The startup provides data analytics specifically for neurological clinical trials, focusing on multiple sclerosis and other neurodegenerative disorders. By enhancing diagnostic accuracy and treatment efficiency, the company aims to improve patient outcomes in neurology.
Funding
$550K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Neurological clinical trials, particularly those focused on multiple sclerosis and other neurodegenerative diseases, require advanced data analytics to accurately assess treatment efficacy and patient outcomes. Traditional methods may lack the precision needed to identify subtle changes and personalize treatment strategies.
Solution
Queen Square Analytics (QSA) provides next-generation data analytics services for neurological clinical trials, leveraging imaging and machine learning technologies to optimize the understanding of treatment effects. QSA supports all stages of clinical trials, from pre-trial imaging protocol design and power calculations to during-trial services like quality audits and data-driven patient staging, and post-trial data mining, causal modelling, and biomarker integration. Their services expedite drug development by reducing the duration of clinical trials and enabling the identification of patient subtypes through AI applied to quantifiable measures, such as imaging and blood biomarkers. This approach facilitates the selection of effective therapies and predicts disability worsening by staging patients in data-driven subtypes.
Target Audience
QSA primarily serves pharmaceutical companies, research institutions, and clinical trial organizations involved in neurological studies, particularly those focused on multiple sclerosis and neurodegenerative disorders.
Features
- Imaging protocol design and optimization for clinical trial scanning sites
- Machine learning models for predicting personalized prognosis in multiple sclerosis
- Data-driven patient staging to stratify patients according to disease progression
- Causal modelling to understand treatment mechanisms of action
- Biomarker integration using multimodal machine learning models
- Brain age prediction from MRI scans for treatment response and disability prediction
- Full clinical research services supported by a certified quality management system and central data storage and archiving
- Compliance with ISO 9001 and FDA 21 Part 11