A recent survey found that 82% of pharmaceutical industry professionals believe that digital transformation will either significantly or moderately shorten the drug development timeline.
The survey was conducted by analytics company GlobalData, which is the parent company of Pharmaceutical Technology.
It found that, of 107 responses, only 3% deemed that digital transformation would have no impact on the drug development timeline while almost half (47%) expected the timeline to be moderately shortened.
Commenting on the results Urte Jakimaviciute, senior director of market research and strategic intelligence at GlobalData, said: “Survey findings highlight that the growing recognition within the pharmaceutical industry that technology, particularly AI, is accelerating innovation and efficiency in the drug discovery and development process, enabling processes such as faster identification of potential drug candidates and optimisation clinical trials processes.”
In a separate survey published in September, respondents were asked how disruptive they anticipated a variety of technologies to be within pharmaceuticals. AI emerged as the most disruptive, with 53.2% considering the disruption to be significant and 21% quantifying it as slight.
Respondents also considered target identification to be the component of the pharmaceutical value chain most set to benefit from the incorporation of AI. This was followed by lead generation and optimisation and pre-clinical and clinical trials.
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By GlobalData
Jakimaviciute concluded: “The fact that most AI-driven drugs are in early stages suggests that more companies are increasingly turning to AI to explore and expand their drug pipelines. This trend also reflects the industry’s growing reliance on AI to enhance R&D productivity. As the industry continues to recognise the potential of AI, this technology is set to become even more essential.”
The digital transformation is already underway, and examples of AI use in drug development are already evident: GlobalData’s drugs database tracks more than 3,000 drugs that have either been developed or repurposed using AI. At this stage, most remain in the early stages of development, either in discovery or pre-clinical.
