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- Tobias, Deirdre K, et al.
(författare)
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Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
- 2023
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Ingår i: Nature Medicine. - 1546-170X. ; 29:10, s. 2438-2457
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Forskningsöversikt (refereegranskat)abstract
- Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.
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- Fabre, Kristin M., et al.
(författare)
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Utilizing microphysiological systems and induced pluripotent stem cells for disease modeling : a case study for blood brain barrier research in a pharmaceutical setting
- 2019
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Ingår i: Advanced Drug Delivery Reviews. - : Elsevier. - 0169-409X .- 1872-8294. ; 140, s. 129-135
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Tidskriftsartikel (refereegranskat)abstract
- Microphysiological systems (MPS) may be able to provide the pharmaceutical industry models that can reflect human physiological responses to improve drug discovery and translational outcomes. With lack of efficacy being the primary cause for drug attrition, developing MPS disease models would help researchers identify novel targets, study mechanisms in more physiologically-relevant depth, screen for novel biomarkers and test/optimize various therapeutics (small molecules, nanoparticles and biologics). Furthermore, with advances in inducible pluripotent stem cell technology (iPSC), pharmaceutical companies can access cells from patients to help recreate specific disease phenotypes in MPS platforms. Combining iPSC and MPS technologies will contribute to our understanding of the complexities of neurodegenerative diseases and of the blood brain barrier (BBB) leading to development of enhanced therapeutics. © 2018
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- Shields, Beverley M., et al.
(författare)
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Development of a clinical calculator to aid the identification of MODY in pediatric patients at the time of diabetes diagnosis
- 2024
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Ingår i: Scientific Reports. - : NATURE PORTFOLIO. - 2045-2322. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Maturity Onset Diabetes of the Young (MODY) is a young-onset, monogenic form of diabetes without needing insulin treatment. Diagnostic testing is expensive. To aid decisions on who to test, we aimed to develop a MODY probability calculator for paediatric cases at the time of diabetes diagnosis, when the existing "MODY calculator" cannot be used. Firth logistic regression models were developed on data from 3541 paediatric patients from the Swedish 'Better Diabetes Diagnosis' (BDD) population study (n = 46 (1.3%) MODY (HNF1A, HNF4A, GCK)). Model performance was compared to using islet autoantibody testing. HbA1c, parent with diabetes, and absence of polyuria were significant independent predictors of MODY. The model showed excellent discrimination (c-statistic = 0.963) and calibrated well (Brier score = 0.01). MODY probability > 1.3% (ie. above background prevalence) had similar performance to being negative for all 3 antibodies (positive predictive value (PPV) = 10% v 11% respectively i.e. similar to 1 in 10 positive test rate). Probability > 1.3% and negative for 3 islet autoantibodies narrowed down to 4% of the cohort, and detected 96% of MODY cases (PPV = 31%). This MODY calculator for paediatric patients at time of diabetes diagnosis will help target genetic testing to those most likely to benefit, to get the right diagnosis.
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