We are pleased to share that Soroosh Afyouni, PhD, Head of Health Data Sciences at bioXcelerate AI, has been featured in an insightful article discussing the critical role of effective data management in accelerating drug discovery and development.
The article, titled Accelerating Drug Discovery and Development with Effective Data Housekeeping, explores how the vast and ever-expanding biobanks of patient medical records, clinical trial data, and genetic information hold immense potential – but only if they are properly managed. Without structured and high-quality data, even the most advanced AI and machine learning models struggle to generate reliable insights.
Key Insights from the Article
The Challenge of Inconsistent Data
Data in healthcare often exists in varying formats, making comparisons difficult and reducing the effectiveness of AI-driven analysis.
The Importance of Data Quality
Poor data quality can hinder clinical trials, with studies showing that up to 50% fail due to a lack of clinical efficacy.
FAIR Data Principles
To maximise the potential of AI and machine learning in healthcare, data must be Findable, Accessible, Interoperable, and Reusable (FAIR). This enables better integration, collaboration, and innovation.
Collaboration Between Academia and Industry
By establishing robust data curation and standardisation practices, academia and industry can work together to improve the reproducibility of findings and accelerate patient outcomes.
About Soroosh Afyouni PhD
Soroosh Afyouni, PhD, leads the Health Data Sciences team at bioXcelerate AI. With a background in statistical neuroimaging and machine learning, he has held research positions at the University of Oxford and the University of Cambridge. His expertise spans the development of time series models for large-scale datasets and the application of AI in early disease detection. Soroosh also brings industry experience from working with major pharmaceutical companies on R&D and clinical trial optimisation.
Read the Full Article
View the full article here.