T1dCteGui: A User-Friendly Clinical Trial Enrichment Tool to Optimize T1D Prevention Studies by Leveraging AI/ML Based Synthetic Patient Population.

Whereas islet autoantibodies (AAs) are well-established risk factors for developing type 1 diabetes (T1D), there is a lack of biomarkers endorsed by regulators to enrich clinical trial populations for those at risk of developing T1D. As such, the development of therapies that delay or prevent the onset of T1D remains challenging. To address this drug development need, the Critical Path Institute's T1D Consortium (T1DC) acquired patient-level data from multiple observational studies and used a model-based approach to evaluate the utility of islet AAs as enrichment biomarkers in clinical trials. An accelerated failure time model was developed, discussed in our previous publication, which provided the underlying evidence required to receive a qualification opinion for islet AAs as enrichment biomarkers from the European Medicines Agency (EMA) in March 2022. To further democratize the use of the model for scientists and clinicians, we developed a Clinical Trial Enrichment Graphical User Interface. The interactive tool allows users to specify trial participant characteristics, including the percentage of participants with a specific AA combination. Users can specify ranges for participant baseline age, sex, blood glucose measurement from the 120-minute timepoints of an oral glucose tolerance test, and HbA1c. The tool then applies the model to predict the mean probability of a T1D diagnosis for that trial population and renders the results to the user. To ensure adequate data privacy and to make the tool open-source, a deep learning-based generative model was used to generate a cohort of synthetic subjects that underpins the tool.

Consortium-based approach to receiving an EMA qualification opinion on the use of islet autoantibodies as enrichment biomarkers in type 1 diabetes clinical studies.

The development of medical products that can delay or prevent progression to stage 3 type 1 diabetes faces many challenges. Of note, optimising patient selection for type 1 diabetes prevention clinical trials is hindered by significant patient heterogeneity and a lack of characterisation of the time-varying probability of progression to stage 3 type 1 diabetes in individuals positive for two or more islet autoantibodies. To meet these needs, the Critical Path Institute's Type 1 Diabetes Consortium was launched in 2017 as a pre-competitive public-private partnership between stakeholders from the pharmaceutical industry, patient advocacy groups, philanthropic organisations, clinical researchers, the National Institutes of Health and the Food and Drug Administration. The Type 1 Diabetes Consortium acquired and aggregated data from three longitudinal observational studies, Environmental Determinants of Diabetes in the Young (TEDDY), Diabetes Autoimmunity Study in the Young (DAISY) and TrialNet Pathway to Prevention (TN01), and used analysis subsets of these data to support the model-based qualification of islet autoantibodies as enrichment biomarkers for patient selection in type 1 diabetes prevention trials, including registration studies. The Type 1 Diabetes Consortium has now received a qualification opinion from the European Medicines Agency for the use of these biomarkers, a major success for the field of type 1 diabetes. This endorsement will improve product developers' ability to design clinical trials of agents intended to prevent or delay type 1 diabetes that are reduced in size and/or length, while being adequately powered.

Leveraging Real-World Data for EMA Qualification of a Model-Based Biomarker Tool to Optimize Type-1 Diabetes Prevention Studies.

The development of therapies to prevent or delay the onset of type 1 diabetes (T1D) remains challenging, and there is a lack of qualified biomarkers to identify individuals at risk of developing T1D or to quantify the time-varying risk of conversion to a diagnosis of T1D. To address this drug development need, the T1D Consortium (i) acquired, remapped, integrated, and curated existing patient-level data from relevant observational studies, and (ii) used a model-based approach to evaluate the utility of islet autoantibodies (AAs) against insulin/proinsulin autoantibody, GAD65, IA-2, and ZnT8 as biomarkers to enrich subjects for T1D prevention. The aggregated dataset was used to construct an accelerated failure time model for predicting T1D diagnosis. The model quantifies presence of islet AA permutations as statistically significant predictors of the time-varying probability of conversion to a diagnosis of T1D. Additional sources of variability that greatly improved the accuracy of quantifying the time-varying probability of conversion to a T1D diagnosis included baseline age, sex, blood glucose measurements from the 120-minute timepoints of oral glucose tolerance tests, and hemoglobin A1c. The developed models represented the underlying evidence to qualify islet AAs as enrichment biomarkers through the qualification of novel methodologies for drug development pathway at the European Medicines Agency (EMA). Additionally, the models are intended as the foundation of a fully functioning end-user tool that will allow sponsors to optimize enrichment criteria for clinical trials in T1D prevention studies.

Comparative physical, mechanical and crystallographic properties of a series of gemfibrozil salts.

OBJECTIVES: Understanding the impact of the counterion on the properties of an acidic or basic drug may influence the choice of salt form, especially for less potent drugs with a high drug load per unit dose. The aim of this work was to determine the influence of the hydrogen bonding potential of the counterion on the crystal structure of salts of the poorly soluble, poorly compressible, acidic drug gemfibrozil and to correlate these with mechanical properties. METHODS: Compacts of the parent drug and the salts were used to determine Young's modulus of elasticity using beam bending tests. Crystal structures were determined previously from X-ray powder diffraction data. KEY FINDINGS: The free acid, tert-butylamine, 2-amino-2-methylpropan-1-ol and 2-amino-2-methylpropan-1,3-diol salts had a common crystal packing motif of infinite hydrogen-bonded chains with cross-linking between pairs of adjacent chains. The tromethamine (trsi) salt, with different mechanical properties, had a two-dimensional sheet-like network of hydrogen bonds, with slip planes, forming a stiffer compact. CONCLUSIONS: The type of counter ion is important in determining mechanical properties and could be selected to afford slip and plastic deformation.