Transforming Pharma with the Power of Generative AI

Generative AI might be the biggest technological inflection point in history and can play a crucial role in enterprise reinvention. Companies are fast realizing the power of Large Language Models (LLMs) and generative AI foundation models in reimagining the way they work. Every role in every enterprise could potentially be reinvented as human-AI collaboration becomes the norm, dramatically amplifying what people can achieve. What’s unique about this evolution is that AI technology, regulation, and business adoption are all accelerating exponentially at the same time.

Generative AI’s Impact on the Pharma Industry

Generative AI can transform the Life Sciences/Pharma industry across the contours of productivity, growth, and efficiency. Functional domains will see a revamp; in fact, early signs of adoption and success are visible across research and drug development and commercial excellence. Pharma-specific occupations across Research and Drug Development, Marketing, Supply Chain, and Manufacturing value chains have a higher potential for generative AI-powered transformation.

1.?Commercial Excellence for Pharma with Generative AI

In pharma sales and marketing, generative AI can power transformation across content management, production, automation, and personalization, leading to better engagement with healthcare professionals (HCPs). Today, generative AI can create content in a few days and adapt content in mere hours. With the power of LLM applications across text, videos, and images, building personalized presentations will drive the HCP experience to the next level. With AI algorithms like Next Best Action and Next Best Timing, businesses can deliver these experiences while leveraging generative AI to work with the target messaging content.

Medical representatives can become more empowered and efficient with on-time nudges and tags that can be relevant both in a doctor’s office and in the field. Smarter generative AI agents can provide pre- and post-call summaries with chatbots for experience augmentation. These personal agents in the field force could also include the softer aspects of grooming, language, and presentation skills that will help control attrition and drive productivity.

Deploying generative AI, coupled with traditional AI, in pharma sales, marketing, and distribution can help realize 10-15 percent (reference #1) incremental growth for pharma companies.

2. Generative AI-powered Research and Drug Development

In the case of innovators, faster identification of novel molecular structures is now becoming a reality due to generative AI, significantly improving speed to market. Research and drug development operations in pharma will get a significant boost through areas like literature review and summarizing the same, compound generation, predicting binding properties to create new structures, and drug formulation design. For generic pharma companies, identifying off-patent drugs and molecules, creating filings, and being the first mover help create competitive advantage. Another area of research and drug development that will see transformation is clinical trials, by reducing the burden on patient data through synthetic data generation. Research and drug development can achieve 10-20 percent (reference #2) faster time to market through the application of generative AI across identification, documentation, and discovery.

3. Excelling with Generative AI across Operations

Functions like finance, manufacturing, and procurement can also see significant disruptions through automation, greater implementation speed, and improved employee experience.

In manufacturing in particular, generative AI can enable standard operating procedure (SOP) management, scenario planning for process optimization and re-design of manufacturing processes, real-time quality monitoring, identifying batch failure, and documentation of the same. Production plans and schedules can be created at the click of a button using generative AI.

Many pharma plants are piloting the use of generative AI for regulatory compliance, summarizing responses to warning letters and crafting first-draft responses to the same.

With faster compliance to finance-related procedures, anomaly detection and risk management are areas that generative AI can enable for the CFO organization. In procurement, generative AI can aid with contract risk management, contract drafting, and even master data management for long-tail indirect spend items.

The C-Suite Imperative

1. Envisage: Ninety percent (reference #3) of biopharma executives report that in the next three years, they anticipate a medium to high impact to their organization’s business processes as a result of generative AI chatbots. However, it’s important to make it real by moving from top-floor to shopfloor and empowering each of the functions to start their journeys towards a generative AI-led transformation. Executives were late to realize the real power of descriptive and predictive AI; with generative AI, the clock is ticking, and the first mover will have the edge over the competition. In Pharma, there are always ‘no-regret’ bets that can be made with generative AI – specifically backend functions like Procurement, Finance and even HR. These functions would surely see the benefit of efficiency and productivity. ?
2. Evaluate: Generative AI is not the solution to every problem. However, at the same time, every aspect of the pharma industry stands to be transformed by this technology. The industry must evaluate its promises prudently, but at the same time, not be constrained by a ‘use-case’ mindset. Organizations must take a dual approach to experimentation: on one hand, they should focus on ‘low-hanging fruit’ using consumable models and applications to realize quick returns, while on the other, they should reinvent the business with models that are customized using their data. At the same time, businesses should not neglect the enablement of enterprise-grade LLM applications and environments. The roles of CIO, CDO, and Analytics Lead are critical in evaluating what is right and provisioning it for the organization. This is where a 2-speed approach will help: one with no-regret functions through a big-bang approach and another with business-critical functions – an approach of cautious interventions – can be thought of. ?
3. Enable: Each layer of the generative AI tech stack (applications, fine-tuning, foundation models, data, and infrastructure) will rapidly evolve as the technology matures and as demand grows. Foundation models need vast amounts of curated data to learn and that makes solving the data challenge an urgent priority for every business. It is important to take a strategic and disciplined approach to acquiring, refining, safeguarding, and deploying data. Organizations need to ensure that they have a modern enterprise data platform built on the cloud with a trusted, reusable set of data products.?While technology enables the possibility, skills and people bring the capability. Strategizing and creating a generative AI people pod should be a key step for this enablement as well. Generative AI enablement must be actioned right from the top – promoters, CEOs, and MDs need a virtual generative AI agent – their own virtual personal assistant.
4. Educate: Generative AI raises important questions about the responsible use of AI. The speed of technology evolution and adoption requires companies to pay close attention to its legal, ethical, and reputational risks for the business. They will have to answer key questions on intellectual property, data privacy and security, discrimination, product liability, trust, and identity. Therefore, education and trust are the two factors that enterprises will have to significantly work towards while adopting generative AI.

The Time to Invest is Now

Moments like this don’t come around often. We’re at the start of an incredibly exciting era that will fundamentally transform the way we access information, create content, serve customer needs, and run businesses. Embedded into the enterprise’s digital core, generative AI and foundation models will optimize tasks, augment human capabilities, and open new vistas for growth. These technologies, spearheaded by generative AI, will create a new playbook for enterprise reinvention.

Accenture is ready to help as you begin to re-imagine your business. If you’d like to know more about how we can partner with you in your digital transformation journey, please feel free to contact us.

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References

1.??Accenture Research based on US BLS May 2023 and O*Net

2.??Accenture Research based on US BLS May 2023 and O*Net

3.??Accenture Technology Vision 2024 Executive Survey