To keep pace in an ultra-competitive industry, pharmaceutical organizations have embraced the artificial intelligence wave. This powerful technology is being used by the biggest healthcare and pharma companies to drive growth and improve outcomes across drug research and discovery, employee training, manufacturing, and more.
According to McKinsey, Generative AI is expected to produce $60bn to $110bn in annual value across the pharmaceutical industry supply chain, and these staggering numbers are why the biggest companies are jumping onboard with AI.
The growth is further highlighted in the fact that schools like the London School of International Business and MIT Sloan are now offering dedicated AI in Pharma qualifications to help upskill those in the industry in what is quickly becoming essential knowledge, as well as the number of scientific papers on AI in the pharmaceutical industry and its ability to revolutionize drug discovery, for example, are published at a rapid rate.
Are you part of a pharmaceutical team that’s not leveraging AI to its fullest potential yet? We’ve picked out 5 of the top use cases of AI in pharma worldwide to showcase where AI can make a difference in your healthcare or pharmaceutical organization. But first, some key stats:
AI in Pharma Statistics:
- McKinsey forecast Generative AI to produce $60bn to $110bn in annual value across the pharmaceutical industry supply chain.
- PwC predicts pharma companies could gain an additional $254bn in annual operating profits worldwide by 2030, assuming a high degree of industrialization of AI use cases.
- Scilife go further, claiming that AI applications can potentially create between $350bn and $410bn in annual value for pharmaceutical companies.
- Scilife adds that using AI in clinical trials could lead to cost savings of 70% per trial and timeline reductions of 80%, reducing the time to develop a drug by four years and saving $26bn.
Bayer: AI Workplace Communication Training
Bayer is one of the most widely-respected healthcare companies in the world, and part of that respect comes from their willingness to lead from the front with technology like artificial intelligence. In line with this innovative spirit, Bayer has implemented AI workplace communication training across several aspects of the organization with great success.
Partnering with VirtualSpeech, who Bayer they as leaders in the area, they deployed AI communication training tackle a number of use cases:
- Realistic negotiation training for Bayer’s procurement departments, who use AI roleplays to prepare for difficult conversations with clients and customers.
- Job interview training for employees who want to move into a new role internally and need to practice answering career-focused questions.
- Intercultural training to ensure employees in global teams are able to communicate and work effectively regardless of their style of work or cultural background.
This collaboration continues to be highly successful, with the AI-powered training receiving an NPS score of 81.6 and a user feedback score of 9/10 from Bayer’s employees, with one stating that it was the “most engaging training [they’ve] ever done”.
Johnson & Johnson: Predictive Maintenance and Demand Forecasting With AI
Inventory and supply chain management is a critical part of the pharmaceutical industry and any gains in that area will have significant positive impact downstream for whichever organization leverages those gains. Johnson & Johnson, with its plant in Mulund, India, has already given us a glimpse into the potential of AI-powered predictive maintenance and demand forecasting.
This Johnson & Johnson factory, utilizing the latest AI/ML , implemented demand sensing, smart logistics, robotics and 3D printing, which resulted in:
- Reduced OTIF losses by 66%
- Accelerated new product introduction by 33%
- Improved cost per piece by 34%
Further, predictive maintenance improved asset reliability and reduced unplanned machine downtime by an impressive 50%. As these AI-powered technologies begin rolling out across other plants and factories, Johnson & Johnson will have the opportunity to scale these gains further.
Insitro: Innovative AI-Driven Drug Development
Insitro says it’s building a different kind of pharma company, one powered by AI and machine learning. Insitro’s ML-driven platform integrates in vitro cellular data produced in labs with human clinical data to help redefine disease. This advanced, tech-first approach allows Insitro to:
- Accelerate the development of new medicines
- Precisely identify therapeutic insights and interventions across a wide spectrum of diseases
- Trains models on gene sequences, clinical outcomes, and pathology slides to make predictions of how cancer patients are likely to respond to particular treatments
The newest AI/ML models can work at a speed and scale far beyond human capabilities, allowing the pharmaceutical industry and companies like Insitro to deliver results faster than ever before.
Siemens & GSK: AI-Accelerated Drug Research
Global technology leader Siemens has gone all in on AI-powered pharma and turned its focus on AI technology that it says will accelerate the next wave of advances in the pharma industry – especially in drug research and development.
Traditionally an inefficient and time-consuming process involving complex experiments in a physical laboratory, today drug R&D at the likes of GlaxoSmithKline (GSK) is being sped up with the help of Siemens’ AI-powered digital solutions.
Siemens’ AI technology allows pharmaceutical companies like GSK to reduce the number of digital experiments they need to conduct (saving costs in the process), thanks to advanced simulation analysis that guides research teams towards fast drug optimization.
The key figure that emerges from this collaboration is a 25% reduction in physical experiments and a greatly reduced overall development time – with even more possibilities to come as Siemens develops its AI technology and integrates with GSK further.
Worldwide & Medidata: Clinical Trials Powered By AI
Worldwide Clinical Trials, a global contract research organization has partnered with Medidata, a leading provider of clinical trial solutions to change the way clinical trial lifecycle looks in order to elevate results. Medidata’s AI solution helps Worldwide and others to:
- Simulating trial outcomes
- Surface insights early
- Guide researchers on next best actions
This helps clinical trial teams make confident, data-backed decisions at a greater pace and ensures that every stage of the trial process, from design to close-out, is optimized for accurate results. Medidata’s AI-powered clinical trial solution has shown to reduce errors by up to 80%, which has exciting potential for the future of this key area of drug research.
Bringing AI Training to Your Organization
If you want to take the next step and implement AI-powered workplace communication training in your organization, get in touch and find out how VirtualSpeech’s award-winning soft skills training can support your learners just like it does for Bayer.
