Estimating the likelihood of epilepsy from clinically noncontributory electroencephalograms using computational analysis: A retrospective, multisite case-control study.

OBJECTIVE: This study was undertaken to validate a set of candidate biomarkers of seizure susceptibility in a retrospective, multisite case-control study, and to determine the robustness of these biomarkers derived from routinely collected electroencephalography (EEG) within a large cohort (both epilepsy and common alternative conditions such as nonepileptic attack disorder). METHODS: The database consisted of 814 EEG recordings from 648 subjects, collected from eight National Health Service sites across the UK. Clinically noncontributory EEG recordings were identified by an experienced clinical scientist (N = 281; 152 alternative conditions, 129 epilepsy). Eight computational markers (spectral [n = 2], network-based [n = 4], and model-based [n = 2]) were calculated within each recording. Ensemble-based classifiers were developed using a two-tier cross-validation approach. We used standard regression methods to assess whether potential confounding variables (e.g., age, gender, treatment status, comorbidity) impacted model performance. RESULTS: We found levels of balanced accuracy of 68% across the cohort with clinically noncontributory normal EEGs (sensitivity =61%, specificity =75%, positive predictive value =55%, negative predictive value =79%, diagnostic odds ratio =4.64, area under receiver operated characteristics curve =.72). Group level analysis found no evidence suggesting any of the potential confounding variables significantly impacted the overall performance. SIGNIFICANCE: These results provide evidence that the set of biomarkers could provide additional value to clinical decision-making, providing the foundation for a decision support tool that could reduce diagnostic delay and misdiagnosis rates. Future work should therefore assess the change in diagnostic yield and time to diagnosis when utilizing these biomarkers in carefully designed prospective studies.

Well-spread samples with dynamic sample sizes.

A spatial sampling design determines where sample locations are placed in a study area so that population parameters can be estimated with relatively high precision. If the response variable has spatial trends, spatially balanced or well-spread designs give precise results for commonly used estimators. This article proposes a new method that draws well-spread samples over arbitrary auxiliary spaces and can be used for master sampling applications. All we require is a measure of the distance between population units. Numerical results show that the method generates well-spread samples and compares favorably with existing designs. We provide an example application using several auxiliary variables to estimate total aboveground biomass over a large study area in Eastern Amazonia, Brazil. Multipurpose surveys are also considered, where the totals of aboveground biomass, primary production, and clay content (3 responses) are estimated from a single well-spread sample over the auxiliary space.

Properties of Packed Bed Structures Formed during Filtration: A Two and Three-Dimensional Model.

Agglomeration is an issue that causes many problems during secondary processing for pharmaceutical companies, causing material to need further processing and costing additional time and resources to ensure a satisfactory outcome. A potential source of agglomeration arises from the particle contacts established during filtration that lead to robust agglomerates forming during drying, so that a necessary first step toward understanding agglomeration is to study the packing properties of filtration beds. Here, we present two and three-dimensional models simulating the formation of packed bed structures during filtration. The models use circular and spherical particles of different sizes, mimicking the bimodal particle size distributions sometimes encountered in industrial practice. The statistics of packing and void formation, along with the distribution of interparticle contacts and percolation structures, are presented and discussed in the context of filtration, drying, and agglomeration. The model paves the way for predictive capabilities that can lead to the rational design of processes to minimize the impact of agglomeration.

What factors contribute towards ambulance on-scene times for suspected stroke patients? An observational study.

INTRODUCTION: Pre-hospital stroke care focusses on rapid access to specialist stroke units, but UK ambulance data shows increasing pre-hospital times. This study aimed to describe factors contributing towards ambulance on-scene times (OST) for suspected stroke patients and identify targets for a future intervention. PATIENTS AND METHODS: Ambulance clinicians in North East Ambulance Service were asked to complete a survey after transporting any suspected stroke patients to describe the patient encounter, interventions and timings. Completed surveys were linked with electronic patient care records. Potentially modifiable factors were identified by the study team. Poisson regression analysis quantified the association of selected potentially modifiable factors with OST. RESULTS: About 2037 suspected stroke patients were conveyed between July and December 2021, resulting in 581 fully completed surveys by 359 different clinicians. The median age of patients was 75 years (interquartile range (IQR) 66-83) and 52% of patients were male. Median OST was 33 min (IQR 26-41). Three potentially modifiable factors were identified as contributors to extended OST. Performing additional advanced neurological assessments added 10% to OST (34 vs 31 min, p = 0.008); intravenous cannulation added 13% (35 vs 31 min, p = <0.001) and ECGs added 22% (35 vs 28 min, p = <0.001). CONCLUSIONS: This study identified three potentially modifiable factors that increased pre-hospital OST with suspected stroke patients. This type of data can be used to target interventions at behaviours that extend pre-hospital OST but which have questionable patient benefit. This approach will be evaluated in a follow up study in the North East of England.

Documentation of atrial fibrillation among non-conveyed ambulance patients: a new primary prevention opportunity?

Introduction: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is a significant risk factor for stroke. Prescription of oral anticoagulant (OAC) medication reduces the risk of AF-related stroke by 64% - yet over 400,000 people in England have undiagnosed (and therefore untreated) AF.Emergency medical services (EMS) encounter a wide range of patients, some of whom may not engage with other healthcare services. AF may be detected by EMS in connection with the cause of the call, or as an incidental finding. While EMS are not traditionally utilised for public health screening, they may offer an opportunity to identify patients with undiagnosed or untreated AF and refer onward.This study aimed to explore what proportion of patients seen by EMS who were not transported to hospital had AF and to estimate how many would potentially benefit from OAC. Methods: A retrospective service evaluation was conducted using routinely collected data from a large UK regional ambulance service. The sample included adults attended by EMS on the 15th of each month in 2019, who were not transported to hospital and where an electrocardiogram was recorded. Of those with AF, we calculated the proportion in whom this was possibly new and report whether OAC was prescribed. Results: There were 859 patients who met the inclusion criteria, of whom 91 (11%) had AF documented. Of the 91 patients with AF, 23 (25%) had no documented history of AF or OAC prescription, so were potentially new diagnoses of AF, who would benefit from consideration of OAC therapy. Conclusion: The EMS assessment offers an opportunity for AF to be identified in patients who were not transported to hospital. EMS may have a role in primary prevention of harm, including stroke, by identifying and referring patients with AF for consideration of OAC.

Digital Design of Filtration and Washing of Active Pharmaceutical Ingredients via Mechanistic Modeling.

To facilitate integrated end-to-end pharmaceutical manufacturing using digital design, a model capable of transferring material property information between operations to predict product attributes in integrated purification processes has been developed. The focus of the work reported here combines filtration and washing operations used in active pharmaceutical ingredient (API) purification and isolation to predict isolation performance without the need of extensive experimental work. A fixed Carman-Kozeny filtration model is integrated with several washing mechanisms (displacement, dilution, and axial dispersion). Two limiting cases are considered: case 1 where there is no change in the solid phase during isolation (no particle dissolution and/or growth), and case 2 where the liquid and solid phases are equilibrated over the course of isolation. In reality, all actual manufacturing conditions would be bracketed by these two limiting cases, so consideration of these two scenarios provides rigorous theoretical bounds for assessing isolation performance. This modeling approach aims to facilitate the selection of most appropriate models suitable for different isolation scenarios, without the requirement to use overly complex models for straightforward isolation processes. Mefenamic acid and paracetamol were selected as representative model compounds to assess a range of isolation scenarios. In each case, the objective of the models was to identify the purity of the product reached with a fixed wash ratio and minimize the changes to the crystalline particle attributes that occur during the isolation process. This was undertaken with the aim of identifying suitable criteria for the selection of appropriate filtration and washing models corresponding to relevant processing conditions, and ultimately developing guidelines for the digital design of filtration and washing processes.

Employing Constant Rate Filtration To Assess Active Pharmaceutical Ingredient Washing Efficiency.

Washing is a key step in pharmaceutical isolation to remove unwanted crystallization solvents and dissolved impurities (mother liquor) from the active pharmaceutical ingredient (API) filter cake to ensure the purity of the product whilst maximizing yield. It is therefore essential to avoid both product dissolution and impurity precipitation during washing, especially precipitation of impurities caused by the wash solvent acting as an antisolvent, affecting purity and causing agglomerate formation. This work investigates the wash solvent flow through a saturated filter cake to optimize washing by displacement, taking account of diffusional mechanisms and manipulating the wash contact time. Constant rate filtration/washing is employed in this study using readily available laboratory equipment. One advantage of using constant rate filtration in this work is that it allows for the collection of separate aliquots during all stages of filtration, washing, and deliquoring of the API cake. This enables a wash profile to be obtained, as well as providing an overall picture on the mass of API lost during isolation and so can assist in optimizing the washing strategy. Particle size analysis of damp cake obtained straight after washing is also performed using laser diffraction. This allowed for agglomerate formation caused during washing to be distinguished from agglomeration that would be caused by subsequent drying of the wet filter cake. This work aims at improving pharmaceutical product quality, increasing sustainability, and reducing manufacturing cost.

Real World Biologic Use and Switch Patterns in Severe Asthma: Data from the International Severe Asthma Registry and the US CHRONICLE Study.

INTRODUCTION: International registries provide opportunities to describe use of biologics for treating severe asthma in current clinical practice. Our aims were to describe real-life global patterns of biologic use (continuation, switches, and discontinuations) for severe asthma, elucidate reasons underlying these patterns, and examine associated patient-level factors. METHODS: This was a historical cohort study including adults with severe asthma enrolled into the International Severe Asthma Registry (ISAR; http://isaregistries.org, 2015-2020) or the CHRONICLE Study (2018-2020) and treated with a biologic. Eleven countries were included (Bulgaria, Canada, Denmark, Greece, Italy, Japan, Kuwait, South Korea, Spain, UK, and USA). Biologic utilization patterns were defined: 1) continuing initial biologic; 2) stopping biologic treatment; or 3) switching to another biologic. Reasons for discontinuation/switching were recorded and comparisons drawn between groups. RESULTS: A total of 3531 patients were included. Omalizumab was the most common initial biologic in 2015 (88.2%) and benralizumab in 2019 (29.6%). Most patients (79%; 2791/3531) continued their first biologic; 10.2% (356/3531) stopped; 10.8% (384/3531) switched. The most frequent first switch was from omalizumab to an anti-IL-5/5R (49.6%; 187/377). The most common subsequent switch was from one anti-IL-5/5R to another (44.4%; 20/45). Insufficient efficacy and/or adverse effects were the most frequent reasons for stopping/switching. Patients who stopped/switched were more likely to have a higher baseline blood eosinophil count and exacerbation rate, lower lung function, and greater health care resource utilization. CONCLUSION: The description of real-life patterns of continuing, stopping, or switching biologics enhances our understanding of global biologic use. Prospective studies involving structured switching criteria could ascertain optimal strategies to identify patients who may benefit from switching.

Asthma Phenotyping in Primary Care: Applying the International Severe Asthma Registry Eosinophil Phenotype Algorithm Across All Asthma Severities.

BACKGROUND: We developed an eosinophil phenotype gradient algorithm and applied it to a large severe asthma cohort (International Severe Asthma Registry). OBJECTIVE: We sought to reapply this algorithm in a UK primary care asthma cohort, quantify the eosinophilic phenotype, and assess the relationship between the likelihood of an eosinophilic phenotype and asthma severity/health care resource use (HCRU). METHODS: Patients age 13 years and older with active asthma and blood eosinophil count or 1 or greater, who were included from the Optimum Patient Care Research Database and the Clinical Practice Research Datalink, were categorized according to the likelihood of eosinophilic phenotype using the International Severe Asthma Registry gradient eosinophilic algorithm. Patient demographic, clinical and HCRU characteristics were described for each phenotype. RESULTS: Of 241,006 patients, 50.3%, 22.2%, and 21.9% most likely (grade 3), likely (grade 2), and least likely (grade 1), respectively, had an eosinophilic phenotype, and 5.6% had a noneosinophilic phenotype (grade 0). Compared with patients with noneosinophilic asthma, those most likely to have an eosinophilic phenotype tended to have more comorbidities (percentage with Charlson comorbidity index of ≥2: 28.2% vs 6.9%) and experienced more asthma attacks (percentage with one or more attack: 24.8% vs 15.3%). These patients were also more likely to have asthma that was difficult to treat (31.1% vs 18.3%), to receive more intensive treatment (percentage on Global Initiative for Asthma 2020 step 4 or 5: 44.2% vs 27.5%), and greater HCRU (eg, 10.8 vs 7.9 general practitioner all-cause consultations per year). CONCLUSIONS: The eosinophilic asthma phenotype predominates in primary care and is associated with greater asthma severity and HCRU. These patients may benefit from earlier and targeted asthma therapy.

A Novel Integrated Workflow for Isolation Solvent Selection Using Prediction and Modeling.

A predictive tool was developed to aid process design and to rationally select optimal solvents for isolation of active pharmaceutical ingredients. The objective was to minimize the experimental work required to design a purification process by (i) starting from a rationally selected crystallization solvent based on maximizing yield and minimizing solvent consumption (with the constraint of maintaining a suspension density which allows crystal suspension); (ii) for the crystallization solvent identified from step 1, a list of potential isolation solvents (selected based on a series of constraints) is ranked, based on thermodynamic consideration of yield and predicted purity using a mass balance model; and (iii) the most promising of the predicted combinations is verified experimentally, and the process conditions are adjusted to maximize impurity removal and maximize yield, taking into account mass transport and kinetic considerations. Here, we present a solvent selection workflow based on logical solvent ranking supported by solubility predictions, coupled with digital tools to transfer material property information between operations to predict the optimal purification strategy. This approach addresses isolation, preserving the particle attributes generated during crystallization, taking account of the risks of product precipitation and particle dissolution during washing, and the selection of solvents, which are favorable for drying.

Exploring the Role of Anti-solvent Effects during Washing on Active Pharmaceutical Ingredient Purity.

Washing is a key step in pharmaceutical isolation to remove the unwanted crystallization solvent (mother liquor) from the active pharmaceutical ingredient (API) filter cake. This study looks at strategies for optimal wash solvent selection, which minimizes the dissolution of API product crystals while preventing the precipitation of product or impurities. Selection of wash solvents to avoid both these phenomena can be challenging but is essential to maintain the yield, purity, and particle characteristics throughout the isolation process. An anti-solvent screening methodology has been developed to quantitatively evaluate the propensity for precipitation of APIs and their impurities of synthesis during washing. This is illustrated using paracetamol (PCM) and two typical impurities of synthesis during the washing process. The solubility of PCM in different binary wash solutions was measured to provide a basis for wash solvent selection. A map of wash solution composition boundaries for precipitation for the systems investigated was developed to depict where anti-solvent phenomena will take place. For some crystallization and wash solvent combinations investigated, as much as 90% of the dissolved PCM and over 10% of impurities present in the PCM saturated mother liquor were found to precipitate out. Such levels of uncontrolled crystallization during washing in a pharmaceutical isolation process can have a drastic effect on the final product purity. Precipitation of both the product and impurities from the mother liquor can be avoided by using a solvent in which the API has a solubility similar to that in the mother liquor; for example, the use of acetonitrile as a wash solvent does not result in precipitation of either the PCM API or its impurities. However, the high solubility of PCM in acetonitrile would result in noticeable dissolution of API during washing and would lead to agglomeration during the subsequent drying step. Contrarily, the use of n-heptane as a wash solvent for a PCM crystal slurry resulted in the highest amount of precipitation among the solvent pairs evaluated. This can be mitigated by designing a multi-stage washing strategy where wash solutions of differing wash solvent concentrations are used to minimize step changes in solubility when the mother liquor and the wash solvent come into contact.

Eosinophilic and Noneosinophilic Asthma: An Expert Consensus Framework to Characterize Phenotypes in a Global Real-Life Severe Asthma Cohort.

BACKGROUND: Phenotypic characteristics of patients with eosinophilic and noneosinophilic asthma are not well characterized in global, real-life severe asthma cohorts. RESEARCH QUESTION: What is the prevalence of eosinophilic and noneosinophilic phenotypes in the population with severe asthma, and can these phenotypes be differentiated by clinical and biomarker variables? STUDY DESIGN AND METHODS: This was an historical registry study. Adult patients with severe asthma and available blood eosinophil count (BEC) from 11 countries enrolled in the International Severe Asthma Registry (January 1, 2015-September 30, 2019) were categorized according to likelihood of eosinophilic phenotype using a predefined gradient eosinophilic algorithm based on highest BEC, long-term oral corticosteroid use, elevated fractional exhaled nitric oxide, nasal polyps, and adult-onset asthma. Demographic and clinical characteristics were defined at baseline (ie, 1 year before or closest to date of BEC). RESULTS: One thousand seven hundred sixteen patients with prospective data were included; 83.8% were identified as most likely (grade 3), 8.3% were identified as likely (grade 2), and 6.3% identified as least likely (grade 1) to have an eosinophilic phenotype, and 1.6% of patients showed a noneosinophilic phenotype (grade 0). Eosinophilic phenotype patients (ie, grades 2 or 3) showed later asthma onset (29.1 years vs 6.7 years; P < .001) and worse lung function (postbronchodilator % predicted FEV1, 76.1% vs 89.3%; P = .027) than those with a noneosinophilic phenotype. Patients with noneosinophilic phenotypes were more likely to be women (81.5% vs 62.9%; P = .047), to have eczema (20.8% vs 8.5%; P = .003), and to use anti-IgE (32.1% vs 13.4%; P = .004) and leukotriene receptor antagonists (50.0% vs 28.0%; P = .011) add-on therapy. INTERPRETATION: According to this multicomponent, consensus-driven, and evidence-based eosinophil gradient algorithm (using variables readily accessible in real life), the severe asthma eosinophilic phenotype was more prevalent than previously identified and was phenotypically distinct. This pragmatic gradient algorithm uses variables readily accessible in primary and specialist care, addressing inherent issues of phenotype heterogeneity and phenotype instability. Identification of treatable traits across phenotypes should improve therapeutic precision.

Characteristics of patients who had a stroke not initially identified during emergency prehospital assessment: a systematic review.

BACKGROUND: Around 25% of patients who had a stroke do not present with typical 'face, arm, speech' symptoms at onset, and are challenging for emergency medical services (EMS) to identify. The aim of this systematic review was to identify the characteristics of acute stroke presentations associated with inaccurate EMS identification (false negatives). METHOD: We performed a systematic search of MEDLINE, EMBASE, CINAHL and PubMed from 1995 to August 2020 using key terms: stroke, EMS, paramedics, identification and assessment. Studies included: patients who had a stroke or patient records; ≥18 years; any stroke type; prehospital assessment undertaken by health professionals including paramedics or technicians; data reported on prehospital diagnostic accuracy and/or presenting symptoms. Data were extracted and study quality assessed by two researchers using the Quality Assessment of Diagnostic Accuracy Studies V.2 tool. RESULTS: Of 845 studies initially identified, 21 observational studies met the inclusion criteria. Of the 6934 stroke and Transient Ischaemic Attack patients included, there were 1774 (26%) false negative patients (range from 4 (2%) to 247 (52%)). Commonly documented symptoms in false negative cases were speech problems (n=107; 13%-28%), nausea/vomiting (n=94; 8%-38%), dizziness (n=86; 23%-27%), changes in mental status (n=51; 8%-25%) and visual disturbance/impairment (n=43; 13%-28%). CONCLUSION: Speech problems and posterior circulation symptoms were the most commonly documented symptoms among stroke presentations that were not correctly identified by EMS (false negatives). However, the addition of further symptoms to stroke screening tools requires valuation of subsequent sensitivity and specificity, training needs and possible overuse of high priority resources.

Advancing the Patient EXperience (APEX) in COPD Registry: Study Design and Strengths.

The Advancing the Patient Experience (APEX) in Chronic Obstructive Pulmonary Disease (COPD) registry (https://www.apexcopd.org/) is the first primary care health system-based COPD registry in the United States. While its ultimate goal is to improve the care of patients diagnosed with COPD, the registry is also designed to describe real-life experiences of people with COPD, track key outcomes longitudinally, and assess the effectiveness of interventions. It will retrospectively and prospectively collect information from 3000 patients enrolled in 5 health care organizations. Information will be obtained from electronic health records, and from extended annual and brief questionnaires completed by patients before clinic visits. Core variables to be collected into the APEX COPD registry were agreed on by Delphi consensus and fall into 3 domains: demographics, COPD monitoring, and treatment. Main strengths of the registry include: 1) its size and scope (in terms of patient numbers, geographic spread and use of multiple information sources including patient-reported information); 2) collection of variables which are clinically relevant and practical to collect within primary care; 3) use of electronic data capture systems to ensure high-quality data and minimization of data-entry requirements; 4) inclusion of clinical, database development, management and communication experts; 5) regular sharing of key findings, both at international/national congresses and in peer-reviewed publications; and 6) a robust organizational structure to ensure continuance of the registry, and that research outputs are ethical, relevant and continue to bring value to both patients and physicians.

Development of the Advancing the Patient Experience in COPD Registry: A Modified Delphi Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is commonly managed by family physicians, but little is known about specifics of management and how this may be improved. The Advancing the Patient Experience in COPD (APEX COPD) registry will be the first U.S. primary care, health system-based registry following patients diagnosed with COPD longitudinally, using a standardized set of variables to investigate how patients are managed in real life and assess outcomes of various management strategies. OBJECTIVE: Gaining expert consensus on a standardized list of variables to capture in the APEX COPD registry. METHODS: A modified, Delphi process was used to reach consensus on which data to collect in the registry from electronic health records (EHRs), patient-reported information (PRI) and patient-reported outcomes (PRO), and by physicians during subsequent office visits. The Delphi panel comprised 14 primary care and specialty COPD experts from the United States and internationally. The process consisted of 3 iterative rounds. Responses were collected electronically. RESULTS: Of the initial 195 variables considered, consensus was reached to include up to 115 EHR variables, 34 PRI/PRO variables and 5 office-visit variables in the APEX COPD registry. These should include information on symptom burden, diagnosis, COPD exacerbations, lung function, quality of life, comorbidities, smoking status/history, treatment specifics (including side effects), inhaler management, and patient education/self-management. CONCLUSION: COPD experts agreed upon the core variables to collect from EHR data and from patients to populate the APEX COPD registry. Data will eventually be integrated, standardized and stored in the APEX COPD database and used for approved COPD-related research.

Understanding API Static Drying with Hot Gas Flow: Design and Test of a Drying Rig Prototype and Drying Modeling Development.

Developing a continuous isolation process to produce a pure, dry, free-flowing active pharmaceutical ingredient (API) is the final barrier to the implementation of continuous end-to-end pharmaceutical manufacturing. Recent work has led to the development of continuous filtration and washing prototypes for pharmaceutical process development and small-scale manufacture. Here, we address the challenge of static drying of a solvent-wet crystalline API in a fixed bed to facilitate the design of a continuous filter dryer for pharmaceutical development, without excessive particle breakage or the formation of interparticle bridges leading to lump formation. We demonstrate the feasibility of drying small batches on a time scale suitable for continuous manufacturing, complemented by the development of a drying model that provides a design tool for process development. We also evaluate the impact of alternative washing and drying approaches on particle agglomeration. We conclude that our approach yields effective technology, with a performance that is amenable to predictive modeling.

International severe asthma registry (ISAR): protocol for a global registry.

BACKGROUND: Severe asthma exerts a disproportionately heavy burden on patients and health care. Due to the heterogeneity of the severe asthma population, many patients need to be evaluated to understand the clinical features and outcomes of severe asthma in order to facilitate personalised and targeted care. The International Severe Asthma Registry (ISAR) is a multi-country registry project initiated to aid in this endeavour. METHODS: ISAR is a multi-disciplinary initiative benefitting from the combined experience of the ISAR Steering Committee (ISC; comprising 47 clinicians and researchers across 29 countries, who have a special interest and/or experience in severe asthma management or establishment and maintenance of severe asthma registries) in collaboration with scientists and experts in database management and communication. Patients (≥18 years old) receiving treatment according to the 2018 definitions of the Global Initiative for Asthma (GINA) Step 5 or uncontrolled on GINA Step 4 treatment will be included. Data will be collected on a core set of 95 variables identified using the Delphi method. Participating registries will agree to provide access to and share standardised anonymous patient-level data with ISAR. ISAR is a registered data source on the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance. ISAR's collaborators include Optimum Patient Care, the Respiratory Effectiveness Group (REG) and AstraZeneca. ISAR is overseen by the ISC, REG, the Anonymised Data Ethics & Protocol Transparency Committee and the ISAR operational committee, ensuring the conduct of ethical, clinically relevant research that brings value to all key stakeholders. CONCLUSIONS: ISAR aims to offer a rich source of real-life data for scientific research to understand and improve disease burden, treatment patterns and patient outcomes in severe asthma. Furthermore, the registry will provide an international platform for research collaboration in respiratory medicine, with the overarching aim of improving primary and secondary care of adults with severe asthma globally.

Developing a Batch Isolation Procedure and Running It in an Automated Semicontinuous Unit: AWL CFD25 Case Study.

A key challenge during the transition from laboratory/small batch to continuous manufacturing is the development of a process strategy that can easily be adopted for a larger batch/continuous process. Industrial practice is to develop the isolation strategy for a new drug/process in batch using the design of experiment (DoE) approach to determine the best isolation conditions and then transfer the isolation parameters selected to a large batch equipment/continuous isolation process. This stage requires a series of extra investigations to evaluate the effect of different equipment geometry or even the adaptation of the parameters selected to a different isolation mechanism (e.g., from dead end to cross flow filtration) with a consequent increase of R&D cost and time along with an increase in material consumption. The CFD25 is an isolation device used in the first instance to develop an isolation strategy in batch (optimization mode) using a screening DoE approach and to then verify the transferability of the strategy to a semicontinuous process (production mode). A d-optimal screening DoE was used to determine the effect of varying the input slurry. Properties such as solid loading, particle size distribution, and crystallization solvent were investigated to determine their impact on the filtration and washing performance and the characteristics of the dry isolated product. A series of crystallization (ethanol, isopropanol, and 3-methylbutan-1-ol) and wash solvents (n-heptane, isopropyl acetate and n-dodcane) were used for the process. To mimic a real isolation process, paracetamol-related impurities, acetanilide and metacetamol, were dissolved in the mother liquor. The selected batch isolation strategy was used for the semicontinuous isolation run. Throughput and filtration parameters, such as cake resistance and flow rate, cake residual liquid content and composition, cake purity, particle-particle aggregation, and extent and strength of agglomerates, were measured to evaluate the consistency of the isolated product produced during a continuous experiment and compared with the isolated product properties obtained during the batch process development. Overall, the CFD25 is a versatile tool which allows both new chemical entity process development in batch and the production of the active pharmaceutical ingredient in semicontinuous mode using the same process parameters without changing equipment. The isolated product properties gained during the semicontinuous run are overall comparable between samples. The residual solvent content and composition differs between some samples due to filter plate blockage. In general, the mean properties obtained during semicontinuous running are comparable with the product properties simulated using the DoE.

Improving acute stroke care in regional hospitals: clinical evaluation of the Victorian Stroke Telemedicine program.

OBJECTIVES: To evaluate the impact of the Victorian Stroke Telemedicine (VST) program during its first 12 months on the quality of care provided to patients presenting with suspected stroke to hospitals in regional Victoria. DESIGN: Historical controlled cohort study comparing outcomes during a 12-month control period with those for the initial 12 months of full implementation of the VST program at each hospital. SETTING: 16 hospitals in regional Victoria that participated in the VST program between 1 January 2010 and 30 January 2016. PARTICIPANTS: Adult patients with suspected stroke presenting to the emergency departments of the participating hospitals. MAIN OUTCOME MEASURES: Indicators for key processes of care, including symptom onset-to-arrival, door-to-first medical review, and door-to-CT times; provision and timeliness of provision of thrombolysis to patients with ischaemic stroke. RESULTS: 2887 patients with suspected stroke presented to participating emergency departments during the control period, 3178 during the intervention period; the patient characteristics were similar for both periods. A slightly larger proportion of patients with ischaemic stroke who arrived within 4.5 hours of symptom onset received thrombolysis during the intervention than during the control period (37% v 30%). Door-to-CT scan time (median, 25 min [IQR, 13-49 min] v 34 min [IQR, 18-76 min]) and door-to-needle time for stroke thrombolysis (73 min [IQR, 56-96 min] v 102 min [IQR, 77-128 min]) were shorter during the intervention. The proportions of patients who received thrombolysis and had a symptomatic intracerebral haemorrhage (4% v 16%) or died in hospital (6% v 20%) were smaller during the intervention period. CONCLUSIONS: Telemedicine has provided Victorian regional hospitals access to expert care for emergency department patients with suspected acute stroke. Eligible patients with ischaemic stroke are now receiving stroke thrombolysis more quickly and safely.