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.

Qualifying a Novel Clinical Trial Endpoint (iBOX) Predictive of Long-Term Kidney Transplant Outcomes.

New immunosuppressive therapies that improve long-term graft survival are needed in kidney transplant. Critical Path Institute's Transplant Therapeutics Consortium received a qualification opinion for the iBOX Scoring System as a novel secondary efficacy endpoint for kidney transplant clinical trials through European Medicines Agency's qualification of novel methodologies for drug development. This is the first qualified endpoint for any transplant indication and is now available for use in kidney transplant clinical trials. Although the current efficacy failure endpoint has typically shown the noninferiority of therapeutic regimens, the iBOX Scoring System can be used to demonstrate the superiority of a new immunosuppressive therapy compared to the standard of care from 6 months to 24 months posttransplant in pivotal or exploratory drug therapeutic studies.

Qualifying a novel clinical trial endpoint (iBOX) predictive of long-term kidney transplant outcomes.

New immunosuppressive therapies that improve long-term graft survival are needed in kidney transplant. Critical Path Institute's Transplant Therapeutics Consortium received a qualification opinion for the iBOX Scoring System as a novel secondary efficacy endpoint for kidney transplant clinical trials through European Medicines Agency's qualification of novel methodologies for drug development. This is the first qualified endpoint for any transplant indication and is now available for use in kidney transplant clinical trials. Although the current efficacy failure endpoint has typically shown the noninferiority of therapeutic regimens, the iBOX Scoring System can be used to demonstrate the superiority of a new immunosuppressive therapy compared to the standard of care from 6 months to 24 months posttransplant in pivotal or exploratory drug therapeutic studies.

Longitudinal estimated glomerular filtration rate (eGFR) modeling in long-term renal function to inform clinical trial design in kidney transplantation.

Kidney transplantation is the preferred treatment for individuals with end-stage kidney disease. From a modeling perspective, our understanding of kidney function trajectories after transplantation remains limited. Current modeling of kidney function post-transplantation is focused on linear slopes or percent decline and often excludes the highly variable early timepoints post-transplantation, where kidney function recovers and then stabilizes. Using estimated glomerular filtration rate (eGFR), a well-known biomarker of kidney function, from an aggregated dataset of 4904 kidney transplant patients including both observational studies and clinical trials, we developed a longitudinal model of kidney function trajectories from time of transplant to 6 years post-transplant. Our model is a nonlinear, mixed-effects model built in NONMEM that captured both the recovery phase after kidney transplantation, where the graft recovers function, and the long-term phase of stabilization and slow decline. Model fit was assessed using diagnostic plots and individual fits. Model performance, assessed via visual predictive checks, suggests accurate model predictions of eGFR at the median and lower 95% quantiles of eGFR, ranges which are of critical clinical importance for assessing loss of kidney function. Various clinically relevant covariates were also explored and found to improve the model. For example, transplant recipients of deceased donors recover function more slowly after transplantation and calcineurin inhibitor use promotes faster long-term decay. Our work provides a generalizable, nonlinear model of kidney allograft function that will be useful for estimating eGFR up to 6 years post-transplant in various clinically relevant populations.

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.

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.

Discovery of PF-06873600, a CDK2/4/6 Inhibitor for the Treatment of Cancer.

Control of the cell cycle through selective pharmacological inhibition of CDK4/6 has proven beneficial in the treatment of breast cancer. Extending this level of control to additional cell cycle CDK isoforms represents an opportunity to expand to additional tumor types and potentially provide benefits to patients that develop tumors resistant to selective CDK4/6 inhibitors. However, broad-spectrum CDK inhibitors have a long history of failure due to safety concerns. In this approach, we describe the use of structure-based drug design and Free-Wilson analysis to optimize a series of CDK2/4/6 inhibitors. Further, we detail the use of molecular dynamics simulations to provide insights into the basis for selectivity against CDK9. Based on overall potency, selectivity, and ADME profile, PF-06873600 (22) was identified as a candidate for the treatment of cancer and advanced to phase 1 clinical trials.

Effective Data Sharing as a Conduit for Advancing Medical Product Development.

INTRODUCTION: Patient-level data sharing has the potential to significantly impact the lives of patients by optimizing and improving the medical product development process. In the product development setting, successful data sharing is defined as data sharing that is actionable and facilitates decision making during the development and review of medical products. This often occurs through the creation of new product development tools or methodologies, such as novel clinical trial design and enrichment strategies, predictive pre-clinical and clinical models, clinical trial simulation tools, biomarkers, and clinical outcomes assessments, and more. METHODS: To be successful, extensive partnerships must be established between all relevant stakeholders, including industry, academia, research institutes and societies, patient-advocacy groups, and governmental agencies, and a neutral third-party convening organization that can provide a pre-competitive space for data sharing to occur. CONCLUSIONS: Data sharing focused on identified regulatory deliverables that improve the medical product development process encounters significant challenges that are not seen with data sharing aimed at advancing clinical decision making and requires the commitment of all stakeholders. Regulatory data sharing challenges and solutions, as well as multiple examples of previous successful data sharing initiatives are presented and discussed in the context of medical product development.

Use of biomarkers to improve immunosuppressive drug development and outcomes in renal organ transplantation: A meeting report.

On September 27-28, 2018 the Food and Drug Administration (FDA) and the Critical Path Institute's Transplant Therapeutics Consortium convened a public workshop titled "Evidence-Based Treatment Decisions in Transplantation: The Right Dose & Regimen for the Right Patient/Individualized Treatment." The workshop facilitated cooperative engagement of transplant community stakeholders, including pharmaceutical industry, academic researchers, clinicians, patients, and regulators to discuss methods to advance the development of novel immunosuppressive drugs for use in solid organ transplantation. Day 1 focused on the utility of biomarkers in drug development, with considerations for seeking regulatory endorsement for use in clinical trials. Biomarkers add value to drug development by improving patient selection criteria, safety monitoring, endpoint selection, and more. Regulatory endorsement through the FDA Biomarker Qualification Program encourages the use of biomarkers in drug development by instilling confidence and consistency in biomarker interpretation across trials. Public-private partnerships or consortia allow stakeholders to share expertise, resources, and data in pursuit of biomarker qualification. Biomarkers relevant to pretransplant risk assessment, early posttransplant care, and assessment of immune response, immunosuppressive drug efficacy, and graft function as discussed on day 1 of the workshop are described.

Recommended Treatment for Antibody-mediated Rejection After Kidney Transplantation: The 2019 Expert Consensus From the Transplantion Society Working Group.

With the development of modern solid-phase assays to detect anti-HLA antibodies and a more precise histological classification, the diagnosis of antibody-mediated rejection (AMR) has become more common and is a major cause of kidney graft loss. Currently, there are no approved therapies and treatment guidelines are based on low-level evidence. The number of prospective randomized trials for the treatment of AMR is small, and the lack of an accepted common standard for care has been an impediment to the development of new therapies. To help alleviate this, The Transplantation Society convened a meeting of international experts to develop a consensus as to what is appropriate treatment for active and chronic active AMR. The aim was to reach a consensus for standard of care treatment against which new therapies could be evaluated. At the meeting, the underlying biology of AMR, the criteria for diagnosis, the clinical phenotypes, and outcomes were discussed. The evidence for different treatments was reviewed, and a consensus for what is acceptable standard of care for the treatment of active and chronic active AMR was presented. While it was agreed that the aims of treatment are to preserve renal function, reduce histological injury, and reduce the titer of donor-specific antibody, there was no conclusive evidence to support any specific therapy. As a result, the treatment recommendations are largely based on expert opinion. It is acknowledged that properly conducted and powered clinical trials of biologically plausible agents are urgently needed to improve patient outcomes.

The importance of drug safety and tolerability in the development of new immunosuppressive therapy for transplant recipients: The Transplant Therapeutics Consortium's position statement.

The Transplant Therapeutics Consortium (TTC) is a public-private partnership between the US Food and Drug Administration and the transplantation community including the transplantation societies and members of the biopharmaceutical industry. The TTC was formed to accelerate the process of developing new medical products for transplant patients. The initial goals of this collaboration are the following: (a) To define which aspects of the kidney transplant drug-development process have clear needs for improvement from an industry and regulatory perspective; (b) to define which of the unmet needs in the process could be positively impacted through the development of specific drug-development tools based on available data; and (c) to determine the most appropriate pathway to achieve regulatory acceptance of the proposed process-accelerating tools. The TTC has identified 2 major areas of emphasis: new biomarkers or endpoints for determining the efficacy of new therapies and new tools to assess the safety or tolerability of new therapies. This article presents the rationale and planned approach to develop new tools to assess safety and tolerability of therapies for transplant patients. We also discuss how similar efforts might support the continued development of patient-reported outcome measures in the future.

Tomato receptor FLAGELLIN-SENSING 3 binds flgII-28 and activates the plant immune system.

Plants and animals detect the presence of potential pathogens through the perception of conserved microbial patterns by cell surface receptors. Certain solanaceous plants, including tomato, potato and pepper, detect flgII-28, a region of bacterial flagellin that is distinct from that perceived by the well-characterized FLAGELLIN-SENSING 2 receptor. Here we identify and characterize the receptor responsible for this recognition in tomato, called FLAGELLIN-SENSING 3. This receptor binds flgII-28 and enhances immune responses leading to a reduction in bacterial colonization of leaf tissues. Further characterization of FLS3 and its signalling pathway could provide new insights into the plant immune system and transfer of the receptor to other crop plants offers the potential of enhancing resistance to bacterial pathogens that have evolved to evade FLS2-mediated immunity.

Chemoselective Preparation of Clickable Aryl Sulfonyl Fluoride Monomers: A Toolbox of Highly Functionalized Intermediates for Chemical Biology Probe Synthesis.

Sulfonyl fluoride (SF)-based activity probes have become important tools in chemical biology. Herein, exploiting the relative chemical stability of SF to carry out a number of unprecedented SF-sparing functional group manipulations, we report the chemoselective synthesis of a toolbox of highly functionalized aryl SF monomers that we used to quickly prepare SF chemical biology probes. In addition to SF, the monomers bear an embedded click handle (a terminal alkyne that can perform copper(I)-mediated azide-alkyne cycloaddition). The monomers can be used either as fragments to prepare clickable SF analogues of drugs (biologically active compounds) bearing an aryl ring or, alternatively, attached to drugs as minimalist clickable aryl SF substituents.

Discovery of a Selective Covalent Inhibitor of Lysophospholipase-like 1 (LYPLAL1) as a Tool to Evaluate the Role of this Serine Hydrolase in Metabolism.

Lysophospholipase-like 1 (LYPLAL1) is an uncharacterized metabolic serine hydrolase. Human genome-wide association studies link variants of the gene encoding this enzyme to fat distribution, waist-to-hip ratio, and nonalcoholic fatty liver disease. We describe the discovery of potent and selective covalent small-molecule inhibitors of LYPLAL1 and their use to investigate its role in hepatic metabolism. In hepatocytes, selective inhibition of LYPLAL1 increased glucose production supporting the inference that LYPLAL1 is a significant actor in hepatic metabolism. The results provide an example of how a selective chemical tool can contribute to evaluating a hypothetical target for therapeutic intervention, even in the absence of complete biochemical characterization.

Identification of multiple salicylic acid-binding proteins using two high throughput screens.

Salicylic acid (SA) is an important hormone involved in many diverse plant processes, including floral induction, stomatal closure, seed germination, adventitious root initiation, and thermogenesis. It also plays critical functions during responses to abiotic and biotic stresses. The role(s) of SA in signaling disease resistance is by far the best studied process, although it is still only partially understood. To obtain insights into how SA carries out its varied functions, particularly in activating disease resistance, two new high throughput screens were developed to identify novel SA-binding proteins (SABPs). The first utilized crosslinking of the photo-reactive SA analog 4-AzidoSA (4AzSA) to proteins in an Arabidopsis leaf extract, followed by immuno-selection with anti-SA antibodies and then mass spectroscopy-based identification. The second utilized photo-affinity crosslinking of 4AzSA to proteins on a protein microarray (PMA) followed by detection with anti-SA antibodies. To determine whether the candidate SABPs (cSABPs) obtained from these screens were true SABPs, recombinantly-produced proteins were generated and tested for SA-inhibitable crosslinking to 4AzSA, which was monitored by immuno-blot analysis, SA-inhibitable binding of the SA derivative 3-aminoethylSA (3AESA), which was detected by a surface plasmon resonance (SPR) assay, or SA-inhibitable binding of [(3)H]SA, which was detected by size exclusion chromatography. Based on our criteria that true SABPs must exhibit SA-binding activity in at least two of these assays, nine new SABPs are identified here; nine others were previously reported. Approximately 80 cSABPs await further assessment. In addition, the conflicting reports on whether NPR1 is an SABP were addressed by showing that it bound SA in all three of the above assays.

Interaction of structure-specific and promiscuous G-protein-coupled receptors mediates small-molecule signaling in Caenorhabditis elegans.

A chemically diverse family of small-molecule signals, the ascarosides, control developmental diapause (dauer), olfactory learning, and social behaviors of the nematode model organism, Caenorhabditis elegans. The ascarosides act upstream of conserved signaling pathways, including the insulin, TGF-ß, serotonin, and guanylyl cyclase pathways; however, the sensory processes underlying ascaroside function are poorly understood. Because ascarosides often are multifunctional and show strongly synergistic effects, characterization of their receptors will be essential for understanding ascaroside biology and may provide insight into molecular mechanisms that produce synergistic outcomes in small-molecule sensing. Based on DAF-8 immunoprecipitation, we here identify two G-protein-coupled receptors, DAF-37 and DAF-38, which cooperatively mediate ascaroside perception. daf-37 mutants are defective in all responses to ascr#2, one of the most potent dauer-inducing ascarosides, although this mutant responds normally to other ascarosides. In contrast, daf-38 mutants are partially defective in responses to several different ascarosides. Through cell-specific overexpression, we show that DAF-37 regulates dauer when expressed in ASI neurons and adult behavior when expressed in ASK neurons. Using a photoaffinity-labeled ascr#2 probe and amplified luminescence assays (AlphaScreen), we demonstrate that ascr#2 binds to DAF-37. Photobleaching fluorescent energy transfer assays revealed that DAF-37 and DAF-38 form heterodimers, and we show that heterodimerization strongly increases cAMP inhibition in response to ascr#2. These results suggest that that the ascarosides' intricate signaling properties result in part from the interaction of highly structure-specific G-protein-coupled receptors such as DAF-37 with more promiscuous G-protein-coupled receptors such as DAF-38.

Synthesis of caeliferins, elicitors of plant immune responses: accessing lipophilic natural products via cross metathesis.

A cross metathesis (CM)-based synthesis of the caeliferins, a family of sulfooxy fatty acids that elicit plant immune responses, is reported. Unexpectedly, detailed NMR spectroscopic and mass spectrometric analyses of CM reaction mixtures revealed extensive isomerization and homologation of starting materials and products. It is shown that the degree of isomerization and homologation in CM strongly correlates with substrate chain length and lipophilicity. Side-product suppression requires appropriate catalyst selection and use of 1,4-benzoquinone as a hydride scavenger.