Improving Access to Mental Health Care in Residents of Long-Term Care Living Facilities.

Objective: Residents of long-term care facilities have reduced access to mental health care due to the availability of providers, transportation, and staff or family members who must accompany the resident. As a result, many residents wait up to 6 months for a first appointment with a psychiatric provider or utilize their primary care provider to meet their mental health care needs.

Methods: To increase access to mental health care, tablets were placed in long-term care facilities to access telehealth visits with mental health providers.

Effectiveness of Integrated Care for Diabetes Mellitus Type 2, Cardiovascular and Chronic Respiratory Diseases: A Systematic Review and Meta-Analysis.

Introduction: In this paper, we use the Rainbow Model of Integrated Care (RMIC) framework to evaluate the effectiveness of integrated care in terms of enhancing the outcomes of chronic conditions such as diabetes mellitus type 2 (DMT2), cardiovascular diseases (CVD), chronic respiratory diseases (CRD), or their combinations.

Methods: The data extracted from randomized controlled trials (RCT) of integrated care interventions for DMT2, CVD, and CRD (follow-up ≥ 3 months) in 11 databases were analysed using random-effects meta-analysis.

Results: A total of 54 eligible studies covering 12,976 participants, with a mean follow-up of 54 weeks, were included.

Evolution of Telehealth Program to Meet Current Needs of Post-Acute and Long-Term Care Communities.

This article describes a telehealth program initially created to reduce transfers to acute care from the nursing home and its evolution into a robust program that includes Behavioral Health, a Medical Director program, and telenursing.

American Association of Nurse Practitioners Research Agenda, 2023-2028.

This report highlights the 2023-2028 American Association of Nurse Practitioners Research Agenda (AANP-RA), which focuses on the research goals of AANP as an organization and is based on its mission and strategic plan. The purpose of the AANP Research Agenda is to outline research priorities that advance the AANP Strategic Plan and concurrently address gaps in nursing science. American Association of Nurse Practitioners supports research studies that are rigorously designed and conducted using quantitative, qualitative, and mixed-methods approaches, as well as implementation science with the potential to positively impact both NP practice and patient health outcomes.

Characterisation of cotadutide's dual GLP-1/glucagon receptor agonistic effects on glycaemic control using an in vivo human glucose regulation quantitative systems pharmacology model.

Background And Purpose: Cotadutide is a dual GLP-1 and glucagon receptor agonist with balanced agonistic activity at each receptor designed to harness the advantages on promoting liver health, weight loss and glycaemic control. We characterised the effects of cotadutide on glucose, insulin, GLP-1, GIP, and glucagon over time in a quantitative manner using our glucose dynamics systems model (4GI systems model), in combination with clinical data from a multiple ascending dose/Phase 2a (MAD/Ph2a) study in overweight and obese subjects with a history of Type 2 diabetes mellitus (NCT02548585).

Experimental Approach: The cotadutide PK-4GI systems model was calibrated to clinical data by re-estimating only food related parameters.

Competency-based curriculum in nurse practitioner education.

Professional nursing standards and guidelines form the foundation for nurse practitioner curriculum. Nurse educators should understand the role these professional standards and guidelines have in the development of curriculum. Recently, nursing education has moved to a competency-based education with the release of the new American Association of Colleges of Nursing Essentials and the National Organization of Nurse Practitioner Faculties Nurse Practitioner Role Core Competencies.

Telehealth Policy and the Advanced Practice Nurse.

Telehealth is an efficient and effective method of care delivery used by advance practice registered nurses (APRNs) nationally, especially in the wake of the coronavirus disease 2019 pandemic. With the ever-changing rules and regulations governing telehealth practice, the APRN may struggle to keep abreast. Telehealth is governed by legislation and regulation in addition to telehealth-specific laws.

BYON4228 is a pan-allelic antagonistic SIRPα antibody that potentiates destruction of antibody-opsonized tumor cells and lacks binding to SIRPγ on T cells.

Background: Preclinical studies have firmly established the CD47-signal-regulatory protein (SIRP)α axis as a myeloid immune checkpoint in cancer, and this is corroborated by available evidence from the first clinical studies with CD47 blockers. However, CD47 is ubiquitously expressed and mediates functional interactions with other ligands as well, and therefore targeting of the primarily myeloid cell-restricted inhibitory immunoreceptor SIRPα may represent a better strategy.

Method: We generated BYON4228, a novel SIRPα-directed antibody.

Thyrotropin Receptor Antagonism by a Novel Small Molecule: Preclinical Observations.

Treatment of Graves' hyperthyroidism (GH) and Graves' orbitopathy (GO) is far from adequate, and hence, new substances that specifically target the autoantigens in GH/GO are warranted. This study determined the preclinical efficacy of SYD5115, a novel low-molecular-weight compound that inhibits the thyrotropin receptor (TSH-R). The TSH-R inhibiting capability of SYD5115 was tested through stimulation of wild-type and chimeric TSH-R expressed in Chinese hamster ovary (CHO) cells using two functional (stimulatory and blocking) cell-based TSH-R-Ab bioassays.

Discovery of SYD5115, a novel orally active small molecule TSH-R antagonist.

The thyrotropin receptor (TSH-R) regulates the thyroid gland and is normally activated by thyrotropin. In patients with Graves' disease, TSH-R is also stimulated by stimulatory TSH-R autoantibodies leading to hyperthyroidism. In this paper, we describe the discovery of SYD5115 (67), a novel small molecule TSH-R antagonist with nanomolar potency.

Safety, Tolerability and Pharmacokinetics of Half-Life Extended Severe Acute Respiratory Syndrome Coronavirus 2 Neutralizing Monoclonal Antibodies AZD7442 (Tixagevimab-Cilgavimab) in Healthy Adults.

Background: AZD7442 is a combination of extended half-life, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific neutralizing monoclonal antibodies (tixagevimab and cilgavimab).

Methods: This phase 1, first-in-human, randomized, double-blind, placebo-controlled, dose-escalation study evaluated AZD7442 administered intramuscularly (300 mg) or intravenously (300, 1000, or 3000 mg) in healthy adults (aged 18-55 years). The primary end point was safety and tolerability.

Evaluating the performance of machine-learning regression models for pharmacokinetic drug-drug interactions.

Combination therapy or concomitant drug administration can be associated with pharmacokinetic drug-drug interactions, increasing the risk of adverse drug events and reduced drug efficacy. Thus far, machine-learning models have been developed that can classify drug-drug interactions. However, to enable quantification of the pharmacokinetic effects of a drug-drug interaction, regression-based machine learning should be explored.

Multiplex Hybrid Antigen-Capture LC-MRM Quantification in Sera and Nasal Lining Fluid of AZD7442, a SARS-CoV-2-Targeting Antibody Combination.

AZD7442 (tixagevimab [AZD8895]/cilgavimab [AZD1061]) is a monoclonal antibody (mAb) combination in development for the prevention and treatment of coronavirus disease 2019. Traditionally, bioanalysis of mAbs is performed using ligand binding assays (LBAs), which offer sensitivity, robustness, and ease of implementation. However, LBAs frequently require generation of critical reagents that typically take several months.

Comparing the applications of machine learning, PBPK, and population pharmacokinetic models in pharmacokinetic drug-drug interaction prediction.

The gold-standard approach for modeling pharmacokinetic mediated drug-drug interactions is the use of physiologically-based pharmacokinetic modeling and population pharmacokinetics. However, these models require extensive amounts of drug-specific data generated from a wide variety of in vitro and in vivo models, which are later refined with clinical data and system-specific parameters. Machine learning has the potential to be utilized for the prediction of drug-drug interactions much earlier in the drug discovery cycle, using inputs derived from, among others, chemical structure.

Digital Health Interventions for Musculoskeletal Pain Conditions: Systematic Review and Meta-analysis of Randomized Controlled Trials.

Background: Digital health solutions can provide populations with musculoskeletal pain with high-reach, low-cost, easily accessible, and scalable patient education and self-management interventions that meet the time and resource restrictions.

Objective: The main objective of this study was to determine the effectiveness of digital health interventions for people with musculoskeletal pain conditions (ie, low back pain, neck pain, shoulder pain, knee pain, elbow pain, ankle pain, and whiplash).

Methods: A systematic review and meta-analysis was conducted.

Harnessing Clinical Trial and Real-World Data Towards an Understanding of Sex Effects on Drug Pharmacokinetics, Pharmacodynamics and Efficacy.

Increasing clinical data on sex-related differences in drug efficacy and toxicity has highlighted the importance of understanding the impact of sex on drug pharmacokinetics and pharmacodynamics. Intrinsic differences between males and females, such as different CYP enzyme activity, drug transporter expression or levels of sex hormones can all contribute to different responses to medications. However, most studies do not include sex-specific investigations, leading to lack of sex-disaggregated pharmacokinetic and pharmacodynamic data.

Development of and insights from systems pharmacology models of antibody-drug conjugates.

Antibody-drug conjugates (ADCs) have gained traction in the oncology space in the past few decades, with significant progress being made in recent years. Although the use of pharmacometric modeling is well-established in the drug development process, there is an increasing need for a better quantitative biological understanding of the pharmacokinetic and pharmacodynamic relationships of these complex molecules. Quantitative systems pharmacology (QSP) approaches can assist in this endeavor; recent computational QSP models incorporate ADC-specific mechanisms and use data-driven simulations to predict experimental outcomes.

Efficacy and safety of intramuscular administration of tixagevimab-cilgavimab for early outpatient treatment of COVID-19 (TACKLE): a phase 3, randomised, double-blind, placebo-controlled trial.

Background: Early intramuscular administration of SARS-CoV-2-neutralising monoclonal antibody combination, tixagevimab-cilgavimab, to non-hospitalised adults with mild to moderate COVID-19 has potential to prevent disease progression. We aimed to evaluate the safety and efficacy of tixagevimab-cilgavimab in preventing progression to severe COVID-19 or death.

Methods: TACKLE is an ongoing, phase 3, randomised, double-blind, placebo-controlled study conducted at 95 sites in the USA, Latin America, Europe, and Japan.

Dissemination enhancement in Doctor of Nursing Practice students.

Purpose: Students in Doctor of Nursing Practice (DNP) programs graduate with a completed DNP Project focused on practice improvement utilizing evidence-based research. Despite the value in disseminating the DNP Project outcomes to an audience of interest, many DNP graduates do not pursue dissemination beyond conclusion of their project and graduation.

Methods: The DNP Project didactic course and the DNP Project manuscripts were revised with active learning assignments designed to improve knowledge, skills, and confidence in professional writing and dissemination.

Intramuscular AZD7442 (Tixagevimab-Cilgavimab) for Prevention of Covid-19.

Background: The monoclonal-antibody combination AZD7442 is composed of tixagevimab and cilgavimab, two neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that have an extended half-life and have been shown to have prophylactic and therapeutic effects in animal models. Pharmacokinetic data in humans indicate that AZD7442 has an extended half-life of approximately 90 days.

Methods: In an ongoing phase 3 trial, we enrolled adults (≥18 years of age) who had an increased risk of an inadequate response to vaccination against coronavirus disease 2019 (Covid-19), an increased risk of exposure to SARS-CoV-2, or both.

Population Pharmacokinetics of Cotadutide in Subjects with Type 2 Diabetes.

Background And Objectives: Cotadutide is a balanced dual glucagon-like peptide-1/glucagon receptor agonist under development for the treatment of nonalcoholic steatohepatitis and chronic kidney disease with type 2 diabetes. The objectives of the analysis were to characterize the population pharmacokinetics of cotadutide following daily subcutaneous injection in subjects with type 2 diabetes and to evaluate the effect of demographic and clinical variables of interest on cotadutide pharmacokinetics.

Methods: This study analyzed 8834 plasma concentrations of cotadutide from 759 subjects with type 2 diabetes who received daily subcutaneous doses from 20 to 600 μg from six clinical studies.

Impact of Infection Control Education on Gastrointestinal Endoscopy Procedural Staff.

To date, minimal research has been conducted on proper use of personal protective equipment and hand hygiene within endoscopy. The American Society for Gastrointestinal Endoscopy has developed guidelines for infection control within the endoscopy suite. A practice change based upon these guidelines was implemented.