TECH & AI
Photo : © GSK
“ A drug is not just a drug . There is this whole ecosystem around it ”
PAUL AGAPOW LEADER IN BIOMEDICAL DATA SCIENCE & MACHINE LEARNING , GSK
Paul Agapow , Leader in Biomedical Data Science and Machine Learning at GSK , says : “ It ’ s a data-rich process . It ' s the right optimisation and , if you could just lean on part of this process , make it 1 % more efficient and so forth , there could be great benefits and great savings there .”
GSK has made some major strides within the field , recently entering into a three-year collaboration agreement that provides GSK with access to Tempus ’ AI-enabled platform , including its library of de-identified patient data . Through its leading AI / ML capabilities , GSK will work together with Tempus to improve clinical trial design , speed up enrollment and identify drug targets . This will contribute to GSK ’ s R & D success rate and provide patients with more personalised treatments , faster .
The problems with mass data The process does not come without its pitfalls – specifically , the ‘ big data paradigm ’.
AI algorithms rely on high-quality data to make accurate predictions and decisions . However , the data used in drug development is often incomplete , inconsistent or biased . This can lead to inaccurate or unreliable results from AI algorithms , which can , in turn , impede the drug development process .
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