AI Trends in the Life Sciences Industry
A fundamental shift in the pharmaceutical industry and artificial intelligence (AI) is occurring, helping to shape the pharma industry in the 21st Century. AI and machine learning offer the pharmaceutical industry with an opportunity to rethink research and development (R&D), so that it can significantly improve the success rate of early stage drug development.
The current drug development process is lengthy and expensive. It can take up to fifteen years for a new drug to go from inception to market, and can cost over $1 billion per drug. The drug discovery process can be greatly aided by AI and machine learning technology. The amount of daily data generated by biomedical research is staggering. It is estimated upwards of 10,000 new biomedical publications from databases and journals are uploaded to the Internet daily, representing an enormous amount of data.
Human researchers are not capable of processing that much data; there is no way for them to gain the knowledge of every new development or discovery in their area of investigation. And, without the ability to aggregate, analyze and connect all of the data available, it’s impossible to synthesize new and usable knowledge.
This is where AI and machine learning can play a major role in supporting the work of drug development researchers. AI can assimilate the mass of scientific data and form essential new knowledge as it pertains to new areas of research. Once the data is reviewed by the machine, it is able to find direct relationships between the data, developing “known facts”. These known facts are curated and a large number of possible hypotheses are generated using previously unrealized connections in the data.
While AI and machine learning is definitely on the radar of pharma leaders, there are obstacles facing pharma companies to increase and integrate talent and technology. Here are some of the biggest challenges:
- Talented people that have deep experience with artificial intelligence as well as biopharma or healthcare are extremely limited. AI experts rarely have an expertise in biology.
- Mindset adoption that AI and machine learning are worth the investment.
- The nature and availability of data has been an issue due to strict regulatory and compliance standards.
- Machine learning requires large quantities of high-quality data. This contrasts sharply with traditional bioscience, which tends to emphasize slow and deliberate changes.
- Isolated data silos that make it difficult for AI applications to access the data they need.
Pharmaceutical leaders are finding ways around these obstacles. They are beginning to emphasize partnerships and collaborations, which was unheard of in the industry even in the recent past. They are restructuring internal computer science in order to reduce underlying barriers within the company.
Data and functional silos are being broken down as a critical factor for machine learning insight. For now, the pharma giants are leading the way, mostly because they have the budget and influence to make it happen. Some pharma and biotech companies are forming new data science teams that have a mix of talent, such as bioinformatics, cheminformatics, clinical analytics, commercial analytics, machine learning, IT, and AI expertise.
In terms of design, the scope and augmentation that AI and machine learning offer will allow researchers to tap into a much broader space, giving a wider and more varied palette for drug discovery. The technology will also help in terms of clinical trials and identify issues sooner, increasing efficiencies and safety. The pharmaceutical industry has much to gain by adopting AI and machine learning methods, leading to a strong, sustainable new pipeline of medicines.
Marsh & McLennan Agency’s Life Science Practice has significant expertise in structuring nationally-recognized insurance and risk management services for clients in the pharmaceutical, medical device and biotechnology industries. To learn more about our smart insurance solutions that allow businesses to thrive in the marketplace, contact us here.