Multilingual Framework for Risk Assessment and Symptom Tracking (MRAST).

The importance and value of real-world data in healthcare cannot be overstated because it offers a valuable source of insights into patient experiences. Traditional patient-reported experience and outcomes measures (PREMs/PROMs) often fall short in addressing the complexities of these experiences due to subjectivity and their inability to precisely target the questions asked. In contrast, diary recordings offer a promising solution. They can provide a comprehensive picture of psychological well-being, encompassing both psychological and physiological symptoms. This study explores how using advanced digital technologies, i.e., automatic speech recognition and natural language processing, can efficiently capture patient insights in oncology settings. We introduce the MRAST framework, a simplified way to collect, structure, and understand patient data using questionnaires and diary recordings. The framework was validated in a prospective study with 81 colorectal and 85 breast cancer survivors, of whom 37 were male and 129 were female. Overall, the patients evaluated the solution as well made; they found it easy to use and integrate into their daily routine. The majority (75.3%) of the cancer survivors participating in the study were willing to engage in health monitoring activities using digital wearable devices daily for an extended period. Throughout the study, there was a noticeable increase in the number of participants who perceived the system as having excellent usability. Despite some negative feedback, 44.44% of patients still rated the app's usability as above satisfactory (i.e., 7.9 on 1-10 scale) and the experience with diary recording as above satisfactory (i.e., 7.0 on 1-10 scale). Overall, these findings also underscore the significance of user testing and continuous improvement in enhancing the usability and user acceptance of solutions like the MRAST framework. Overall, the automated extraction of information from diaries represents a pivotal step toward a more patient-centered approach, where healthcare decisions are based on real-world experiences and tailored to individual needs. The potential usefulness of such data is enormous, as it enables better measurement of everyday experiences and opens new avenues for patient-centered care.

Signal-to-noise ratio to assess magnitude, kinetics and impact on pharmacokinetics of the immune response to an adalimumab biosimilar.

Background: The antidrug antibody (ADA) signal-to-noise (S/N) ratio was explored as a novel immunogenicity measure to evaluate the immune response of healthy subjects to a single dose of GP2017, an adalimumab biosimilar. Methodology/results: Bioanalytical methods used for the analysis of ADA S/N ratios and ADA titers were validated for sensitivity, precision and drug interference. ADA S/N ratios strongly correlated with ADA titers. Correlations between ADA area under the curve and ADAmax and pharmacokinetics (PK) were stronger for ADA S/N ratio than for ADA titers. Conclusion: ADA S/N ratio allowed for a more sensitive evaluation of the magnitude and kinetics of the immune response, was better correlated with adalimumab PK and was superior to ADA titers in assessing the impact of the immune response on PK.

Establishing an Expert Consensus on Key Indicators of the Quality of Life among Breast Cancer Survivors: A Modified Delphi Study.

(1) Background: The needs of cancer survivors are often not reflected in practice. One of the main barriers of the use of patient-reported outcomes is associated with data collection and the interpretation of patient-reported outcomes (PROs) due to a multitude of instruments and measuring approaches. The aim of the study was to establish an expert consensus on the relevance and key indicators of quality of life in the clinical practice of breast cancer survivors. (2) Methods: Potential indicators of the quality of life of breast cancer survivors were extracted from the established quality of life models, depicting survivors' perspectives. The specific domains and subdomains of quality of life were evaluated in a two-stage online Delphi process, including an international and multidisciplinary panel of experts. (3) Results: The first round of the Delphi process was completed by 57 and the second by 37 participants. A consensus was reached for the Physical and Psychological domains, and on eleven subdomains of quality of life. The results were further supported by the additional ranking of importance of the subdomains in the second round. (4) Conclusions: The current findings can serve to optimize the use of instruments and address the challenges related to data collection and interpretation as the facilitators of the adaption in routine practice.

"I Don't Even Want to Come Out": the Suppressed Voices of Our Future and Opening the Lid on Sexual and Gender Minority Youth Workplace Discrimination in Europe: a Qualitative Study.

Introduction: In Europe, young sexual and gender minority (SGM) people continue to face discrimination in the labour sector despite advances in legislation towards their acceptance and equal treatment. Non-discrimination policy strategies helping SGM individuals are not equally enforced in all contexts, making it difficult for many SGM individuals to disclose their identity, hence undermining their health and well-being. Methods: Qualitative semi-structured interviews were conducted between October 2020 and February 2021 with 55 SGM youth (18-27 years) having work experience from Austria, Croatia, Serbia, Slovakia, Spain and the UK. Results: From the analysis, three overarching themes were significant: (1) societal discrimination played a major role in sociocultural factors and policy considerations, (2) workplace discrimination had distinct factors and impacts on SGM individuals and (3) SGM inclusion should use strategies to ensure workplace diversity and equality. Conclusions: SGM individuals from contexts of poor acceptance tended to hide their identity in the workplace, while transgender and non-binary individuals were prone to experience force-disclosure and discrimination in all aspects of employment. There is a lack of resolute reaction from policy makers in managing problems faced by SGM people in workplaces. New laws improving the status of SGM people need to be further adopted, staff training should be implemented, and managers are crucial in achieving an inclusive climate in the workplace.Policy ImplicationsIt is essential to implement policies on how to effectively handle problems faced by sexual and gender minority people in the workplace.

Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors.

BACKGROUND: It is encouraging to see a substantial increase in individuals surviving cancer. Even more so since most of them will have a positive effect on society by returning to work. However, many cancer survivors have unmet needs, especially when it comes to improving their quality of life (QoL). Only few survivors are able to meet all of the recommendations regarding well-being and there is a body of evidence that cancer survivors' needs often remain neglected from health policy and national cancer control plans. This increases the impact of inequalities in cancer care and adds a dangerous component to it. The inequalities affect the individual survivor, their career, along with their relatives and society as a whole. The current study will evaluate the impact of the use of big data analytics and artificial intelligence on the self-efficacy of participants following intervention supported by digital tools. The secondary endpoints include evaluation of the impact of patient trajectories (from retrospective data) and patient gathered health data on prediction and improved intervention against possible secondary disease or negative outcomes (e.g. late toxicities, fatal events). METHODS/DESIGN: The study is designed as a single-case experimental prospective study where each individual serves as its own control group with basal measurements obtained at the recruitment and subsequent measurements performed every 6 months during follow ups. The measurement will involve CASE-cancer, Patient Activation Measure and System Usability Scale. The study will involve 160 survivors (80 survivors of Breast Cancer and 80 survivors of Colorectal Cancer) from four countries, Belgium, Latvia, Slovenia, and Spain. The intervention will be implemented via a digital tool (mHealthApplication), collecting objective biomarkers (vital signs) and subjective biomarkers (PROs) with the support of a (embodied) conversational agent. Additionally, the Clinical Decision Support system (CDSS), including visualization of cohorts and trajectories will enable oncologists to personalize treatment for an efficient care plan and follow-up management. DISCUSSION: We expect that cancer survivors will significantly increase their self-efficacy following the personalized intervention supported by the m-HealthApplication compared to control measurements at recruitment. We expect to observe improvement in healthy habits, disease self-management and self-perceived QoL. Trial registration ISRCTN97617326. https://doi.org/10.1186/ISRCTN97617326 . Original Registration Date: 26/03/2021.

Step-wise approach to developing a scale-independent design space for functional tablet coating process.

The objective of this study is to present a practical example of a scale-independent design space development using a step-wise approach. A detailed description of the development process with a systematic outline of the main steps is provided. Design space is developed for film coating of tablets with moisture protective polyvinyl alcohol (PVA) based coating. The impact of scale-independent coating process parameters on the properties of film-coated tablets (FCT), i.e. water activity and film coating protection ability, and consequently on product long-term stability is explored. The main finding is that with model simplifications, a step-wise approach and rational development of scale-independent design space for the coating process, it is possible to efficiently predict, control, and optimize the long-term stability of a moisture sensitive product. However, the PVA moisture protective coating itself is recognized as having conflicting effects on product stability.

Elucidating molecular properties of kappa-carrageenan as critical material attributes contributing to drug dissolution from pellets with a multivariate approach.

Multivariate data analysis (MVDA) and artificial neural networks (ANN) are supporting statistical methodologies required for successful development and manufacturing of drug products. To address this purpose, a complex dataset from 49 industrially produced capsules filled with pellets was first analyzed through the development of a multiple linear regression model focused on determining raw material attributes or process parameters with a significant impact on drug dissolution. Based on the model, the following molecular and micrometrics properties of κ-carrageenan have been identified as critical material attributes with the highest contribution to drug dissolution: molecular weight and polydispersity index, viscosity, content of potassium ions, wettability, particle size, and density. The process parameters identified to control the drug dissolution behavior of pellets were amount of granulation liquid, torque of dry blend, spheronization parameters, and yields after screening. To further scrutinize the dataset, an ANN model was subsequently built, incorporating 29 batches addressing drug particle size and process parameters such as torque during granulation and spheronization time as critical factors. Finally, this study demonstrates the ability of MVDA and ANN to allow prediction of the key performance drivers influencing the drug dissolution of industrially developed capsules filled with pellets and it highlights their complementary relationship.

Diffuse large B-cell lymphoma: 10 years' real-world clinical experience with rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisolone.

Treatment with rituximab plus a regimen of cyclophosphamide, doxorubicin, vincristine and prednisolone (CHOP) for patients with diffuse large B-cell lymphoma (DLBCL) has proven efficacy in clinical trials. The present study investigated its application in clinical practice. This single-center, retrospective database analysis included patients with DLBCL treated at the Slovenian Institute of Oncology Ljubljana between 2004 and 2013. Overall survival (OS) and progression-free survival (PFS) were assessed according to International Prognostic Index (IPI) and revised IPI (R-IPI) categories. Overall, 573 patients with DLBCL were included in the study (median follow-up, 45.3 months; range, 0.1-143.0). Patients were categorized as IPI 'low' (n=170; 30%), 'low-intermediate' (n=134; 23%), 'high-intermediate' (n=129; 23%) and 'high' (n=140; 24%) risk. R-IPI groups were indicated with 'very good' (n=59; 10%), 'good' (n=245; 43%) and 'poor' (n=269; 47%) prognosis. Ten-year OS and PFS rates were 51 and 72%, respectively; median OS was 124 months and median PFS was not reached. Ten-year OS rates were 80 and 87% in low-risk and 'very good' prognosis groups, respectively, and 30 and 37% in high-risk and poor prognosis patients, respectively. This analysis of patients with DLBCL indicated that many patients treated with R-CHOP and R-CHOP-like regimens in the real-world setting have excellent outcomes.

Scientific, statistical, practical, and regulatory considerations in design space development.

The quality by design (QbD) paradigm guides the pharmaceutical industry towards improved understanding of products and processes, and at the same time facilitates a high degree of manufacturing and regulatory flexibility throughout the establishment of the design space. This review article presents scientific, statistical and regulatory considerations in design space development. All key development milestones, starting with planning, selection of factors, experimental execution, data analysis, model development and assessment, verification, and validation, and ending with design space submission, are presented and discussed. The focus is especially on frequently ignored topics, like management of factors and CQAs that will not be included in experimental design, evaluation of risk of failure on design space edges, or modeling scale-up strategy. Moreover, development of a design space that is independent of manufacturing scale is proposed as the preferred approach.

Single Nucleotide Polymorphisms in Genes MACC1, RAD18, MMP7 and SDF-1a As Prognostic Factors in Resectable Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) represents one of the most common malignancies worldwide. Research has indicated that functional gene changes such as single nucleotide polymorphism (SNP) influence carcinogenesis and metastasis and might have an influence on disease relapse. The aim of our study was to evaluate the role of SNPs in selected genes as prognostic markers in resectable CRC. PATIENTS AND METHODS: In total, 163 consecutive patients treated surgically for CRC of stages I, II and III at the University Medical Centre in Maribor in 2007 and 2008 were investigated. DNA was isolated from formalin-fixed paraffin-embedded CRC tissue from the Department of Pathology and SNPs in genes SDF-1a, MMP7, RAD18 and MACC1 were genotyped using polymerase chain reaction followed by high resolution melting curve analysis or restriction fragment length polymorphism. RESULTS: We found worse disease-free survival (DFS) for patients with TT genotype of SNP rs1990172 in gene MACC1 (p = 0.029). Next, we found worse DFS for patients with GG genotype for SNP rs373572 in gene RAD18 (p = 0.020). Higher frequency of genotype GG of MMP7 SNP rs11568818 was found in patients with T3/T4 stage (p = 0.014), N1/N2 stage (p = 0.041) and with lymphovascular invasion (p = 0.018). For MACC1 rs1990172 SNP we found higher frequency of genotype TT in patients with T3/T4 staging (p = 0.024). Higher frequency of genotype GG of RAD18 rs373572 was also found in patients with T1/T2 stage with disease relapse (p = 0.041). CONCLUSIONS: Our results indicate the role of SNPs as prognostic factors in resectable CRC.

The interprocess NIR sampling as an alternative approach to multivariate statistical process control for identifying sources of product-quality variability.

We are presenting a new approach of identifying sources of variability within a manufacturing process by NIR measurements of samples of intermediate material after each consecutive unit operation (interprocess NIR sampling technique). In addition, we summarize the development of a multivariate statistical process control (MSPC) model for the production of enteric-coated pellet product of the proton-pump inhibitor class. By developing provisional NIR calibration models, the identification of critical process points yields comparable results to the established MSPC modeling procedure. Both approaches are shown to lead to the same conclusion, identifying parameters of extrusion/spheronization and characteristics of lactose that have the greatest influence on the end-product's enteric coating performance. The proposed approach enables quicker and easier identification of variability sources during manufacturing process, especially in cases when historical process data is not straightforwardly available. In the presented case the changes of lactose characteristics are influencing the performance of the extrusion/spheronization process step. The pellet cores produced by using one (considered as less suitable) lactose source were on average larger and more fragile, leading to consequent breakage of the cores during subsequent fluid bed operations. These results were confirmed by additional experimental analyses illuminating the underlying mechanism of fracture of oblong pellets during the pellet coating process leading to compromised film coating.

Single Nucleotide Polymorphisms as Prognostic and Predictive Factors of Adjuvant Chemotherapy in Colorectal Cancer of Stages I and II.

Colorectal cancer (CRC) is a highly heterogeneous disease regarding the stage at time of diagnosis and there is special attention regarding adjuvant chemotherapy in unselected patients with stage I and stage II. The clinicohistologically based TNM staging system with emphasis on histological evaluation of primary tumor and resected regional lymph nodes remains the standard of staging, but it has restricted sensitivity resulting in false downward stage migration. Molecular characteristics might predispose tumors to a worse prognosis and identification of those enables identifying patients with high risk of disease recurrence. Suitable predictive markers also enable choosing the most appropriate therapy. The current challenge facing adjuvant chemotherapy in stages I and II CRC is choosing patients with the highest risk of disease recurrence who are going to derive most benefit without facing unnecessary adverse effects. Single nucleotide polymorphisms (SNPs) are one of the potential molecular markers that might help us identify patients with unfavorable prognostic factors regarding disease initiation and recurrence and could determine selection of an appropriate chemotherapy regimen in the adjuvant and metastatic setting. In this paper, we discuss SNPs of genes involved in the multistep processes of cancerogenesis, metastasis, and the metabolism of chemotherapy that might prove clinically significant.

High-throughput automated dissolution method applicable for a wide dose range of controlled release pellets.

The aim of the present study was to demonstrate the application of an automated high-throughput (HT) dissolution method as a useful screening tool for characterization of controlled release pellets in the formulation development phase. Five controlled release pellet formulations with drug substances exhibiting high or low solubility were chosen to investigate the correlation of the automated HT dissolution method with the conventional dissolution testing. Overall, excellent correlations (R(2 )>( )0.96) between the HT and the conventional dissolution method were obtained. In one case the initial unsatisfactory correlation (R(2 )=( )0.84) and poor method agreement (SD = 12.5) was improved by optimizing the HT dissolution method with design of experiment approach. Here in comparison to initial experimental HT dissolution settings, increased amount of pellets (25% of the capsule filling mass), lower temperature (22 °C) and no shaking resulted in significantly better correlation (R(2 )=( )0.97) and method agreement (SD = 5.3). These results show that such optimization is valuable for the development of HT dissolution methods. In conclusion, the high correlation of dissolution profiles obtained from the conventional and the automated HT dissolution method combined with low within-sample and measurement system variability, justifies the utilization of the automated HT dissolution method during development phase of controlled release pellets.

Clinical-pharmacist intervention reduces clinically relevant drug-drug interactions in patients with heart failure: A randomized, double-blind, controlled trial.

BACKGROUND: Incidence of drug-drug interactions (DDIs) increases with complexity of treatment and comorbidities, as in heart failure (HF). This randomized, double-blind study evaluated the intervention of the pharmacist on prevalence of clinically relevant DDIs (NCT01855165). METHODS: Patients admitted with HF were screened for clinically relevant DDIs, and randomized to control or intervention. All attending physicians received standard advice about pharmacological therapy; those in the intervention group also received alerts about clinically relevant DDIs. Primary endpoint was DDI at discharge and secondary were re-hospitalization or death during follow-up. RESULTS: Of 213 patients, 51 (mean age, 79 ± 6 years; male, 47%) showed 66 clinically relevant DDIs and were randomized. For intervention (n=26) versus control (n=25), the number of patients with and the number of DDIs were significantly lower at discharge: 8 vs. 18 and 10 vs. 31; p=0.003 and 0.0049, respectively. Over a 6 month follow-up period, 11 control and 9 intervention patients were re-hospitalized or died (p>0.2 for all). No significant differences were seen between control and intervention for patients with eGFR <60 mL/min/1.73 m(2) (78%) for re-hospitalization or death (10 vs. 7; p=0.74). CONCLUSIONS: Pharmacist intervention significantly reduces the number of patients with clinically relevant DDIs, but not clinical endpoints 6 months from discharge.

In-line NIR monitoring of key characteristics of enteric coated pellets.

We describe the development of an in-line monitoring approach for the fluid-bed drying and coating steps for the production of enteric coated pellets by NIR. Our results show that key pellet characteristics can be monitored in-line. Likewise, the finished product acidic resistance is in excellent agreement to the in-line NIR predictions. Samples were collected at regular intervals and analyzed by several reference methods to characterize both process steps. In-line NIR models for pellets size sieve fractions, residual solvent content, and amount of coating layer have been constructed. Both the pellet coating layer amount and the in-vitro enteric performance demonstrate low variability which represents a challenge to the usual chemometric model development approach. To overcome this challenge a hierarchical PLS model for predicting acidic resistance was successfully constructed using time-evolving spectral data from 22 batches. Moreover, a novel multivariate meta-analysis of the PLS loadings of individual in-line models and the hierarchical PLS model has identified which pellet characteristics correlate most significantly with the observed enteric performance of the finished product. Additionally, the meta-analysis pointed toward the presence of further mechanisms unrelated to studied characteristics that also significantly influence the acidic resistance.

Integrating artificial and human intelligence into tablet production process.

We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

Rapid exploration of curing process design space for production of controlled-release pellets.

Time and cost are among the most often cited hurdles limiting the rate and extent of adoption of Quality by Design (QbD) and Process Analytical Technology. In this article, we demonstrate that, with appropriate techniques, a key QbD element can be achieved with amount of resources comparable to classical development approach. To control the dissolution rate of a highly soluble drug substance from latex polymer coated pellets, we have examined the effect of key variables affecting the curing process step by an experimental design study. To explore and characterize the Design Space, we have produced and tested 62 distinct pellet samples. To achieve this in a reasonable amount of time, we have developed a scaled-down automated dissolution method that demonstrated excellent correlation to the classical method. By careful planning of experimentation, we were able to obtain all samples from just two batches of pellet cores. The curing process Design Space was explored by statistical modeling of samples obtained from the first batch. Robustness and repeatability of the Design Space at the edge of failure was preliminarily investigated by analysis of selected samples from the second batch with encouraging results.

Correlating cellulose derivative intrinsic viscosity with mechanical susceptibility of swollen hydrophilic matrix tablets.

Hydrophilic matrix tablets are prone to mechanical stress while passing through the gastrointestinal tract, which may result in inappropriate drug-release characteristics. Intrinsic viscosity is a physical polymer property that can be directly compared across various types and grades of polymers and correlated with the mechanical susceptibility of swollen matrix tablets. Five tablet formulations containing different HPMC and HPC polymers were prepared and analyzed using an in vitro glass bead manipulation test. The dissolution rate results were modeled using the Korsmeyer-Peppas equation and a correlation was found between the fit constants k and n, goodness-of-fit measure parameters, and intrinsic viscosity. Moreover, the dissolution profiles were used to calculate the degree of mechanical susceptibility for each formulation, defined as the ratio of the average dissolution rate after manipulation and the initial dissolution rate before manipulation. It was confirmed that an increased intrinsic viscosity polymer value resulted in a decrease in mechanical susceptibility. Considering this, two simple rules were defined for designing robust matrix tablets with respect to mechanical stresses.

Microsatellite instability in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer in the world. In 75% CRC develops sporadically, in 25% hereditary or as a consequence of inflammatory bowel disease. CRC carcinogenesis develops over many years. The cause of CRC in 85% is chromosomal instability (CIN) and in 15% microsatellite instability (MSI-H), where hereditary nonpolyposis colorectal cancer (HNPCC) represents 10-20%. Microsatellite sequences (MS) are repeated sequences of short stretches of DNA all over the genome. Microsatellite stability (MSS) means MS are the same in each cell of an individual, whereas microsatellite instability (MSI-H) means MS differ in normal and cancer cells of an individual. The cause of MSI-H is a damaged mismatch repair mechanism (MMR), with the most important MMR proteins being MSH2, MLH1 and MSH6. CONCLUSIONS: MSI-H seems to be an important prognostic factor in CRC and an important predictive factor of CRC chemotherapeutic treatment efficacy. Clinical trials conducted until now have shown contradictory findings in different chemotherapeutic settings, adjuvant and palliative; therefore MSI-H is going to be the object of the future research. The future of cancer treatment is in the individualized therapy based on molecular characteristics of the tumour, such as MSI-H in CRC.

Aerosol lidar intercomparison in the framework of the EARLINET project. 2. Aerosol backscatter algorithms.

An intercomparison of aerosol backscatter lidar algorithms was performed in 2001 within the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET). The objective of this research was to test the correctness of the algorithms and the influence of the lidar ratio used by the various lidar teams involved in the EARLINET for calculation of backscatter-coefficient profiles from the lidar signals. The exercise consisted of processing synthetic lidar signals of various degrees of difficulty. One of these profiles contained height-dependent lidar ratios to test the vertical influence of those profiles on the various retrieval algorithms. Furthermore, a realistic incomplete overlap of laser beam and receiver field of view was introduced to remind the teams to take great care in the nearest range to the lidar. The intercomparison was performed in three stages with increasing knowledge on the input parameters. First, only the lidar signals were distributed; this is the most realistic stage. Afterward the lidar ratio profiles and the reference values at calibration height were provided. The unknown height-dependent lidar ratio had the largest influence on the retrieval, whereas the unknown reference value was of minor importance. These results show the necessity of making additional independent measurements, which can provide us with a suitable approximation of the lidar ratio. The final stage proves in general, that the data evaluation schemes of the different groups of lidar systems work well.