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AI has the potential to speed up clinical trials

AI and ML are streamlining clinical trials, delivering validated real-time data to decision-making teams faster and with more accuracy.

EU agency says two jabs 'vital' to battle Delta variant
The European Medicines Agency said that evidence suggests that "both doses of a two-dose Covid-19 vaccine... are needed to provide adequate protection against the Delta variant" - Copyright AFP/File KAREN BLEIER
The European Medicines Agency said that evidence suggests that "both doses of a two-dose Covid-19 vaccine... are needed to provide adequate protection against the Delta variant" - Copyright AFP/File KAREN BLEIER

Healthcare is drowning in the sea of unused data they collect. Yet healthcare leaders can potentially take advantage of this amass of data. For example, with clinical trials. When performing clinical trials, patient data – quality control, quantity and availability – is paramount for maintaining quality assurance and for the faster turnaround needed to develop drugs and treatments.

Tim Riely, VP Clinical Data Analytics at IQVIA, has been considering how business leaders in the life sciences industry can leverage AI-enhanced data to accelerate interoperability, flexibility/speed, and insightful data visualization.

Tim Riely begins his assessment by considering the extent of data that needs to be processed within the healthcare world: “Tasked with analysing over 1 trillion gigabytes of data annually, business leaders in life sciences are reaping significant benefits from AI-enhanced data to transform their operations and achieve accelerated outcomes.”

To aid scientists in this task, artificial intelligence, including machine learning algorithms, can be of assistance. Here Riely puts forward: “AI and ML are streamlining clinical trials, delivering validated real-time data to decision-making teams faster and with more accuracy.”

More specifically, Riely thinks that such technologies can: “This accelerates the drug development process and minimizes risks of data deviation, enhancing staff productivity and improving data collection.

With actual cases in the life sciences sector, Riely puts forward: “Biopharma organizations, for example, are embedding AI across the lifecycle of their assets, leading to increased success rates, faster regulatory approvals, minimized time for reimbursement and improved cash flow from the clinical trial process, from start through launch.”

Furthermore, he adds: “AI is also helping clinical staff submit documents to the Trial Master File (a set of documents proving that the clinical trial has been conducted following regulatory requirements) faster, improve the quality of data collected as part of the trial, identify sub-populations of individuals who most benefit from a treatment and predict risks to a clinical trial.” 

As AI itself advances and increases its ‘thinking’ capabilities, healthcare can garner further advantages. Riely sees some of these as: “As we move into a world of generative AI, we are seeing a positive impact across the industry. Specifically, by gaining insights faster through chat interfaces, developing solutions faster with new engineering tools, improving discrepancy detection and accelerating document authoring – making tasks such as protocol creation and safety narratives more efficient.”

There are risks that need to be considered when embarking on the use of such technologies, and Riely is mindful of these: “However, as with all new technology implementations, it is also important to take precautions when implementing generative AI. To harness its full potential, the technology must be trained with high-quality, regulatory-compliant data and provide recommendations to experts making final decisions. It must also be engineered for security, safety and accuracy.”

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Written By

Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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