Harnessing AI in Biopharma: A Transformative Journey, Not Just a Quick Fix
In the rapidly evolving landscape of biopharmaceuticals, the integration of artificial intelligence (AI) has emerged as a pivotal development. Recently, Zifo's prominent figure, Sujeegar Jeevanandam, offered insights into AI's impact on drug discovery, emphasizing that it should not be viewed as a magical solution but rather as a significant tool capable of revolutionizing research processes.
The demand for leveraging AI in drug discovery has skyrocketed, especially as the industry's reputation for being cautious in technology adoption faces scrutiny. According to Zifo’s latest survey, only one in three scientists express confidence in utilizing scientific data for AI applications. This statistic highlights a substantial gap in data readiness, which poses challenges for the biopharma sector striving to harness the power of AI effectively.
Despite this perceived caution, Jeevanandam insists that biopharma is not fundamentally risk-averse. He described the sector as inherently risky, where starting trials often entails navigating uncertainty. "You never start a trial with a guarantee of success; it's inherently a betting game," Sujeegar stated, underlining the industry's nature of calculated risks.
AI's true power, Jeevanandam elucidates, lies in its ability to provide cumulative value throughout various phases of the drug development pipeline. He argues that even a modest 5% improvement in any stage can lead to substantial savings, amounting to millions or even billions of dollars. The potential for cost efficiency makes AI a compelling consideration for organizations aiming to optimize their research endeavors.
Interestingly, Sujeegar points out that the most impactful applications of AI might not be the immediate, groundbreaking advancements that typically capture headlines. Instead, he highlighted the mundane yet essential ability of AI to quickly access and retrieve information—a task that can save significant time and resources. This practical utilization of AI can drastically improve workflows by eliminating time spent searching for existing data.
Concerns surrounding AI in the biopharma context often revolve around privacy and the evolving role of scientists in research. However, Jeevanandam reassures that expertise in AI is not a prerequisite for scientists. He advocates for an approach where AI is made more user-friendly, allowing a wider audience within the scientific community to engage with its capabilities. The responsibility of seamlessly integrating AI into biotechnology operations doesn't rest solely on data scientists; it extends across all levels, from lab technicians to executives.
According to Jeevanandam, the speed at which AI is being adopted today is surpassing previous technology revolutions, such as Electronic Lab Notebooks (ELN) and Laboratory Information Management Systems (LIMS). The onus is on everyone in the organization to incorporate AI effectively into their workflows and to leverage its benefits, illustrating the holistic nature of this technological shift.
To explore Sujeegar Jeevanandam’s complete viewpoint, you can visit Zifo’s official blog available online. Zifo Technologies, recognized globally as a leader in enabling AI and data-driven enterprise informatics for science-driven organizations, continues to advance the application of digital scientific innovations across various industries including Pharmaceuticals, Biotechnology, Chemicals, and more. With a trusted network of over 190 organizations worldwide, Zifo stands at the forefront of integrating AI into research, development, and clinical operations, paving the way for a future where science and technology work hand in hand to drive advancements in healthcare.
The demand for leveraging AI in drug discovery has skyrocketed, especially as the industry's reputation for being cautious in technology adoption faces scrutiny. According to Zifo’s latest survey, only one in three scientists express confidence in utilizing scientific data for AI applications. This statistic highlights a substantial gap in data readiness, which poses challenges for the biopharma sector striving to harness the power of AI effectively.
Despite this perceived caution, Jeevanandam insists that biopharma is not fundamentally risk-averse. He described the sector as inherently risky, where starting trials often entails navigating uncertainty. "You never start a trial with a guarantee of success; it's inherently a betting game," Sujeegar stated, underlining the industry's nature of calculated risks.
AI's true power, Jeevanandam elucidates, lies in its ability to provide cumulative value throughout various phases of the drug development pipeline. He argues that even a modest 5% improvement in any stage can lead to substantial savings, amounting to millions or even billions of dollars. The potential for cost efficiency makes AI a compelling consideration for organizations aiming to optimize their research endeavors.
Interestingly, Sujeegar points out that the most impactful applications of AI might not be the immediate, groundbreaking advancements that typically capture headlines. Instead, he highlighted the mundane yet essential ability of AI to quickly access and retrieve information—a task that can save significant time and resources. This practical utilization of AI can drastically improve workflows by eliminating time spent searching for existing data.
Concerns surrounding AI in the biopharma context often revolve around privacy and the evolving role of scientists in research. However, Jeevanandam reassures that expertise in AI is not a prerequisite for scientists. He advocates for an approach where AI is made more user-friendly, allowing a wider audience within the scientific community to engage with its capabilities. The responsibility of seamlessly integrating AI into biotechnology operations doesn't rest solely on data scientists; it extends across all levels, from lab technicians to executives.
According to Jeevanandam, the speed at which AI is being adopted today is surpassing previous technology revolutions, such as Electronic Lab Notebooks (ELN) and Laboratory Information Management Systems (LIMS). The onus is on everyone in the organization to incorporate AI effectively into their workflows and to leverage its benefits, illustrating the holistic nature of this technological shift.
To explore Sujeegar Jeevanandam’s complete viewpoint, you can visit Zifo’s official blog available online. Zifo Technologies, recognized globally as a leader in enabling AI and data-driven enterprise informatics for science-driven organizations, continues to advance the application of digital scientific innovations across various industries including Pharmaceuticals, Biotechnology, Chemicals, and more. With a trusted network of over 190 organizations worldwide, Zifo stands at the forefront of integrating AI into research, development, and clinical operations, paving the way for a future where science and technology work hand in hand to drive advancements in healthcare.
Topics Health）
【About Using Articles】
You can freely use the title and article content by linking to the page where the article is posted.
※ Images cannot be used.
【About Links】
Links are free to use.