RESEARCH REPORT
Reinventing life sciences in the age of generative AI
5-MINUTE READ
August 30, 2024
In brief
- Generative AI is transforming the life sciences industry, enhancing areas such as drug discovery and improving patient care.
- The true value of AI comes from the reinvention of workflows and processes end to end and at scale across the value chain.
- We have identified five must-do actions that the C-suite must consider to reinvent in the age of generative AI.
This is not your typical technology upgrade
Supercharging science with intelligent technologies
The life sciences industry is on the brink of a groundbreaking revolution with the integration of intelligent technologies like generative AI and next generation computing. These innovations could significantly reduce the time and cost associated with bringing new medicines to market. Currently, the process takes an average of 10-12 years, with costs exceeding $2.6 billion and a high failure rate.1
Life sciences companies need to adopt these intelligent technologies and embrace this paradigm shift to remain competitive. Early adopters are likely to achieve a significant advantage in transforming industry challenges into opportunities.
AI is revolutionizing the pharmaceutical value chain
Generative AI is revolutionizing the biopharma industry, offering strategic opportunities to generate significant value if workflows and processes are consistently reinvented end-to-end.
AI-driven methods have accelerated the discovery of over 50 drug candidates and streamlined clinical trials by optimizing protocols through data analysis.2 Manufacturing efficiency can also be improved, with up to a 90% reduction in resource use.3 Moreover, intelligent technologies are refining better capital allocation across the value chain. By leveraging historical sales data, prescription patterns, epidemiology, and demographic data, forecasting becomes more accurate and improves the planning of new manufacturing sites.
These are just a few examples of how intelligent technologies are driving meaningful and positive changes in the biopharma industry. Employed correctly, they can create a significant competitive advantage at each step of the value chain.
Opportunity at every step
AI enhances R&D by speeding up trials, approvals, efficiency and increasing success rates. Challenges like tech inconsistency and data silos exist but can be tackled through better cross-disciplinary collaboration and process optimization
Intelligent tech is accelerating drug recipe development from wet lab to in-silico methods. AI aids in quick regulatory approvals, enhances manufacturing coordination, and boosts supply chain resilience, ensuring compliance and market adaptability.
Integrating classical and generative AI in supply chain design enhances resilience, agility, and sustainability. It focuses on patients and customers, using deep knowledge and data integration to improve plans and capacity.
AI revolutionizes commercialization by improving access, marketing, and customer engagement. It boosts efficiency and improves content creation and compliance processes. AI also equips field teams with tools for data insights and customer engagement.
The impact of generative AI
Based on our research and client experience, if intelligent technologies are used at scale and workflows are reinvented appropriately, companies can achieve:
1-4yr
reduction in bringing a new medicine to market
$0.5-2bn
revenue upside per new medicine
35-45%
reduction in costs per successful drug
10-15%
reduction in working capital (inventory)
10-30%
acceleration of time to peak sales
30%
reduction in corporate function costs
The full potential lies in connection
To fully unlock the potential of generative AI, life sciences companies must adopt a comprehensive approach and think in terms of connecting across value streams. This involves integrating AI across all workflows and building end-to-end processes and capabilities rather than focusing on isolated use cases. Such a holistic strategy makes sure that companies can maximize the benefits of intelligent technologies and achieve significant results for the patient, the entire organization, and the healthcare system.
Five C-Suite imperatives
1
Lead with value
2
Reinventing talent and ways of working
3
Understand and develop an AI-enabled secure digital core
4
Close the gap on responsible AI
5
Drive and support continuous reinvention
1. Lead with value
Companies should understand how generative AI can redefine their processes and enhance capabilities, moving beyond mere cost savings to drive innovation and growth.
2. Reinventing talent and ways of working
Adopting generative AI requires a reevaluation of company processes and workflows, requiring substantial investments in new skills and a shift in roles and behaviors.
3. Understand and develop an AI-enabled secure digital core
Establishing a robust digital infrastructure that integrates advanced digital platforms, a data and AI backbone and a secure digital foundation is essential. This infrastructure must treat data as a strategic asset and allow for the flexibility to adapt to evolving use cases.
4. Close the gap on responsible AI
As AI technologies evolve, addressing ethical concerns and managing risks become paramount. Companies must prioritize responsible AI practices to mitigate potential negative impacts and maintain trust with stakeholders.
5. Drive and support continuous reinvention
To keep pace with technological advancements, companies must foster a culture of innovation and continuous reinvention, constantly adapting their strategies and operations.
Where could reinvention take your business?
Continuous reinvention is a must-have strategy for the biopharma industry. Businesses that reinvent with generative AI will be at the forefront of new performance standards and enhance personalized experiences. It will enable businesses to boost productivity, and generate new revenue streams. The opportunity is multifaceted and holds the potential to significantly enhance patient care.
Sources
1 Taking R&D from Billions to Millions. Accenture.
2 Massachusetts General — Haas Lab Research Summary. Nov 2023.
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