Hydrophobic deep eutectic solvent (HDES) as oil phase in lipid-based drug formulations.

There is increasing pharmaceutical interest in deep eutectic solvents not only as a green alternative to organic solvents in drug manufacturing, but also as liquid formulation for drug delivery. The present work introduces a hydrophobic deep eutectic solvent (HDES) to the field of lipid-based formulations (LBF). Phase behavior of a mixture with 2:1 M ratio of decanoic- to dodecanoic acid was studied experimentally and described by thermodynamic modelling. Venetoclax was selected as a hydrophobic model drug and studied by atomistic molecular dynamics simulations of the mixtures. As a result, valuable molecular insights were gained into the interaction networks between the different components. Moreover, experimentally the HDES showed greatly enhanced drug solubilization compared to conventional glyceride-based vehicles, but aqueous dispersion behavior was limited. Hence surfactants were studied for their ability to improve aqueous dispersion and addition of Tween 80 resulted in lowest droplet sizes and high in vitro drug release. In conclusion, the combination of HDES with surfactant(s) provides a novel LBF with high pharmaceutical potential. However, the components must be finely balanced to keep the integrity of the solubilizing HDES, while enabling sufficient dispersion and drug release.

Predictions of biorelevant solubility change during dispersion and digestion of lipid-based formulations.

Computational approaches are increasingly explored in development of drug products, including the development of lipid-based formulations (LBFs), to assess their feasibility for achieving adequate oral absorption at an early stage. This study investigated the use of computational pharmaceutics approaches to predict solubility changes of poorly soluble drugs during dispersion and digestion in biorelevant media. Concentrations of 30 poorly water-soluble drugs were determined pre- and post-digestion with in-line UV probes using the MicroDISS Profiler™. Generally, cationic drugs displayed higher drug concentrations post-digestion, whereas for non-ionized drugs there was no discernible trend between drug concentration in dispersed and digested phase. In the case of anionic drugs there tended to be a decrease or no change in the drug concentration post-digestion. Partial least squares modelling was used to identify the molecular descriptors and drug properties which predict changes in solubility ratio in long-chain LBF pre-digestion (R2 of calibration = 0.80, Q2 of validation = 0.64) and post-digestion (R2 of calibration = 0.76, Q2 of validation = 0.72). Furthermore, multiple linear regression equations were developed to facilitate prediction of the solubility ratio pre- and post-digestion. Applying three molecular descriptors (melting point, LogD, and number of aromatic rings) these equations showed good predictivity (pre-digestion R2 = 0.70, and post-digestion R2 = 0.68). The model developed will support a computationally guided LBF strategy for emerging poorly water-soluble drugs by predicting biorelevant solubility changes during dispersion and digestion. This facilitates a more data-informed developability decision making and subsequently facilitates a more efficient use of formulation screening resources.

User Experience of Persons Using Ingestible Sensor-Enabled Pre-Exposure Prophylaxis to Prevent HIV Infection: Cross-Sectional Survey Study.

Background: A digital health technology's success or failure depends on how it is received by users. objectives: We conducted a user experience (UX) evaluation among persons who used the Food and Drug Administration-approved Digital Health Feedback System incorporating ingestible sensors (ISs) to capture medication adherence, after they were prescribed oral pre-exposure prophylaxis (PrEP) to prevent HIV infection. We performed an association analysis with baseline participant characteristics, to see if "personas" associated with positive or negative UX emerged. Methods: UX data were collected upon exit from a prospective intervention study of adults who were HIV negative, prescribed oral PrEP, and used the Digital Health Feedback System with IS-enabled tenofovir disoproxil fumarate plus emtricitabine (IS-Truvada). Baseline demographics; urine toxicology; and self-report questionnaires evaluating sleep (Pittsburgh Sleep Quality Index), self-efficacy, habitual self-control, HIV risk perception (Perceived Risk of HIV Scale 8-item), and depressive symptoms (Patient Health Questionnaire-8) were collected. Participants with ≥28 days in the study completed a Likert-scale UX questionnaire of 27 questions grouped into 4 domain categories: overall experience, ease of use, intention of future use, and perceived utility. Means and IQRs were computed for participant total and domain subscores, and linear regressions modeled baseline participant characteristics associated with UX responses. Demographic characteristics of responders versus nonresponders were compared using the Fisher exact and Wilcoxon rank-sum tests. Results: Overall, 71 participants were enrolled (age: mean 37.6, range 18-69 years; n=64, 90% male; n=55, 77% White; n=24, 34% Hispanic; n=68, 96% housed; and n=53, 75% employed). No demographic differences were observed in the 63 participants who used the intervention for ≥28 days. Participants who completed the questionnaire were more likely to be housed (52/53, 98% vs 8/10, 80%; P=.06) and less likely to have a positive urine toxicology (18/51, 35% vs 7/10, 70%; P=.08), particularly methamphetamine (4/51, 8% vs 4/10, 40%; P=.02), than noncompleters. Based on IQR values, ≥75% of participants had a favorable UX based on the total score (median 3.78, IQR 3.17-4.20), overall experience (median 4.00, IQR 3.50-4.50), ease of use (median 3.72, IQR 3.33-4.22), and perceived utility (median 3.72, IQR 3.22-4.25), and ≥50% had favorable intention of future use (median 3.80, IQR 2.80-4.40). Following multipredictor modeling, self-efficacy was significantly associated with the total score (0.822, 95% CI 0.405-1.240; P<.001) and all subscores (all P<.05). Persons with more depressive symptoms reported better perceived utility (P=.01). Poor sleep was associated with a worse overall experience (-0.07, 95% CI -0.133 to -0.006; P=.03). Conclusions: The UX among persons using IS-enabled PrEP (IS-Truvada) to prevent HIV infection was positive. Association analysis of baseline participant characteristics linked higher self-efficacy with positive UX, more depressive symptoms with higher perceived utility, and poor sleep with negative UX.

Current status and advances to improving drug delivery in diffuse intrinsic pontine glioma.

Diffuse midline glioma (DMG), including tumors diagnosed in the brainstem (diffuse intrinsic pontine glioma - DIPG), is the primary cause of brain tumor-related death in pediatric patients. DIPG is characterized by a median survival of <12 months from diagnosis, harboring the worst 5-year survival rate of any cancer. Corticosteroids and radiation are the mainstay of therapy; however, they only provide transient relief from the devastating neurological symptoms. Numerous therapies have been investigated for DIPG, but the majority have been unsuccessful in demonstrating a survival benefit beyond radiation alone. Although many barriers hinder brain drug delivery in DIPG, one of the most significant challenges is the blood-brain barrier (BBB). Therapeutic compounds must possess specific properties to enable efficient passage across the BBB. In brain cancer, the BBB is referred to as the blood-brain tumor barrier (BBTB), where tumors disrupt the structure and function of the BBB, which may provide opportunities for drug delivery. However, the biological characteristics of the brainstem's BBB/BBTB, both under normal physiological conditions and in response to DIPG, are poorly understood, which further complicates treatment. Better characterization of the changes that occur in the BBB/BBTB of DIPG patients is essential, as this informs future treatment strategies. Many novel drug delivery technologies have been investigated to bypass or disrupt the BBB/BBTB, including convection enhanced delivery, focused ultrasound, nanoparticle-mediated delivery, and intranasal delivery, all of which are yet to be clinically established for the treatment of DIPG. Herein, we review what is known about the BBB/BBTB and discuss the current status, limitations, and advances of conventional and novel treatments to improving brain drug delivery in DIPG.

Thyroid Hyperplasia and Neoplasm Adverse Events Associated With Glucagon-Like Peptide-1 Receptor Agonists in the Food and Drug Administration Adverse Event Reporting System: Retrospective Analysis.

Background: Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) are one of the most commonly used drugs for type 2 diabetes mellitus. Clinical guidelines recommend GLP-1 RAs as an adjunct to diabetes therapy in patients with chronic kidney disease, presence or risk of atherosclerotic cardiovascular disease, and obesity. The weight loss observed in clinical trials has been explored further in healthy individuals, putting GLP-1 RAs on track to be the next weight loss treatment. Objective: Although the adverse event profile is relatively safe, most GLP-1 RAs come with a labeled boxed warning for the risk of thyroid cancers, based on animal models and some postmarketing case reports in humans. Considering the increasing popularity of this drug class and its expansion into a new popular indication, a further review of the most recent postmarketing safety data was warranted to quantify thyroid hyperplasia and neoplasm instances. Methods: GLP-1 RA patient reports from the US Food and Drug Administration (FDA) Adverse Event Reporting System database were analyzed using reporting odds ratios and 95% CIs. Results: In this study, we analyzed over 18 million reports from the US FDA Adverse Event Reporting System and provided evidence of significantly increased propensity for thyroid hyperplasias and neoplasms in patients taking GLP-1 RA monotherapy when compared to patients taking sodium-glucose cotransporter-2 (SGLT-2) inhibitor monotherapy. Conclusions: GLP-1 RAs, regardless of indication, are associated with an over 10-fold increase in thyroid neoplasm and hyperplasia adverse event reporting when compared to SGLT-2 inhibitors.

Factor Analysis of Patients Who Find Tablets or Capsules Difficult to Swallow Due to Their Large Size: Using the Personal Health Record Infrastructure of Electronic Medication Notebooks.

BACKGROUND: Understanding patient preference regarding taking tablet or capsule formulations plays a pivotal role in treatment efficacy and adherence. Therefore, these preferences should be taken into account when designing formulations and prescriptions. OBJECTIVE: This study investigates the factors affecting patient preference in patients who have difficulties swallowing large tablets or capsules and aims to identify appropriate sizes for tablets and capsules. METHODS: A robust data set was developed based on a questionnaire survey conducted from December 1, 2022, to December 7, 2022, using the harmo smartphone app operated by harmo Co, Ltd. The data set included patient input regarding their tablet and capsule preferences, personal health records (including dispensing history), and drug formulation information (available from package inserts). Based on the medication formulation information, 6 indices were set for each of the tablets or capsules that were considered difficult to swallow owing to their large size and concomitant tablets or capsules (used as controls). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of each index. The index demonstrating the highest area under the curve of the ROC was selected as the best index to determine the tablet or capsule size that leads to swallowing difficulties. From the generated ROCs, the point with the highest discriminative performance that maximized the Youden index was identified, and the optimal threshold for each index was calculated. Multivariate logistic regression analysis was performed to identify the risk factors contributing to difficulty in swallowing oversized tablets or capsules. Additionally, decision tree analysis was performed to estimate the combined risk from several factors, using risk factors that were significant in the multivariate logistic regression analysis. RESULTS: This study analyzed 147 large tablets or capsules and 624 control tablets or capsules. The "long diameter + short diameter + thickness" index (with a 21.5 mm threshold) was identified as the best indicator for causing swallowing difficulties in patients. The multivariate logistic regression analysis (including 132 patients with swallowing difficulties and 1283 patients without) results identified the following contributory risk factors: aged <50 years (odds ratio [OR] 1.59, 95% CI 1.03-2.44), female (OR 2.54, 95% CI 1.70-3.78), dysphagia (OR 3.54, 95% CI 2.22-5.65), and taking large tablets or capsules (OR 9.74, 95% CI 5.19-18.29). The decision tree analysis results suggested an elevated risk of swallowing difficulties for patients with taking large tablets or capsules. CONCLUSIONS: This study identified the most appropriate index and threshold for indicating that a given tablet or capsule size will cause swallowing difficulties, as well as the contributory risk factors. Although some sampling biases (eg, only including smartphone users) may exist, our results can guide the design of patient-friendly formulations and prescriptions, promoting better medication adherence.

Medical, pharmaceutical, and nutritional applications of 3D-printing technology in diabetes.

AIMS: Despite numerous studies covering the various features of three-dimensional printing (3D printing) technology, and its applications in food science and disease treatment, no study has yet been conducted to investigate applying 3D printing in diabetes. Therefore, the present study centers on the utilization and impact of 3D printing technology in relation to the nutritional, pharmaceutical, and medicinal facets of diabetes management. It highlights the latest advancements, and challenges in this field. METHODS: In this review, the articles focusing on the application and effect of 3D printing technology on medical, pharmaceutical, and nutritional aspects of diabetes management were collected from different databases. RESULT: High precision of 3D printing in the placement of cells led to accurate anatomic control, and the possibility of bio-printing pancreas and ß-cells. Transdermal drug delivery via 3D-printed microneedle (MN) patches was beneficial for the management of diabetes disease. 3D printing supported personalized medicine for Diabetes Mellitus (DM). For instance, it made it possible for pharmaceutical companies to manufacture unique doses of medications for every diabetic patient. Moreover, 3D printing allowed the food industry to produce high-fiber and sugar-free products for the individuals with DM. CONCLUSIONS: In summary, applying 3D printing technology for diabetes management is in its early stages, and needs to be matured and developed to be safely used for humans. However, its rapid progress in recent years showed a bright future for the treatment of diabetes.

Quality by Design Considerations for Drop-on-Demand Point-of-Care Pharmaceutical Manufacturing of Precision Medicine.

Distributed and point-of-care (POC) manufacturing facilities enable an agile pharmaceutical production paradigm that can respond to localized needs, providing personalized and precision medicine. These capabilities are critical for narrow therapeutic index drugs and pediatric or geriatric dosing, among other specialized needs. Advanced additive manufacturing, three-dimensional (3D) printing, and drop-on-demand (DoD) dispensing technologies have begun to expand into pharmaceutical production. We employed a quality by design (QbD) approach to identify critical quality attributes (CQAs), critical material attributes (CMAs), and critical process parameters (CPPs) of a POC pharmaceutical manufacturing paradigm. This theoretical framework encompasses the production of active pharmaceutical ingredient (API) "inks" at a centralized facility, which are distributed to POC sites for DoD dispensing into/onto delivery vehicles (e.g., orodispersible films, capsules, single liquid dose vials). Focusing on the POC dispensing/dosing processes, QbD considerations and cause-and-effect analyses identified the dispensed API quantity and solid-state form (CQAs), as well as the nozzle diameter, system pressure channel, and number of drops dispensed (CPPs) for detailed investigation. Final assay quantification and content uniformity CQAs were measured from demonstrative levothyroxine sodium single-dose liquid vials of glycerin/water, meeting the standard acceptance values. Each POC facility is unlikely to maintain full quality control laboratory capabilities, requiring the development of appropriate atline or inline methods to ensure quality control. We developed control strategies, including atline ultraviolet-visible (UV-vis) verification of the API ink prior to dispensing, inline drop counting during dispensing, intermediate atline-dispensed volume checks, and offline batch confirmation by liquid chromatography-tandem mass spectrometry (LC-MS/MS) following production.

Eculizumab in myasthenia gravis: A review.

Eculizumab, a monoclonal antibody against complement C5, is a novel therapy to treat refractory myasthenia gravis (MG). The present review was undertaken to study the role of eculizumab in MG. This includes the drug's mechanism, pharmacokinetics, clinical trial findings, tolerability, side effects, safety, dosage, administration, and cost. An English-language search for relevant items was undertaken using Embase and PubMed from 1946 to present. Clinical trial registries/databases and websites were also searched for relevant data. Keywords were eculizumab and MG. The present review found 103 articles after initial screening. Current data support eculizumab as an effective, safe, and tolerable drug in cases of refractory MG. However, its cost can prevent it from being widely accessible to a majority of the general population.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection.

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

Genesis, mechanism, and avoidance of cosmetic coating defects - An industrial case study.

Film-coated tablets as solid oral dosage forms are a well-accepted way of administering drugs but are not without specific challenges during manufacturing. One relevant criterion of the final product is the visual integrity and therewith, the absence of cosmetic optical defects such as edge chipping. The aim of the present study was to examine the origin of those edge chipping defects, which were observed during commercial manufacturing of film-coated tablets, and to provide recommendations for process optimization to reduce the defect occurrence. The unraveling of the herein described phenomenon necessitated an interplay of in-depth material characterization, discrete element modeling (DEM) as well as an in-house developed optical measurement system for the automated quantification of tablet defects. As a result of this investigation, the automatic unloading step after the tablet coating process was identified as the most critical step for the occurrence of chipping defects and a replacement by manual unloading was proposed to reduce the defect propensity. The recommended optimization was subsequently confirmed in several manufacturing runs and a reduction of defect propensity by a factor of 5 was observed, highlighting the relevance and the impact of the performed thorough investigation.

Impact of a Nationwide Medication History Sharing Program on the Care Process and End-User Experience in a Tertiary Teaching Hospital: Cohort Study and Cross-Sectional Study.

Background: Timely and comprehensive collection of a patient's medication history in the emergency department (ED) is crucial for optimizing health care delivery. The implementation of a medication history sharing program, titled "Patient's In-home Medications at a Glance," in a tertiary teaching hospital aimed to efficiently collect and display nationwide medication histories for patients' initial hospital visits. Objective: As an evaluation was necessary to provide a balanced picture of the program, we aimed to evaluate both care process outcomes and humanistic outcomes encompassing end-user experience of physicians and pharmacists. Methods: We conducted a cohort study and a cross-sectional study to evaluate both outcomes. To evaluate the care process, we measured the time from the first ED assessment to urgent percutaneous coronary intervention (PCI) initiation from electronic health records. To assess end-user experience, we developed a 22-item questionnaire using a 5-point Likert scale, including 5 domains: information quality, system quality, service quality, user satisfaction, and intention to reuse. This questionnaire was validated and distributed to physicians and pharmacists. The Mann-Whiteny U test was used to analyze the PCI initiation time, and structural equation modeling was used to assess factors affecting end-user experience. Results: The time from the first ED assessment to urgent PCI initiation at the ED was significantly decreased using the patient medication history program (mean rank 42.14 min vs 28.72 min; Mann-Whitney U=346; P=.03). A total of 112 physicians and pharmacists participated in the survey. Among the 5 domains, "intention to reuse" received the highest score (mean 4.77, SD 0.37), followed by "user satisfaction" (mean 4.56, SD 0.49), while "service quality" received the lowest score (mean 3.87, SD 0.79). "User satisfaction" was significantly associated with "information quality" and "intention to reuse." Conclusions: Timely and complete retrieval using a medication history-sharing program led to an improved care process by expediting critical decision-making in the ED, thereby contributing to value-based health care delivery in a real-world setting. The experiences of end users, including physicians and pharmacists, indicated satisfaction with the program regarding information quality and their intention to reuse.

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online.

BACKGROUND: The online pharmacy market is growing, with legitimate online pharmacies offering advantages such as convenience and accessibility. However, this increased demand has attracted malicious actors into this space, leading to the proliferation of illegal vendors that use deceptive techniques to rank higher in search results and pose serious public health risks by dispensing substandard or falsified medicines. Search engine providers have started integrating generative artificial intelligence (AI) into search engine interfaces, which could revolutionize search by delivering more personalized results through a user-friendly experience. However, improper integration of these new technologies carries potential risks and could further exacerbate the risks posed by illicit online pharmacies by inadvertently directing users to illegal vendors. OBJECTIVE: The role of generative AI integration in reshaping search engine results, particularly related to online pharmacies, has not yet been studied. Our objective was to identify, determine the prevalence of, and characterize illegal online pharmacy recommendations within the AI-generated search results and recommendations. METHODS: We conducted a comparative assessment of AI-generated recommendations from Google's Search Generative Experience (SGE) and Microsoft Bing's Chat, focusing on popular and well-known medicines representing multiple therapeutic categories including controlled substances. Websites were individually examined to determine legitimacy, and known illegal vendors were identified by cross-referencing with the National Association of Boards of Pharmacy and LegitScript databases. RESULTS: Of the 262 websites recommended in the AI-generated search results, 47.33% (124/262) belonged to active online pharmacies, with 31.29% (82/262) leading to legitimate ones. However, 19.04% (24/126) of Bing Chat's and 13.23% (18/136) of Google SGE's recommendations directed users to illegal vendors, including for controlled substances. The proportion of illegal pharmacies varied by drug and search engine. A significant difference was observed in the distribution of illegal websites between search engines. The prevalence of links leading to illegal online pharmacies selling prescription medications was significantly higher (P=.001) in Bing Chat (21/86, 24%) compared to Google SGE (6/92, 6%). Regarding the suggestions for controlled substances, suggestions generated by Google led to a significantly higher number of rogue sellers (12/44, 27%; P=.02) compared to Bing (3/40, 7%). CONCLUSIONS: While the integration of generative AI into search engines offers promising potential, it also poses significant risks. This is the first study to shed light on the vulnerabilities within these platforms while highlighting the potential public health implications associated with their inadvertent promotion of illegal pharmacies. We found a concerning proportion of AI-generated recommendations that led to illegal online pharmacies, which could not only potentially increase their traffic but also further exacerbate existing public health risks. Rigorous oversight and proper safeguards are urgently needed in generative search to mitigate consumer risks, making sure to actively guide users to verified pharmacies and prioritize legitimate sources while excluding illegal vendors from recommendations.

Chemical composition and biological activities of Cucurbita okeechobeensis extracts from its aerial parts, seeds, and fruit shells.

The Cucurbita genus has been widely used in traditional medicinal systems across different countries. In this study, we aimed to investigate the chemical composition, antioxidant properties, enzyme inhibitory, and cytotoxic effects of methanol and aqueous extracts obtained from the aerial parts, seeds, and fruit shells of Cucurbita okeechobeensis. Antioxidant properties were assessed using various chemical methods, including radical quenching (DPPH and ABTS), reducing power (CUPRAC and FRAP), metal chelation, and phosphomolybdenum assays. The extracts' enzyme inhibitory effects were tested against cholinesterase, amylase, glucosidase, and tyrosinase, whereas different cancer cell lines were used for the cytotoxicity study. The chemical composition, evaluated by HPLC-ESI-MSn, showed that the most abundant compounds were flavonoids (mainly quercetin glycosides) followed by phenolic acids (mostly caffeic acid derivatives). The aerial parts displayed stronger antioxidant ability than the seed and fruit shells, in agreement with the highest content in phytochemicals. In addition, the methanol extracts presented the highest bioactivity and content in phytochemicals; among them, the extract of the aerial part exhibited significant cytotoxic effects on cancer cell lines and induced apoptosis. Overall, our results suggest that C. okeechobeensis is a valuable source of bioactive compounds for the pharmaceutical and nutraceutical industries.

Essential oil pharmaceuticals for killing ectoparasites on dogs.

BACKGROUND: External parasites, particularly ticks and fleas, are among the most common problems affecting dogs. Chemical medicines are commonly used to prevent and eliminate such external parasites, but their improper use can cause adverse reactions, and the toxins they contain may remain in the environment. OBJECTIVES: The objective of this study was to investigate the in vitro efficacy of Zanthoxylum limonella, citronella, clove, peppermint, and ginger essential oils against dog ticks and fleas and to test the sensitivity of dogs' skin to these essential oils. METHODS: The five essential oils were tested for in vitro efficacy against ticks and fleas, and the two most effective essential oils were then tested on the dogs' skin. RESULTS: The results revealed that these five essential oils at 16% concentrations effectively inhibited the spawning of female engorged ticks. In addition, all five essential oils had a strong ability to kill tick larvae at concentrations of 2% upward. Furthermore, 4% concentrations of the five essential oils quickly eliminated fleas, especially clove oil, which killed 100% of fleas within 1 h. A 50%, 90%, and 99% lethal concentration (LC50, LC90, and LC99) for the essential oils on tick larvae in 24 h were found to be low values. LC50, LC90, and LC99 for the essential oils on flea in 1 h was lowest values. Clove oil at 16% concentration was the most satisfactory essential oil for application on dogs' skin, with a low percentage of adverse effects. CONCLUSIONS: This study confirmed the effectiveness of essential oils for practical use as tick and flea repellents and eliminators. Essential-oil-based pharmaceutical can replace chemical pesticides and provide benefits for both consumers and the environment.

Development of an extemporaneous preparation formulation using a simple and non-solubilizing matrix for first in human clinical study.

Extemporaneous preparation (EP) formulation is an attractive strategy to accelerate the formulation development of new chemical entities for first entry into human study. In this work, an EP suspension formulation for a development drug candidate GDC-6599 was successfully developed. The formulation spanned a wide concentration range from 0.1 to 2.0 mg/mL. A non-solubilizing vehicle, 0.6 % (w/v) methylcellulose solution was used to suspend GDC-6599. An aversive agent denatonium benzoate at an extremely low level (6 ppm) was applied as a taste masking agent. This enabled a simple matrix for the analysis of related substances from GDC-6599 during all stability studies. Microcrystalline cellulose at 10 mg/mL concentration was added to the EP formulation to generate a suspension appearance, leading to the success of using a single placebo for matching active formulation at all concentrations. The developed formulation demonstrated excellent homogeneity, sufficient stability and passed microbiological enumeration test. Rinsing performance test demonstrated that greater than 99.8 % amount of drug was successfully recovered by rinsing with water twice, providing guidance for clinical dosing. Biopharmaceutical assessment was conducted by both in silico simulation and in vitro tests. Greater than 90 % bioaccessibility of the EP suspension formulation was obtained via an in vitro system mimicking the human gastrointestinal absorption, consistent with the result from the in silico modeling. The developed EP formulation was successfully used to support the early single ascending dose (SAD) cohorts of GDC-6599 Phase I clinical study. The formulation matrix and assessment workflow developed in this work are generalizable as a platform for EP formulation development of new chemical entities for early phase clinical studies.