaluation using hiPSC technology.

A three-dimensional mouse liver organoid platform for assessing EDCs metabolites simulating liver metabolism.

Hepatic metabolism is an important process for evaluate the potential activity and toxicity of endocrine disrupting chemicals (EDCs) metabolites. Organization for Economic Co-operation and Development (OECD) has advocated the development of in vitro assays that mimic in vivo hepatic metabolism to eventually replace classical animal tests. In response to this need, we established a 3D mouse liver organoid (mLO) platform that mimics the animal model and is distinct from existing models. We evaluated the effects the activity of EDC metabolites generated through mLOs based on human cell-based reporter gene assays in addition to existing models. This study emphasizes the importance of hepatic ex-vivo and suggests the need a new metabolic model through a 3D mLOs platform. These results indicate that mLOs provides a novel biological method to screen for potential endocrine-disrupting activities of EDC metabolites.

Millisecond-level transient heating and temperature monitoring technique for ultrasound-induced thermal strain imaging.

Background: Ultrasound-induced thermal strain imaging (US-TSI) is a promising ultrasound imaging modality that has been demonstrated in preclinical studies to identify a lipid-rich necrotic core of an atherosclerotic plaque. However, human physiological motion, e.g., cardiac pulsation, poses challenges in implementing US-TSI applications, where achieving a millisecond-level temperature rise by delivering acoustic energy from a compact US-TSI probe is a key requirement. This study aims to develop a transient ultrasound heating and thermocouple monitoring technique at the millisecond level for US-TSI applications. Methods: We designed, prototyped, and characterized a novel US-TSI probe that includes a high-power, 3.5 MHz heating transducer with symmetrical dual 1D concave array. Additionally, millisecond-level temperature monitoring was demonstrated with fast-response thermocouples in laser- and ultrasound- induced thermal tests. Subsequently, we demonstrated the prototyped US-TSI probe can produce a desired temperature rise in a millisecond-short time window in vitro phantom and in vivo animal tests. Results: The prototyped US-TSI probe delivered zero-to-peak acoustic pressure up to 6.2 MPa with a 90 VPP input voltage. Both laser- and ultrasound- induced thermal tests verified that the selected thermocouples can monitor temperature change within 50 ms. The fast-response thermocouple confirmed the transient heating ability of the US-TSI probe, achieving a 3.9 °C temperature rise after a 25 ms heating duration (50% duty cycle) in the gel phantom and a 2.0 °C temperature rise after a 50 ms heating duration (50% duty cycle) in a pig model. Conclusions: We successfully demonstrated a millisecond-level transient heating and temperature monitoring technique utilizing the novel US-TSI probe and fast-response thermocouples. The reported transient ultrasound heating and thermocouple monitoring technique is promising for future in vivo human subject studies in US-TSI or other ultrasound-related thermal investigations.

Investigation of the suitability of confocal Raman spectroscopy for the demonstration of bioequivalence of topical products.

Bioequivalence studies of topical formulations have attracted increased interest as the European Medicines Agencies "Guideline on quality and equivalence on locally applied, locally acting cutaneous products" describes them in the context of the approval of generics. Since the guideline only proposes tape stripping as a destructive method for bioequivalence testing in in vitro skin penetration, the aim of this study was to investigate the suitability of confocal Raman spectroscopy (CRS) as a non-destructive alternative. To validate the CRS results, tape stripping and CRS experiments using ketoprofen as a model API were performed consecutively on the same samples of ex vivo porcine skin after frozen storage and compared. All experiments were also carried out on two different animal test subjects to investigate a possible influence of inter-individual variations. Furthermore, the influence of the chosen incubation times inside and outside of the steady state was determined. We were able to show that CRS and tape stripping results were very similar both in overall detected API amounts as well as in the results of bioequivalence testing, proving CRS is not only suitable for quantitative skin penetration experiments but also for bioequivalence testing. Inter-individual variations were found to be relevant when comparing formulations measured on different subjects. Bioequivalence testing however reached the same results on both subjects. Finally, the chosen incubation time was limited by skin disintegration, the reaching of steady state however did not influence the results of bioequivalence testing.

Characterization of a highly pathogenic porcine Teschoviruses 5 emerged in Western China.

Porcine teschovirus (PTV) is a devastating virus that targets the central nervous system and led to great economic losses in Europe between the 1920s and 1960s. Since 1973, PTV variants with lower pathogenicity have been prevalent globally, whereas highly pathogenic PTV strains have rarely emerged. In 2022, diarrhea with high mortality occurred on a pig farm in Gansu China. Virome analysis revealed that PTV was enriched among diarrheal samples. A PTV strain was then isolated and characterized by TEM, IFA, and growth kinetic features. Phylogenetic analyses revealed that the isolate shared an identity of approximately 90% with the most related PTV strain and with various mutant clusters among VP1. Further animal tests demonstrated that the isolate can result in serious respiratory distress, watery diarrhea, paralysis and high mortality in challenged pigs. H&E staining revealed the presence of lymphocyte cells infiltration and hemorrhage in the tissues. Overall, a PTV variant with high mortality was identified in western China, which could result in interstitial pneumonia, hemorrhage, and diarrhea. Although most PTV strains are associated with asymptomatic infection now, the sporadic occurrence of highly pathogenic PTVs is worthy of alarm.

Effect of Ethanol Extract and Ethyl Acetate Fraction of Soursop Leaves administration on Malondialdehyde Levels of Alloxan-Induced Rat Endocrine Cells

Soursop leaves (Annona muricata L.) contain many antioxidant compounds such as phenols and flavonoids that play an active role in inhibiting oxidative stress and can inhibit damage and death in cells, tissues, or organs. The objective of this study was to determine the effect of soursop leaf ethanol extract and ethyl acetate fraction effect on malondialdehyde levels and the quantity of pancreatic endocrine cells in male rats (Mus musculus) induced with alloxan. Method, the test animals were divided into seven groups (n=4). The normal control group was only given feed, the negative control group was given CMC-Na solution, the positive control group was given vitamin C dose of 50 mg/kg.BW, treatment group I was given soursop ethanol extract dose of 50 mg/kg.BW, treatment group II was given soursop ethanol extract dose of 100 mg./kg.BW, ethyl acetate fraction treatment group III was given soursop ethyl acetate fraction dose of 25 mg/kg BW, and treatment group IV was given soursop ethyl acetate fraction dose of 50 mg/kg BW. Results showed that the administration of ethyl acetate fraction of soursop leaves at a dose of 25 mg/kg BW showed the most effective potential significantly (p&lt;0.05) in reducing malondialdehyde levels and cell death. In conclusion, administering ethanol extract and ethyl acetate fraction of soursop leaves to rats which experiencing oxidative stress in their pancreas can stimulate and increase regeneration of endocrine cell in all rat groups. This is proven by a decrease of malondialdehyde levels and the number of necrosis cell necrosis. 1

Formulation and Evaluation of Transdermal Dissolving Microneedle Loaded with Ethanol Extract of Cocor Bebek Leaves (Kalanchoe pinnata)

Background: Acne is a chronic skin inflammation caused by blockage of the sebaceous glands in the skin and hypercolonization of the acne-causing bacteria Propionibacterium acnes. Cocor bebek leaves (Kalanchoe pinnata) are known to contain various secondary metabolites, including flavonoids, with antibacterial activity. Objective: In an effort to prevent side effects from using oral and topical antibiotics to treat acne, an alternative acne treatment that is safer and more effective with a strong drug delivery system is needed: microneedle patch technology containing natural ingredients. Methods: A microneedle patch formulation of Cocor bebek leaf extract was developed using a combination of HPMC and PVP polymers. The evaluation of microneedle patches included irritation tests with rat test animals and antibacterial activity tests against Propionibacterium acnes. The results showed the formation of yellow microneedle patches with uniform needles. The evaluation results showed that the microneedle patch has an irritation index value classified as non-irritant and has antibacterial activity against Propionibacterium acnes, with the highest inhibitory diameter at an extract concentration of 30% with a moderate inhibition category. Conclusion: The microneedle patch cocor bebek leaf extract shows potential as an effective drug delivery system for the treatment of acne that is safe for use on the skin.

Business Strategy To Increase Company Profit: Leveraging New Business Model CRO (Contract Research Organization) At Laboratory Animal Division PT. XYZ

The increasing prevalence of infectious and non-communicable diseases has spurred pharmaceutical and biotechnology companies to intensify research and development efforts for new drugs, particularly vaccines. The COVID-19 pandemic has prompted many companies and research institutions to find solutions. Preclinical testing in animals is mandatory in vaccine development, which highlights the importance of animals to ensure the safety and efficacy of drugs before clinical trials (conducted in humans). The surge in demand for animal testing presents a unique opportunity for PT XYZ to leverage the Laboratory Animal Division (LAD) as a Contract Research Organization (CRO). By offering services such as providing laboratory animals, providing materials of animal origin, and facilitating testing, PT XYZ transformed DHL from a cost center to a profit center. This research aims to identify customer needs and evaluate the business potential of CRO in DHL PT XYZ. This study combines qualitative data analysis with the Kepner Tregoe method and quantitative with the Analytical Hierarchy Process (AHP) method. This study recommends that PT XYZ prioritize the implementation of strategies aimed at improving service quality, expanding the variety of animal breeds and services, and obtaining relevant certifications. The results of this analysis and business strategy cost leadership are essential to increase customer satisfaction, grow market share, and ultimately achieve the company's revenue growth target.