Pharmacokinetics of Intravenously (DIZ101), Subcutaneously (DIZ102), and Intestinally (LCIG) Infused Levodopa in Advanced Parkinson Disease.

Neurology

From the Department of Pharmacology (F.B., E.E.), University of Gothenburg; Neurology (F.B.), Sahlgrenska University Hospital, Göteborg; Department of Pharmaceutical Biosciences (M.E.), Uppsala University; Pharm Assist Sweden AB (M.E.), Uppsala; Department of Neuroscience (D.N.), Uppsala University; Department of Clinical Neurosciences (A.J., P.S.), Karolinska Institutet (A.J., P.S.), Solna; Department of Biomedical and Clinical Sciences (F.L., N.D.), Linköping University (F.L., N.D.); Neurology (P.O.), Department of Clinical Sciences, Lund University; CTC Clinical Trial Consultants AB (F.H.), Uppsala; and Dizlin Pharmaceuticals (L.B.) Gothenburg, Sweden.

Published: September 2022

Background And Objectives: Intestinal levodopa/carbidopa gel infusion (LCIG) is superior to oral treatment in advanced Parkinson disease. The primary objective of this trial was to investigate whether continuous subcutaneous or intravenous infusion with a continuously buffered acidic levodopa/carbidopa solution yields steady-state plasma concentrations of levodopa that are equivalent in magnitude, and noninferior in variability, to those obtained with LCIG in patients with advanced Parkinson disease.

Methods: A concentrated acidic levodopa/carbidopa (8:1) solution buffered continuously and administered intravenously (DIZ101) or subcutaneously (DIZ102) was compared with an approved LCIG in a randomized, 3-period crossover, open-label, multicenter trial. Formulations were infused for 16 hours to patients with Parkinson disease who were using LCIG as their regular treatment. Patients were recruited from several university neurology clinics but came to the same phase I unit for treatment. Pharmacokinetic variables and safety including dermal tolerance are reported. The primary outcomes were bioequivalence and noninferior variability of DIZ101 and DIZ102 vs LCIG with respect to levodopa plasma concentrations.

Results: With dosing adjusted to estimated bioavailability, DIZ101 and DIZ102 produced levodopa plasma levels within standard bioequivalence limits compared with LCIG in the 18 participants who received all treatments. Although the levodopa bioavailability for DIZ102 was complete, it was 80% for LCIG. Therapeutic concentrations of levodopa were reached as quickly with subcutaneous administration of DIZ102 as with LCIG and remained stable throughout the infusions. Owing to poor uptake of LCIG, carbidopa levels in plasma were higher with DIZ101 and DIZ102 than with the former. All individuals receiving any of the treatments (n = 20) were included in the evaluation of safety and tolerability. Reactions at the infusion sites were mild and transient.

Discussion: It is feasible to rapidly achieve high and stable levodopa concentrations by means of continuous buffering of a subcutaneously administered acidic levodopa/carbidopa-containing solution.

Trial Registration Information: ClinicalTrials.gov identifier: NCT03419806. Registration first posted on February 5, 2018, first patient enrolled on February 16, 2018.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9519246PMC
http://dx.doi.org/10.1212/WNL.0000000000200804DOI Listing

Publication Analysis

Top Keywords

advanced parkinson
12
parkinson disease
12
diz101 diz102
12
lcig
10
intravenously diz101
8
diz101 subcutaneously
8
subcutaneously diz102
8
acidic levodopa/carbidopa
8
levodopa/carbidopa solution
8
concentrations levodopa
8

Similar Publications

Nutritional epidemiology aims to link dietary exposures to chronic disease, but the instruments for evaluating dietary intake are inaccurate. One way to identify unreliable data and the sources of errors is to compare estimated intakes with the total energy expenditure (TEE). In this study, we used the International Atomic Energy Agency Doubly Labeled Water Database to derive a predictive equation for TEE using 6,497 measures of TEE in individuals aged 4 to 96 years.

View Article and Find Full Text PDF

Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.

View Article and Find Full Text PDF

Small, obligately anaerobic strains 13CB8C, 13CB11C, 13CB18C and 13GAM1G were isolated from a faecal sample in a patient with Parkinson's disease with a history of duodenal resection. After conducting a comprehensive polyphasic taxonomic analysis including genomic analysis, we propose the establishment of one new genus and four new species. The novel bacteria are sp.

View Article and Find Full Text PDF

Does aligning misinformation content with individuals' core moral values facilitate its spread? We investigate this question in three behavioral experiments ( = 615; = 505; ₂ = 533) that examine how the alignment of audience values and misinformation framing affects sharing behavior, in conjunction with analyzing real-world Twitter data ( = 20,235; 809,414 tweets) that explores how aligning the moral values of message senders with misinformation content influences its dissemination in the context of COVID-19 vaccination misinformation. First, we investigate how aligning messages' moral framing with participants' moral values impacts participants' intentions to share true and false news headlines and whether this effect is driven by a lack of analytical thinking. Our results show that framing a post such that it aligns with audiences' moral values leads to increased sharing intentions, independent of headline familiarity, and participants' political ideology but find no effect of analytical thinking.

View Article and Find Full Text PDF

Introduction: Neurodegenerative diseases, including Parkinson's, Alzheimer's, and epilepsy, pose significant diagnostic and treatment challenges due to their complexity and the gradual degeneration of central nervous system structures. This study introduces a deep learning framework designed to automate neuro-diagnostics, addressing the limitations of current manual interpretation methods, which are often time-consuming and prone to variability.

Methods: We propose a specialized deep convolutional neural network (DCNN) framework aimed at detecting and classifying neurological anomalies in MRI data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!