A model-informed clinical trial simulation tool with a graphical user interface for Duchenne muscular dystrophy.

Quantitative model-based clinical trial simulation tools play a critical role in informing study designs through simulation before actual execution. These tools help drug developers explore various trial scenarios in silico to select a clinical trial design to detect therapeutic effects more efficiently, therefore reducing time, expense, and participants' burden. To increase the usability of the tools, user-friendly and interactive platforms should be developed to navigate various simulation scenarios. However, developing such tools challenges researchers, requiring expertise in modeling and interface development. This tutorial aims to address this gap by guiding developers in creating tailored R Shiny apps, using an example of a model-based clinical trial simulation tool that we developed for Duchenne muscular dystrophy (DMD). In this tutorial, the structural framework, essential controllers, and visualization techniques for analysis are described, along with key code examples such as criteria selection and power calculation. A virtual population was created using a machine learning algorithm to enlarge the available sample size to simulate clinical trial scenarios in the presented tool. In addition, external validation of the simulated outputs was conducted using a placebo arm of a recently published DMD trial. This tutorial will be particularly useful for developing clinical trial simulation tools based on DMD progression models for other end points and biomarkers. The presented strategies can also be applied to other diseases.

Type 1 diabetes prevention clinical trial simulator: Case reports of model-informed drug development tool.

Clinical trials seeking to delay or prevent the onset of type 1 diabetes (T1D) face a series of pragmatic challenges. Despite more than 100 years since the discovery of insulin, teplizumab remains the only FDA-approved therapy to delay progression from Stage 2 to Stage 3 T1D. To increase the efficiency of clinical trials seeking this goal, our project sought to inform T1D clinical trial designs by developing a disease progression model-based clinical trial simulation tool. Using individual-level data collected from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies, we previously developed a quantitative joint model to predict the time to T1D onset. We then applied trial-specific inclusion/exclusion criteria, sample sizes in treatment and placebo arms, trial duration, assessment interval, and dropout rate. We implemented a function for presumed drug effects. To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. Using this tool, power curves can also be generated through iterations. The web-based tool is publicly available: https://app.cop.ufl.edu/t1d/. Herein, we briefly describe the tool and provide instructions for simulating a planned clinical trial with two case studies. This tool will allow for improved clinical trial designs and accelerate efforts seeking to prevent or delay the onset of T1D.

Five multivariate Duchenne muscular dystrophy progression models bridging six-minute walk distance and MRI relaxometry of leg muscles.

The study aimed to provide quantitative information on the utilization of MRI transverse relaxation time constant (MRI-T2) of leg muscles in DMD clinical trials by developing multivariate disease progression models of Duchenne muscular dystrophy (DMD) using 6-min walk distance (6MWD) and MRI-T2. Clinical data were collected from the prospective and longitudinal ImagingNMD study. Disease progression models were developed by a nonlinear mixed-effect modeling approach. Univariate models of 6MWD and MRI-T2 of five muscles were developed separately. Age at assessment was the time metric. Multivariate models were developed by estimating the correlation of 6MWD and MRI-T2 model variables. Full model estimation approach for covariate analysis and five-fold cross validation were conducted. Simulations were performed to compare the models and predict the covariate effects on the trajectories of 6MWD and MRI-T2. Sigmoid Imax and Emax models best captured the profiles of 6MWD and MRI-T2 over age. Steroid use, baseline 6MWD, and baseline MRI-T2 were significant covariates. The median age at which 6MWD is half of its maximum decrease in the five models was similar, while the median age at which MRI-T2 is half of its maximum increase varied depending on the type of muscle. The models connecting 6MWD and MRI-T2 successfully quantified how individual characteristics alter disease trajectories. The models demonstrate a plausible correlation between 6MWD and MRI-T2, supporting the use of MRI-T2. The developed models will guide drug developers in using the MRI-T2 to most efficient use in DMD clinical trials.

Multivariate modeling of magnetic resonance biomarkers and clinical outcome measures for Duchenne muscular dystrophy clinical trials.

Although regulatory agencies encourage inclusion of imaging biomarkers in clinical trials for Duchenne muscular dystrophy (DMD), industry receives minimal guidance on how to use these biomarkers most beneficially in trials. This study aims to identify the optimal use of muscle fat fraction biomarkers in DMD clinical trials through a quantitative disease-drug-trial modeling and simulation approach. We simultaneously developed two multivariate models quantifying the longitudinal associations between 6-minute walk distance (6MWD) and fat fraction measures from vastus lateralis and soleus muscles. We leveraged the longitudinal individual-level data collected for 10 years through the ImagingDMD study. Age of the individuals at assessment was chosen as the time metric. After the longitudinal dynamic of each measure was modeled separately, the selected univariate models were combined using correlation parameters. Covariates, including baseline scores of the measures and steroid use, were assessed using the full model approach. The nonlinear mixed-effects modeling was performed in Monolix. The final models showed reasonable precision of the parameter estimates. Simulation-based diagnostics and fivefold cross-validation further showed the model's adequacy. The multivariate models will guide drug developers on using fat fraction assessment most efficiently using available data, including the widely used 6MWD. The models will provide valuable information about how individual characteristics alter disease trajectories. We will extend the multivariate models to incorporate trial design parameters and hypothetical drug effects to inform better clinical trial designs through simulation, which will facilitate the design of clinical trials that are both more inclusive and more conclusive using fat fraction biomarkers.

Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies.

Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short-term) trial durations. Hence, we sought to improve such efforts by developing a quantitative disease progression model for type 1 diabetes. Individual-level data obtained from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies were used to develop a joint model that links the longitudinal glycemic measure to the timing of type 1 diabetes diagnosis. Baseline covariates were assessed using a stepwise covariate modeling approach. Our study focused on individuals at risk of developing type 1 diabetes with the presence of two or more diabetes-related autoantibodies (AAbs). The developed model successfully quantified how patient features measured at baseline, including HbA1c and the presence of different AAbs, alter the timing of type 1 diabetes diagnosis with reasonable accuracy and precision (<30% RSE). In addition, selected covariates were statistically significant (p < 0.0001 Wald test). The Weibull model best captured the timing to type 1 diabetes diagnosis. The 2-h oral glucose tolerance values assessed at each visit were included as a time-varying biomarker, which was best quantified using the sigmoid maximum effect function. This model provides a framework to quantitatively predict and simulate the time to type 1 diabetes diagnosis in individuals at risk of developing the disease and thus, aligns with the needs of pharmaceutical companies and scientists seeking to advance therapies aimed at interdicting the disease process.

Chronotype, Time of Day, and Performance on Intelligence Tests in the School Setting.

Research suggests the existence of an association between chronotype and intellectual performance, but the nature of this link remains unclear. Studies conducted in a laboratory setting point to the synchrony effect (better performance at a person's preferred time of day) for fluid intelligence, but not for crystallized intelligence, whereas studies that have analyzed students' grades suggest that the effect exists for both. In the present study, we aimed to verify the synchrony effect by applying direct measures of crystallized intelligence, fluid intelligence, and subjective sleepiness-alertness in a sample of high school students during their morning or afternoon class. The results revealed a synchrony effect for crystallized, but not for fluid intelligence. During morning class, students with a morning chronotype performed better than evening chronotypes on a test of crystallized intelligence, whereas during afternoon class there was no difference between chronotypes. The association resulted from decreased performance during morning class in evening chronotypes that improved during afternoon class and constant performance in morning chronotypes. These effects were independent of sleepiness-alertness levels. The results suggest that individual differences between chronotypes may be important for tasks performed during morning classes, but not during afternoon ones, and that performance across school days may depend on time of day in evening chronotypes.

Development of a model-based clinical trial simulation platform to optimize the design of clinical trials for Duchenne muscular dystrophy.

Early clinical trials of therapies to treat Duchenne muscular dystrophy (DMD), a fatal genetic X-linked pediatric disease, have been designed based on the limited understanding of natural disease progression and variability in clinical measures over different stages of the continuum of the disease. The objective was to inform the design of DMD clinical trials by developing a disease progression model-based clinical trial simulation (CTS) platform based on measures commonly used in DMD trials. Data were integrated from past studies through the Duchenne Regulatory Science Consortium founded by the Critical Path Institute (15 clinical trials and studies, 1505 subjects, 27,252 observations). Using a nonlinear mixed-effects modeling approach, longitudinal dynamics of five measures were modeled (NorthStar Ambulatory Assessment, forced vital capacity, and the velocities of the following three timed functional tests: time to stand from supine, time to climb 4 stairs, and 10 meter walk-run time). The models were validated on external data sets and captured longitudinal changes in the five measures well, including both early disease when function improves as a result of growth and development and the decline in function in later stages. The models can be used in the CTS platform to perform trial simulations to optimize the selection of inclusion/exclusion criteria, selection of measures, and other trial parameters. The data sets and models have been reviewed by the US Food and Drug Administration and the European Medicines Agency; have been accepted into the Fit-for-Purpose and Qualification for Novel Methodologies pathways, respectively; and will be submitted for potential endorsement by both agencies.

The Parent's Chronotype and Child's Sleeping Quality in Association with Relationship Satisfaction.

The prospective Ulm-SPATZ study was investigated to assess the role of child sleeping quality between 4 to 6 years of age in affecting a partner's sleeping and relationship satisfaction within a couple. The study was conducted using a triadic approach in which the child was included in the Actor-Partner-Interdependence Model (APIM). Sleeping quality of the child was determined by using the German version of the children's sleep habits questionnaire, sleeping features of the parents were assessed by using the Munich chronotype questionnaire, and the partner relationship assessment was performed by employing the German version of the parenting stress index questionnaire. In 211 German triads, we observed that sleeping characteristics and partner relationship scores at different child ages are consistent for both men and women. Higher and statistically significant sleep duration, time spent in bed, the midpoint of sleep, time getting out of bed, and sleep onset in women compared to men during the working days were observed. The APIM analyses showed a significant direct effect of child sleep quality on the partner relationship satisfaction. In women, a mediated effect of child sleep quality acted through sleep duration and time spent in bed on the partner relationship satisfaction score during both free and working days. In men, low child sleep quality was found to be associated with increased sleep onset during both free and working days. Child sleep quality influences relationship satisfaction mostly in mothers, likely because of their higher involvement in childcare during working days. Distress in the couple could be counteracted by a major involvement of the fathers in child management.

Complex Gait Is Related to Cognitive Functioning in Older People: A Cross-Sectional Study Providing an Innovative Test.

BACKGROUND: Many studies have demonstrated an inverse relationship between gait performance and cognitive impairment. The main purposes of this study were: (1) to design and validate a complex gait test (CGT) in older people, (2) to analyze the effects of age and sex on CGT, and (3) to analyze the association between CGT performance and physical functioning and cognitive measures. METHODS: A total of 279 older people (60-97 years) were analyzed in 2019. Fitness tests, gait performance, and several cognitive measures such asthe Trail-Walking Test and Montreal Cognitive Assessment were used. RESULTS: The CGT reported adequate reliability and validity parameters. In the test-retest analysis, the intra-class correlation coefficient was 0.868 (p < 0.001). There was a significant correlation between the CGT and Trail-Walking Test (r = 0.592; p < 0.001). The linear regression analysis showed that the CGT was associated with the Montreal Cognitive Assessment (R2 = 0.357; p =0.001). The binary logistic regression analysis revealed that a high CGT score was a risk factor for mild cognitive impairment (odds ratio 1.201, 95% CI 1.081-1.334; p = 0.001). The ROC curve of the mild cognitive impairment was predicted by the CGT performance (area under the curve = 0.768, 95% CI 0.647-0.889; p < 0.001), reaching the cut-off point at 20.25 s. CONCLUSIONS: The CGT showed good reliability and validity and may serve as a potential biomarker in mild cognitive impairment prediction in older adults aged 60-97 years.

Machine Learning in Drug Discovery and Development Part 1: A Primer.

Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.

Chronotype and time-of-day effects on mood during school day.

Existing evidence suggests an association between mood, time-of-day and morningness-eveningness (M-E). Since few studies have been carried out among adolescents, in this study daily mood fluctuations were analyzed in the naturalistic school context during 2 d in order to test how chronotype and time-of-day are related to mood during the school schedule period and check if sleep length is involved in the above relation. A sample of 655 adolescents (12-16 years) reported mood levels (current level of pleasantness) three times during school day (8:10-8:30 h, 10:20-11:40 h, 13:50-14:10 h). They also reported M-E preference and time in bed. Neither age nor sex were related to mood. However, the results indicated that regardless of chronotype mood increased throughout the school day from the lowest morning levels. Moreover, morning types showed better mood compared to other chronotypes, while evening types exhibited the lowest mood. Evening-oriented students slept less than other chronotypes, but time in bed was not involved in the relationship between chronotype and mood. These results suggest that it is not shortened sleep duration responsible for decreased mood in evening-oriented students.

Chronotype, gender, and time for sex.

The study aimed at testing chronotype and gender differences in the time of day when humans feel the greatest need for sex and the time of day they actually undertake sexual activity. A Polish sample of 565 participants aged between 18 and 57 was tested. In females, regardless of chronotype, the greatest need for sex occurred between 18:00 and 24:00, but a secondary peak appeared only in morning types at 6:00-9:00. In males, the greatest need for sex occurred either in the morning or evening hours: in evening types at 9:00-12:00 and 18:00-3:00; in neither types at 6:00-9:00 and 18:00-24:00; in morning types at 6:00-12:00 and 18:00-24:00. Considering time of day when subjects were undertaking sexual activity most frequently, this appeared between 18:00 and 24:00 for all the participants, and prolonged until 3:00 at night in evening type males. Morningness preference was more strongly related to the timing of need for sex than to the timing of actual sexual activity (r = -0.275 vs. r = -0.174), while the timing of desire and the timing of sexual activity were positively, but moderately related (r = 0.320).

Evening adolescents: the role of family relationships and pubertal development.

Accumulating evidence suggests that evening-type adolescents are exposed to a number of determinants that might have a negative impact on their health condition. Despite the fact that biological and psychosocial factors are interrelated, their impacts on the shift toward eveningness during puberty have been considered only separately. In this study, the effects of frequency of conflicts and functional autonomy on the relationship between pubertal development and Morningness-Eveningness (M-E) were tested together. A sample of 2081 adolescents aged 12-16 completed pubertal development, M-E, family frequency of conflicts and functional autonomy scales. Results indicated that greater functional autonomy and more conflicts in the family were unique predictors of greater eveningness, and they both together were better predictors of M-E than an advanced age and pubertal development. Apart from biological development, family relationship seems an important factor explaining progressive tendency toward eveningness during puberty and adolescence. Some implications to adolescent development were indicated.

Daily fluctuations in attention at school considering starting time and chronotype: an exploratory study.

Interest to investigate daily fluctuations in cognitive tasks, so-called "school-rhythms", lies in exploring the most favourable time-of-day for learning considering the analysis of variations in performance taking into account individual differences. The aim of this study was to describe daily fluctuations in attention at three different times of the school day, two different days, considering chronotype and three different school start times (08:00, 08:15 and 08:30 h). Participants were 669 adolescents aged 12-16. Sleep length and inductive reasoning were considered as covariates. In general, attention increased throughout the school day, boys reached higher attention than girls and, moreover, evening type boys reached higher attention than evening type girls. No differences between chronotypes were observed. When students were familiar with the task, chronotype, sex and time-of-day interactions seem to be important factors to consider.

Hemisphere Preference Test: psychometric properties and relations with academic performance among adolescents.

The present study explored, in adolescents, the dimensionality (factorial structure), reliability (internal consistency and test-retest stability) and predictive validity (in relation with academic grades) of the Hemispheric Preference Test (HPT), a widely used self-report index of thinking styles among adults. A sample of 990 Spanish adolescents aged 10-14 completed HPT and reported their academic grades. Results indicated a two-factor structure for HPT that can be interpreted in terms of left- and right-Hemisphere Preference (HP). The two-factor structure was clearer in boys compared to girls. The internal consistency and test-retest at 6 and 12 months were satisfactory. Left-HP scores decreased with age whereas girls obtained a higher mean score on right-HP sub-scale. Finally, Left-HP accounted for a significant variance percentage on academic grades after controlling for age and sex. Results suggested that Spanish version of the HPT was effective and reliable among adolescents.

Women would like their partners to be more synchronized with them in their sleep-wake rhythm.

Men sleep shorter and go to bed and get up later than women, thus they are later chronotypes. This difference between the sexes is most pronounced between puberty and menopause indicating the possibility that morningness is subject to sexual dimorphism related to reproductive aspects. The objective of the study was to compare the sleep-wake behavior of women with their actual partners and with their preferred partners. As a hypothesis, we expect some assortment in mating concerning chronotype (with the actual partner), but we also expect a higher synchronization with a preferred ideal partner. 167 women were analyzed in this study (mean age: 23.0 ± 2.57 (SD) years). Mated women were earlier chronotypes than their partners (t = -2.051, p = .042, d = .34) but the difference was small (11:02 min ± 1:04 min). The results of the present study showed women preferring a partner synchronized to their own sleep-wake-rhythm more than their actual partners were. The above result was true either for single facets of the sleep-wake rhythm (e.g. bed time, sleep onset) or for midpoint of sleep on free days - an indicator of actual chronotype: women's and their partners' correlation of midpoint of sleep was lower (r = .513) than women's and their ideal partners' correlation (r = .855). Amongst various sleep-wake measures, women particularly preferred a partner going to bed at the same time. Assortative mating according to sleep-wake rhythm exists, but women for long-term pair-bonds would like their partners far more synchronized.

Morningness and life satisfaction: further evidence from Spain.

Life satisfaction is a crucial component of well being, thus research of its determinants are of great importance and are conducted worldwide. Recently, morningness has been shown to be related to greater life satisfaction in Polish and German samples; and in the present study, this relationship was tested in a Spanish adult sample. The results provide further evidence for the relationship of morningness with higher life satisfaction, which it seems independent of culture and geographic location.

Circadian preference and thinking styles: implications for school achievement.

Research has shown that thinking styles could have an influence on academic achievement. Previous studies have described that evening types are usually right-thinkers who tend to be creative and intuitive, whereas morning types tend to be left-thinkers who prefer verbal and analytic strategies in processing information. However, these studies have been realized among undergraduates, who have more freedom to choose their time schedules according to their circadian preference than adolescents or adult workers. On other hand, the relationship between thinking styles and circadian preference has not been analyzed considering school achievement. The present study aims (1) to investigate the relationship between circadian preference, that is, behavioral differences in circadian rhythmic expression, and thinking styles, referring to the preference toward information processing typical of the right versus the left cerebral hemisphere; and (2) to test the implications for self-reported school achievement. A sample of 1134 preadolescents and adolescents (581 girls; mean ± SD age: 12.1 ± 1.47, range: 10-14 yrs) completed the Morningness-Eveningness Scale for Children (MESC) as measure of circadian preference (morning, neither, or evening types), the Hemispheric Preference Test (HPT), conceived as a tool to measure thinking styles (right-, balanced-, and left-thinkers), and self-reported school achievement. Results indicated a greater percentage of left-thinkers among morning types and a greater percentage of right-thinkers among evening types. No differences were found among balanced-thinkers and neither types. Morning types and left-thinkers reported the highest subjective level of achievement, followed by evening types and left-thinkers, and morning types and right-thinkers. Evening types and right-thinkers reported the lowest subjective level of achievement. Finally, multivariate regression analysis indicated that age, left hemisphere and morning preferences accounted for 14.2% of total variance on self-reported achievement.

Morningness-eveningness and sleep habits among adolescents: age and gender differences.

Previous research has indicated the need to use large samples in different cultural contexts in order to clarify age and gender differences on morningness-eveningness and sleep habits. The goal of our research was to study the relationship between morningness-eveningness and sleep habits in a large sample of 2,649 adolescents between 12 and 16 years. The Morningness- Eveningness Scale for Children and an adaptation of the School Sleep Habits Survey measures were used. Results indicated a greater tendency toward eveningness with age and higher eveningness in 13- and 14-year-old girls. Older adolescents claimed later rising time on weekends, later bedtime and shorter sleep length, and greater social jetlag, weekend rise time delay, and weekend bedtime delay. Girls reported earlier rising time on weekdays, later rising time on weekends, longer sleep length on weekends, and greater social jetlag and weekend rising time delay. Lastly, evening oriented adolescents claimed later rising time and bedtime, shorter sleep length on weekdays but longer sleep duration on weekends, and greater social jetlag, weekend rising time delay, and weekend bedtime delay.

Morningness-eveningness and health-related quality of life among adolescents.

Accumulating evidence suggests that evening-type adolescents are exposed to a number of determinants that might have a negative impact on their health condition. Given that few studies have investigated the association between chronotype and quality of life measures in large samples of adolescents, the aim of this study was to assess the relationship between morningness-eveningness and health-related quality of life among 1600 adolescents (aged 12-16 years). Adolescents completed the Veçu et Santé Perçue de L'adolescent (VSP-A) and the Morningness-Eveningness Scale for Children (MESC). Girls and older adolescents reported worse health indicators and were more evening oriented. Evening-type adolescents obtained lower scores on vitality, physical and psychological well-being, body image, relations with parents, relations with teachers, school work and global health scale.