For the third year in a row, Cognizant has signed up to the Pharma Industry Awards 2024 as impact ambassador. The impact ambassador programme drives engagement with thought leadership initiatives from companies supporting the sector; Cognizant helps firms use technology to modernise and build new business processes. Business River, organiser of the awards, asked Cognizant’s David Staunton, head of transformation, life sciences manufacturing, and David Sheedy, head of life sciences manufacturing Ireland, for their predictions for the year ahead.
What do you see as the most significant trends and developments currently shaping the life sciences pharmaceutical industry?
In the highly competitive and fast-paced pharmaceutical manufacturing industry, several significant trends and developments are shaping its future. GMP manufacturers are focused on accelerating product launches, increasing production capacity for high-demand medicines, enhancing supply chain security and improving sustainability. The industry is leveraging advanced technologies to achieve these goals, with a particular emphasis on data utilisation.
Establishing a defined and centralised data infrastructure is crucial, enabling companies to connect, access, store and analyse data effectively. This data-centric approach helps in making informed business decisions, optimising production processes and improving the economics of medicine manufacturing.
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Additionally, the push towards personalised treatments and cures is driving innovation, with traditional and generative AI technology playing a pivotal role in making these new therapies more affordable and accessible. The integration of cutting-edge technologies and robust data management systems is essential for companies to remain competitive and thrive in this evolving landscape.
Where is digital innovation having the biggest impact in the life sciences pharmaceutical industry today? Are there particular technologies that are driving these advancements?
Digital innovation is profoundly impacting the life sciences manufacturing industry, primarily through advances in connecting systems to each other and the cloud, as well as using AI, generative AI, digital twins and advanced data analytics to drive business value.
These technologies streamline new product introductions by enhancing process understanding to reduce timelines. They also boost production capacity for in-demand medicine by improving global decision-making, increasing equipment reliability and reducing batch release times. This strategic use of digital innovations ensures that companies remain competitive and ready for future technological advancements.
What are the key factors that contribute to achieving true innovation in the pharmaceutical manufacturing industry?
Innovation is about creatively making guesses, whilst using trial and error to create evidence for progress towards the end goal. This forward-thinking mindset, combined with a very clear picture of what value you need to drive is crucial.
A culture of continuous improvement and openness to new technologies includes promoting collaboration, agility and a willingness to adopt new approaches tailored to achieving company goals.
For example, if the objective is to accelerate product launch or increase capacity and yield, implementing digital twins can help achieve these objectives. If done correctly digital twins allow companies to learn offline using trial and error minimising production disruptions and accelerating innovation. Utilising advanced data analytics and AI in combination with digital twins can significantly optimise decision-making and improve efficiency.
Best practice implementation approaches ensure that new technologies and processes are seamlessly integrated, maximising their benefits.
Artificial intelligence, particularly generative AI, is revolutionising various sectors. How is AI being used in the life sciences pharmaceutical industry, and what potential do you see for generative AI in drug discovery and development?
In the life sciences and pharmaceutical industry, AI – particularly generative AI – is revolutionising operations by enhancing decision-making and data analysis. Generative AI interfaces simplify and enhance access to insights across various organisational functions. When combined with mathematical modelling, and digital twins, generative AI facilitates a new dimension of decision-making, providing actionable insights in real time. It helps identify the next best actions for manufacturers, lab maintenance and IT/OT staff, enhancing team capabilities.
This technology is integral to digital transformation strategies, delivering in-depth data analysis and answers to critical questions instantly. In drug discovery and development, AI’s potential lies in its ability to analyse vast data sets, predict molecule behaviour and streamline research processes. Life science companies are increasingly leveraging generative AI to transform operations, enhance efficiency and accelerate innovation in drug development.
How is the integration of cutting-edge technology transforming the way pharmaceutical companies operate and innovate?
Cutting-edge technology including generative AI is already revolutionising pharmaceutical companies by streamlining operations, enhancing innovation and improving sustainability. Generative AI accelerates new product introductions by automatically conducting process-fit and lab method transfer gap analyses to reduce project timelines.
It enhances staff capabilities with near real-time information, leading to better decision-making and increased capacity. In supply chain management, generative AI provides precise guidance on tasks and timings, improving reliability and security of supply.
For sustainability, generative AI interfaces with digital twins to offer insights into energy, water and solvent usage, aiding environmentally friendly decisions without requiring extensive training.
Companies are leveraging AI to optimise drug discovery and development processes, using it to analyse vast data sets and predict molecule behaviour, thus expediting research and reducing costs. AI-driven continuous improvement mechanisms establish and refine standard work procedures, supporting operational excellence through data-driven insights and iterative enhancements.
Looking ahead, what are the emerging technologies or innovations that will have the most profound impact on the pharmaceutical industry over the next decade?
Several emerging technologies will profoundly impact the pharmaceutical industry. This century is marked by biotech advancements and the promise of connected, deployable modular factories, enhancing access to personalised treatments. This would mean instead of one factory serving millions with standardised medicine, modular factories can be situated on hospital premises, treating patients with personalised therapies processed on-site.
Generative AI reduces the need for specialist coding expertise, significantly shortening project timelines. It also facilitates programming robots, reducing workloads and enabling widespread use of robotics in manufacturing and laboratories. Industry 4.0′s integration of cyber-physical systems introduces co-bots, working alongside humans to enhance efficiency and productivity.
Moreover, bidirectional connectivity and seamless data flow through advanced tech stacks are becoming economically vital, making the vision of personalised, efficient and scalable pharmaceutical manufacturing a reality. These innovations promise to revolutionise the industry, bringing us closer to curing diseases and making personalised medicine more accessible.
