Big Data Genome Regulation Research 
Drug Discovery World
JULY 11, 2023
Drug discovery and development timelines can span 10-15 years or more from initial discovery to market approval and typically require the analysis of massive amounts of data. Advances in quantum computing are also showing early promise for increasingly complex data analyses.
pharmaphorum
JULY 4, 2022
And this is where modern technologies and data-driven medical informatics can really bridge the gaps in rare disease research,” said Dr Joanne Hackett, head of Genomic and Precision Medicine at IQVIA, during a recent pharmaphorum webinar. Navigating rare disease research and treatment.
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Drug Discovery World
FEBRUARY 6, 2024
Technologies like artificial intelligence (AI), machine learning (ML) and robotics/automation are enabling researchers to process enormous data sets and conduct preclinical investigations in record time, speeding up the process and offering greater accuracy.
XTalks
APRIL 5, 2021
Bioinformaticians use a combination of mathematics, computer science and biology to help scientists make sense of the data gathered from research projects. The Human Genome Project could not have succeeded without the use of bioinformatics. This job furthers the field of biomedical research and supports drug development.
pharmaphorum
MARCH 16, 2021
International deep real-world evidence company Savana is on a mission to give health researchers the power to unlock the clinical value embedded within electronic health records (EHRs) using artificial intelligence (AI) and clinical Natural Language Processing (NLP) techniques. AI use in the pandemic.
Drug Discovery World
DECEMBER 27, 2023
Ng is working on critical challenges in clinical trials, specifically in planning and recruitment, and has been building innovative solutions designed to benefit patients and researchers – with a focus on efficiency, transparency and diversity in clinical development. This episode is available here.
Drug Discovery World
SEPTEMBER 5, 2022
Throughout the continuum of drug development, from target discovery to patient selection, machine learning approaches are being adopted to reliably mine vast amounts of data and make predictions with higher accuracy Anita Ramanathan discusses how machine learning is currently used across different stages of cancer research. .
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