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Phenotypic high-throughput screening identifies aryl hydrocarbon receptor agonism as common inhibitor of toxin-induced retinal pigment epithelium cell death.
No full textThe retinal pigment epithelium (RPE) is essential to maintain retinal function, and RPE cell death represents a key pathogenic stage in the progression of several blinding ocular diseases, including age-related macular degeneration (AMD). To identify pathways and compounds able to prevent RPE cell death, we developed a phenotypic screening pipeline utilizing a compound library and high-throughput screening compatible assays on the human RPE cell line, ARPE-19, in response to different disease relevant cytotoxic stimuli. We show that the metabolic by-product of the visual cycle all-trans-retinal (atRAL) induces RPE apoptosis, while the lipid peroxidation by-product 4-hydroxynonenal (4-HNE) promotes necrotic cell death. Using these distinct stimuli for screening, we identified agonists of the aryl hydrocarbon receptor (AhR) as a consensus target able to prevent both atRAL mediated apoptosis and 4-HNE-induced necrotic cell death. This works serves as a framework for future studies dedicated to screening for inhibitors of cell death, as well as support for the discussion of AhR agonism in RPE pathology
A risk analysis of alpelisib-induced hyperglycemia in patients with advanced solid tumors and breast cancer
No full textImportance: Hyperglycemia is an on-target effect of PI3Kα inhibitors. Early identification and intervention of treatment-induced hyperglycemia is important for improving management of patients receiving a PI3Kα inhibitor like alpelisib.
Objective: To characterize early grade 3/4 alpelisib-related hyperglycemia, along with associated incidence, management, and outcomes using a machine learning model
Design and Setting: Data for the risk model was pooled from patients receiving alpelisib +/- fulvestrant in the open-label phase 1 X2101 trial and the randomized, double-blind phase 3 SOLAR-1 trial.
Participants: The pooled population (n=505) included patients with advanced solid tumors (X2101, n=221) or HR+/HER2− ABC (SOLAR-1, n=284). Hyperglycemia incidence and management were analyzed for SOLAR-1. Additional external validation was performed using the BYLieve trial (n=340).
Intervention(s) (for clinical trials) or Exposure(s) (for observational studies): Alpelisib +/- fulvestrant/letrozole.
Main Outcome(s) and Measure(s): A machine learning model capable of predicting risk of early grade 3/4 alpelisib-induced hyperglycemia.
Results: A random forest model identified 5 baseline characteristics most associated with risk of developing grade 3/4 hyperglycemia (fasting plasma glucose, body mass index, HbA1c, monocytes, age). This model was used to derive a score to classify patients as high- or low-risk for developing grade 3/4 hyperglycemia. Applying the model to patients treated with alpelisib + fulvestrant in SOLAR-1 showed shorter time to grade 3/4 hyperglycemia, higher incidence of hyperglycemia, increased use of antihyperglycemic medications, and more discontinuations due to hyperglycemia (14.2% vs 2.2% of discontinuations) in the high- vs low-risk group. Among patients in SOLAR-1 with PIK3CA mutations, median progression-free survival was similar between the high- and low-risk groups (11.0 vs 10.9 mo). For external validation, the model was applied to the BYLieve trial, where successful classification into high and low risk groups with shorter time to grade 3/4 hyperglycemia in the high-risk group was observed.
Conclusions and Relevance: A risk model using 5 clinically relevant baseline characteristics was able to identify patients at higher or lower probability for developing alpelisib-induced hyperglycemia. Early identification of patients that may be at higher risk for hyperglycemia may improve management (including monitoring and early intervention) and potentially lead to improved outcomes
Modeling Proteomes Using Unsupervised Machine Learning Approaches on SomaScan Aptamer-based Proteome Hybridization Technology
No full textAbstract: Robust and reliable proteome measurements provide mechanistic insights important to biomedical research. We have developed a clinical proteome profiling platform named So-maScan that has expanded to measure 7,523 proteoforms for 6,594 human proteins by UniprotID. SomaScan is based on modified DNA-based affinity reagents called SOMAmers (Slow Off-rate Modified Aptamers). Providing independent corroborating evidence that the SomaScan assay measures the intended proteins enhances the utility and interpretability of the platform. We have therefore evaluated the capabilities of the platform by profiling a panel of well characterized CCLE cancer models. Unsupervised learning methods demonstrate the SomaScan assay’s ability to distinguish cell lines and identify both tissue-specific and oncogenic pathways. Publicly avail-able CCLE transcriptome profiling sets an expectation of endogenous protein to which each SOMAmer is annotated. We found orthogonal transcript data support protein annotation for ap-proximately one third of the SOMAmer reagents, consistent with transcript to protein correlation observed in many other studies. The SomaScan platform is a technically reproducible proteome measuring device available for biomedical and clinical applications providing investigators with reliable data to inform underlying biochemical mechanisms and with the ability to utilize individual SOMAmer reagents for follow-up studies and clinical biomarker assay development
Validating a composite endpoint for acceptability evaluation of oral drug formulations in the pediatric population: a randomized, open-label, single dose, cross-over study
No full textObjective: This study aimed to validate the newly developed composite acceptability endpoint to investigate acceptability of oral pediatric drug formulations that integrates swallowability and palatability assessments.
Methods: In this open-label study acceptability of oral formulations was tested in 3 age groups (1 - <6 16 months, 6 - <12 years, and 12 - <18 years) with a 2-way cross-over design in children aged 1 - <6 months (syrup and mini-tablets), and with an incomplete block design of 4 sequences with 3 out of 4 formulations (syrup, mini-tablets, oblong tablet, and round tablet) each in children aged 6 - <18 years. The primary endpoint was acceptability derived from the composite acceptability endpoint. Secondary endpoints were palatability and acceptability derived from swallowability.
Results: A total of 320 children were stratified into 3 age groups (80 children aged 1 - <6 months, 120 children aged 6 - <12 years, and 120 children aged 12 - <18 years). All participants completed the study. Age-specific differences were observed in acceptability derived from the composite acceptability endpoint. Mini-tablets had the highest acceptability in participants aged 1 - <6 months and 6 - <12 years while the oblong tablet was leading in adolescent participants (12 - <18 years).
Conclusion: This study demonstrated that the composite acceptability endpoint method integrating both swallowability and palatability assessments is a sensitive method to assess acceptability of drug formulations in children of different age
Identification and characterization of human GDF15 knockouts.
No full textGrowth differentiation factor 15 (GDF15) is a secreted protein that regulates food intake, body weight and stress responses in pre-clinical models1. The physiological function of GDF15 in humans remains unclear. Pharmacologically, GDF15 agonism in humans causes nausea without accompanying weight loss2, and GDF15 antagonism is being tested in clinical trials to treat cachexia and anorexia. Human genetics point to a role for GDF15 in hyperemesis gravidarum, but the safety or impact of complete GDF15 loss, particularly during pregnancy, is unknown3-7. Here we show the absence of an overt phenotype in human GDF15 loss-of-function carriers, including stop gains, frameshifts and the fully inactivating missense variant C211G3. These individuals were identified from 75,018 whole-exome/genome-sequenced participants in the Pakistan Genomic Resource8,9 and recall-by-genotype studies with family-based recruitment of variant carrier probands. We describe 8 homozygous ('knockouts') and 227 heterozygous carriers of loss-of-function alleles, including C211G. GDF15 knockouts range in age from 31 to 75 years, are fertile, have multiple children and show no consistent overt phenotypes, including metabolic dysfunction. Our data support the hypothesis that GDF15 is not required for fertility, healthy pregnancy, foetal development or survival into adulthood. These observations support the safety of therapeutics that block GDF15
Stakeholder perspective on current issues in Data Monitoring Committees
No full textA Data Monitoring Committee (DMC) is a group of experts that reviews accumulating data from one or more ongoing clinical trials on a regular basis. The DMC advises the sponsor regarding the continuing safety of trial subjects and those yet to be recruited to the trial, as well as the continuing validity and scientific merit of the trial. While DMCs are widely used considerable variability exists in how DMCs are conducted. This paper offers practical recommendations, derived from the 2023 PSI and CEN Conferences' interactive workshops, to enhance DMCs’ operations and performance. We will focus on a number of topics that are part of the DMC process and where there is unclarity and inconsistency. This paper focuses on four key areas that can significantly impact DMC performance and impact, and where there is inconsistency in current practices: 1) Open Sessions: we discuss the benefits of incorporating open sessions in DMC meetings to enhance transparency, inclusivity, and the consideration of diverse perspectives, as well as pitfalls of open sessions. 2) Communication with the DMC: We reflect on the importance of effective and proper communication channels between the DMC and relevant stakeholders, including sponsors, investigators, and regulatory authorities, to foster collaboration and exchange of critical information, whilst retaining study integrity throughout. 3). Access to efficacy data: we highlight the need for timely and appropriate access to efficacy data by DMCs and discuss how to implement this in practice and how to address potential concerns regarding multiplicity. 4) Interactive data displays: We outline the utilization of innovative and interactive data displays to facilitate more intuitive interpretation and understanding of study results by the DMC. By addressing these specific topics, we aim to provide comprehensive practical recommendations that bridge the gap between current practices and optimal DMC functionality
People of TM: Videos of Martin Brom
No full textThese videos will be used for external social media engagement campaign on platforms like LinkedIn and YouTube etc.featuring stories of people in TM. No IP related content
Scientific principles and experimental approaches for the assessment of risk factors relevant to potential carcinogenicity of gene therapies: consensus statements
No full textThere is an urgent need to improve the non-clinical evaluation of potential carcinogenicity of gene therapies (GTs), including the use of more human-relevant models, that can inform and help reduce the risk of clinical adverse events. Regulatory agencies and the pharmaceutical industry are actively seeking improvements and alternatives to current models and approaches. Progress is, however, hampered by the lack of promising experimental platforms to address potential risks, and an apparent lack of consensus among scientists regarding how the potential carcinogenicity of GTs should be identified and measured in a regulatory context. Questions remain as to the most appropriate platforms and toxicological principles to support robust, scientific, and reliable risk assessment of vector safety.
Motivated by these concerns, a meeting of international scientific experts was organised by NC3Rs/UKEMS (London, March 2023) to discuss principles and open questions on the assessment of vector-mediated carcinogenicity. This paper describes the scientific background and consensus reached amongst delegates on the definition of vector genotoxicity in non-clinical testing, sources of uncertainty, suitable toxicological endpoints for genotoxic assessment of GTs, and future research needs. It addresses the challenges in predicting carcinogenesis, the insufficient range of validated test systems, and other issues that impact the evaluation of vector-mediated carcinogenicity risks, such as understanding the “background noise” (both technical and biological) of proposed endpoints and avoidance of tests that are prone to misleading and/or uninformative results.
The recommendations in this consensus paper should inform the further development of regulatory guidelines for the non-clinical toxicological assessment of GT products
The role of complement factor I rare genetic variants in age related macular degeneration in Finland.
No full textAge-related macular degeneration (AMD) is the leading cause of irreversible blindness in the developed world. The alternative pathway (AP) of complement has been linked to the pathogenesis of AMD. In particular, rare variants (RVs) in the complement factor I (CFI) gene encoding the Factor I (FI) protein confer increased AMD risk. The prevalence of CFI RVs are well characterised in European AMD, however little is known about other populations. The Finnish population underwent genetic restriction events which have skewed allele frequencies in unexpected ways. A series of novel or enriched CFI RVs were identified in individuals with dry AMD from the Finnish Biobank Cooperative (FINBB), but the relationship between these genotypes and contribution to disease was unclear. Understanding how RVs impact the ability of FI to regulate the complement system is important to inform mechanistic understanding for how different genotypes contribute to disease development. To explore this a series of in vitro assays were used to functionally characterise the protein products of 3 CFI RVs enriched in FINBB dry AMD, where no prior data were available. The G547R variant resulted in almost complete loss of both classical pathway and AP regulatory potential. The c.982 g>a variant encoding G328R FI perturbed an exon splice enhancer site which resulted in exon skipping and a premature stop codon in vitro and low levels of FI in vivo. Despite detailed analysis no defect in levels or function was demonstrated in T107A. Functional characterization of all Finnish CFI RVs in the cohort allowed us to demonstrate that in Finnish dry AMD, collectively the type 1 CFI RVs (associated with FI haploinsufficiency) were significantly enriched with odds ratio (ORs) of 72.6 (95% confidence interval; CI 16.92 to 382.1). Meanwhile, type 2 CFI RVs (associated with FI dysfunction) collectively conferred a significant OR of 4.97 (95% CI 1.522 to 15.74), and non-impaired or normal CFI RV collectively conferred an of OR 3.19 (95% CI 2.410 to 4.191) although this was driven primarily by G261D. Overall, this study for the first time determined the ORs and functional effect for all CFI RVs within a Geographic Atrophy (GA) cohort, enabling calculations of combined risk scores that underline the risk conferred by type 1 and 2 CFI RVs in GA/AMD
Building Confidence in Physiologically Based Pharmacokinetic Modeling of CYP3A Induction Mediated by Rifampin: An Industry Perspective
No full textPhysiologically Based Pharmacokinetic (PBPK) modeling offers a viable approach to predict drug-drug interactions (DDIs) with the potential to streamline or reduce clinical trial burden if predictions can be made with sufficient confidence. In this study, the ability to predict the effect of rifampin, a well-characterized CYP3A4 inducer, on 20 CYP3A probes with publicly available PBPK models, was assessed. Substrates with a range of fm,CYP3A (0.086 to 1.0), Fg (0.11 to 1) and Fh (0.09 to 0.96) were included. Predictions were most likely to be accurate for compounds that are not P-gp substrates or that are P-gp substrates but that have high permeability. Case studies for 3 more challenging DDI predictions (ie, for eliglustat, tofacitinib, and ribociclib) are presented. Along with parameter sensitivity analysis to understand key parameters impacting DDI simulations, alternative model structures should be considered, eg, a mechanistic absorption model instead of a first-order absorption model might be more appropriate for a P-gp substrate with low permeability. Any mechanisms pertinent to the CYP3A substrate that rifampin might impact should be considered for inclusion in the model. While this analysis focused on rifampin, the learnings should apply to other inducers