The life sciences industry has recently been rocked by dramatic changes in how healthcare is provided, how drugs are developed and researched, the technologies available that enable companies to optimise operations, and the regulatory shifts that were implemented to address the changing life sciences landscape. It seems, for the pharmaceutical and medical device industries, the only constant is change.
And as we forge into 2023, it’s already apparent that further ongoing changes will constantly pressure companies to adapt, by adopting new technologies and ways of executing critical business operations. Here are six predictions from IQVIA, addressing what life sciences companies should expect and prepare for in 2023 – from optimising data for artificial intelligence (AI) analysis, to comprehensive labelling technology, natural language processing (NLP) for detecting adverse events (AEs), and more.
Life sciences organisations prepare data & IT landscapes for large-volume AI analysis
Andrew Mitchell, global head of product management and senior director of pharmacovigilance & regulatory technology at IQVIA believes that “AI is being hailed as the saviour of everything and, while there is much promise, one must look beyond the hype as technology adoption follows a well-defined path. AI-technology for life sciences is still firmly in an early adoption phase. It is yet to navigate the ‘trough of disillusionment’ that much-touted technologies like crypto and blockchain now find themselves in.”
He continues: “Drug Safety departments are responsible for protecting patients by managing the risks associated with medical products, products which cost on average $1.3bn to bring to market*1. We should not take our ‘hands off this wheel’ when vehicle motor manufacturers face federal action over inflated ‘self-driving’ claims with serious, sometimes fatal, motor accidents resulting from an over reliance on automation.”
“Machine translation is mature, compared with many other AI-driven automation technologies, yet, even with BLU scores above 85%, adverse event translations require human certification,” Mitchell explains. “Our prediction for 2023 is that life sciences companies, and Drug Safety departments in particular, will continue to invest in AI – however truly autonomous, touchless safety case processing will be bespoke, and targeted solutions delivered. For example, handling large, clearly defined sub-sets of adverse events related to COVID vaccines. Long-term value for most organisations will be in ‘AI-assistance’ not ‘touch-less automation’, but the biggest steps forward will be in AI-preparation that delivers value from Day One – improving the quality and oversight of data, standardising, adding consistency, and reducing latency in order to deliver actionable analytics.”
Smart labelling technology becomes keystone investment for regulatory compliance
Cham Williams, associate director of business systems at IQVIA, predicts that, “In order to remain compliant with increasingly stringent labelling regulations, life sciences organisations must prioritise labelling technology modernisation in their 2023 IT roadmap. Organisations need to be proactive about labelling in the coming year; most don’t see an issue with the current process, but 50% of recalls are caused by labelling.”
Williams continues: “The organisations that successfully deploy smart labelling technology, including intelligent automation and natural language processing (NLP), will gain a real-time view of the status of every labelling change and have a better understanding of how to adjust labels and communicate those changes to localisation teams around the world. NLP and AI are likely to become popular tools for labelling products. They will add value and help make product decisions more efficient. The adoption of these transformational technologies is a first step for structured content that can be repurposed in submissions and regulatory processes.”
Connecting intelligence across the enterprise is now critical for quality operations
I myself, as senior director of product management in quality solutions at IQVIA, believe that, as life sciences quality operations continue to shift from reactive to proactive, organisations that want to further support quality processes by deploying artificial intelligence (AI) and machine learning (ML) in 2023 and beyond must take a connected intelligence approach to quality operations. This involves deploying true cloud solutions designed for the life sciences industry that can connect information from end-to-end enterprise operations and data silos to feed AI and ML algorithms and generate quality insights.
I also think that taking a connected intelligence approach involves solving the AI/ML validation problem. One of the things that has held back AI/ML for use in life sciences companies is that software must be validated, and validation focuses on achieving expected results. However, AI and ML are difficult to validate because you can realise new, unprecedented insight from AI/ML analysis, which will require validation techniques that extend beyond traditional validation methods.
Despite these challenges, organisations that fail to take a connected intelligence approach and deploy AI/ML to quality operations will find they do not have access to the information needed to reap actionable insights and optimise quality operations.
Natural language processing enables safety teams to manage surging adverse event volumes
Alisa Hummings, global head CEVA, medical information and pharmacovigilance, at IQVIA, notes: “Lifecycle safety teams are able to identify and track an increasing number of adverse events in the life sciences industry each year. In part, this is due to new digital sources of information, such as social media, online forums, and wearable devices like fitness watches that monitor health signals. In addition, medicines are becoming increasingly targeted towards specific populations for niche treatments. Inefficient and noncompliant safety operations are made much more difficult through use only of human analysis.”
Hummings adds: “Companies that have not implemented artificial intelligence (AI) and natural language processing (NLP) technologies to support the identification and analysis of potential AEs by 2023 will find themselves failing to keep up with tightening regulations, as opposed to their competitors who have successfully deployed AI for safety operations.”
Cross-functional integration is adopted to add value throughout drug development lifecycle
Michelle Gyzen, senior director of strategic solutions in regulatory affairs & drug development solutions at IQVIA, believes: “Regulatory affairs teams within life sciences organisations possess a unique opportunity to drive connected intelligence across the enterprise to support critical drug development, safety, and regulatory operations. Companies traditionally use stand-alone applications to handle regulatory affairs, which means they can’t easily access data from separate safety, regulatory, and quality systems.”
Gyzen continues: “However, life sciences organisations that want to succeed and innovate in 2023, as well as open the doors to future innovations that can directly impact market success and revenue capture, must deploy cross-functional integration between regulatory and other verticals within biopharma (safety, clinical, quality, etc.). Cross-functional integration between verticals creates better synergy and value along the continuum of the drug development lifecycle.”
She also notes: “The use of AI for regulatory operations in life sciences is about to explode in 2023. Regulatory technology of the future will do much more than gather data – it will also use automation and predictive analytics to provide intelligent, actionable insights. The main challenge in incorporating artificial intelligence (AI) into regulatory systems is bridging the gap between historical data sets.”
Gyzen concludes: “By starting cross-functional integration with regulatory affairs and drug development, organisations can immediately see the impact of eliminating data silos and effectively managing valuable data across the enterprise. In addition, the comprehensive nature of now-connected data sources will enable more in-depth AI-driven analysis – leading to valuable, actionable insights that improve not only regulatory operations but enterprise success as a whole.”
Unending innovation in the face of constant change yields life sciences leaders
As we continue to experience new trends and operational changes in the life sciences industry, companies will be required to meet those changes and overcome new obstacles by adapting new ways of executing critical operations and optimising processes. Those companies that remain at the forefront of innovation, by adopting technology solutions that are designed to address industry pain points, will be best equipped to ascend to the top of the next generation of life sciences leaders.
About the author
As regulatory and product management leader for IQVIA’s Quality Compliance, Kari Miller is responsible for driving strategic product direction, and delivery of industry best practices and regulatory compliance solutions for quality management. She focuses specifically on translating market and industry requirements into enterprise quality management solutions that meet the needs of the heavily regulated Life Sciences market. Miller is also responsible for the Quality Compliance product roadmap, product partner relationships, and overall product direction.
