| 1. |
|
|
| 2. |
- Lapinlampi, Niina, et al.
(författare)
-
Common data elements and data management : Remedy to cure underpowered preclinical studies
- 2017
-
Ingår i: Epilepsy Research. - : Elsevier BV. - 0920-1211. ; 129, s. 87-90
-
Tidskriftsartikel (refereegranskat)abstract
- Lack of translation of data obtained in preclinical trials to clinic has kindled researchers to develop new methodologies to increase the power and reproducibility of preclinical studies. One approach relates to harmonization of data collection and analysis, and has been used for a long time in clinical studies testing anti-seizure drugs. EPITARGET is a European Union FP7-funded research consortium composed of 18 partners from 9 countries. Its main research objective is to identify biomarkers and develop treatments for epileptogenesis. As the first step of harmonization of procedures between laboratories, EPITARGET established working groups for designing project-tailored common data elements (CDEs) and case report forms (CRFs) to be used in data collection and analysis. Eight major modules of CRFs were developed, presenting >1000 data points for each animal. EPITARGET presents the first single-project effort for harmonization of preclinical data collection and analysis in epilepsy research. EPITARGET is also anticipating the future challenges and requirements in a larger-scale preclinical harmonization of epilepsy studies, including training, data management expertise, cost, location, data safety and continuity of data repositories during and after funding period, and incentives motivating for the use of CDEs.
|
|
| 3. |
- Müllauer, Julia, et al.
(författare)
-
Pharmacokinetic modeling of P-glycoprotein function at the rat and human blood--brain barriers studied with (R)-[11C]verapamil positron emission tomography.
- 2012
-
Ingår i: EJNMMI Research. - 2191-219X. ; 2
-
Tidskriftsartikel (refereegranskat)abstract
- ABSTRACT: BACKGROUND: This study investigated the influence of P-glycoprotein (P-gp) inhibitor tariquidar on the pharmacokinetics of P-gp substrate radiotracer (R)-[11C]verapamil in plasma and brain of rats and humans by means of positron emission tomography (PET). METHODS: Data obtained from a preclinical and clinical study, in which paired (R)-[11C]verapamil PET scans were performed before, during, and after tariquidar administration, were analyzed using nonlinear mixed effects (NLME) modeling. Administration of tariquidar was included as a covariate on the influx and efflux parameters (Qin and Qout) in order to investigate if tariquidar increased influx or decreased outflux of radiotracer across the blood--brain barrier (BBB). Additionally, the influence of pilocarpine-induced status epilepticus (SE) was tested on all model parameters, and the brain-to-plasma partition coefficient (VT-NLME) was calculated. RESULTS: Our model indicated that tariquidar enhances brain uptake of (R)-[11C]verapamil by decreasing Qout. The reduction in Qout in rats during and immediately after tariquidar administration (sevenfold) was more pronounced than in the second PET scan acquired 2 h after tariquidar administration (fivefold). The effect of tariquidar on Qout in humans was apparent during and immediately after tariquidar administration (twofold reduction in Qout) but was negligible in the second PET scan. SE was found to influence the pharmacological volume of distribution of the central brain compartment Vbr1. Tariquidar treatment lead to an increase in VT-NLME, and pilocarpine-induced SE lead to increased (R)-[11C]verapamil distribution to the peripheral brain compartment. CONCLUSIONS: Using NLME modeling, we were able to provide mechanistic insight into the effects of tariquidar and SE on (R)-[11C]verapamil transport across the BBB in control and 48 h post SE rats as well as in humans.
|
|
| 4. |
- Pitkänen, Asla, et al.
(författare)
-
Advances in the development of biomarkers for epilepsy
- 2016
-
Ingår i: Lancet Neurology. - 1474-4422. ; 15:8, s. 843-856
-
Forskningsöversikt (refereegranskat)abstract
- Over 50 million people worldwide have epilepsy. In nearly 30% of these cases, epilepsy remains unsatisfactorily controlled despite the availability of over 20 antiepileptic drugs. Moreover, no treatments exist to prevent the development of epilepsy in those at risk, despite an increasing understanding of the underlying molecular and cellular pathways. One of the major factors that have impeded rapid progress in these areas is the complex and multifactorial nature of epilepsy, and its heterogeneity. Therefore, the vision of developing targeted treatments for epilepsy relies upon the development of biomarkers that allow individually tailored treatment. Biomarkers for epilepsy typically fall into two broad categories: diagnostic biomarkers, which provide information on the clinical status of, and potentially the sensitivity to, specific treatments, and prognostic biomarkers, which allow prediction of future clinical features, such as the speed of progression, severity of epilepsy, development of comorbidities, or prediction of remission or cure. Prognostic biomarkers are of particular importance because they could be used to identify which patients will develop epilepsy and which might benefit from preventive treatments. Biomarker research faces several challenges; however, biomarkers could substantially improve the management of people with epilepsy and could lead to prevention in the right person at the right time, rather than just symptomatic treatment.
|
|
