Case Study: A Look at How Artificial Intelligence Is Being Used by the Pharma Industry in Drug Development and Clinical Trials

The report includes complete overview of pharma companies leading the integration of AI into their operations, partnerships between Big Pharma and AI start-ups, and AI vendor company profiles among many others.

The pharmaceutical industry has a reputation as being risk averse to embracing new technologies and spent many years in “watch and wait” mode regarding artificial intelligence (AI).

Compared to other industries, pharma has been slow to adopt AI, but there has been increased activity over the past few years.

AI can be used across a wide range of functions, including drug discovery, clinical trials, smart supply chains, and sales and marketing. Leading AI start-ups in drug discovery include Exscientia, Atomwise, Recursion, Iktos, Insilico Medicine, and Sensyne Health.

Many pharmaceutical companies are partnering with these and other start-ups to take advantage of their AI technology. Pharmaceutical companies are beginning to set up in-house AI capabilities. GSK was an early pioneer in this field, as it set up an in-house AI unit in 2017. Other companies like Novartis, Roche, and Bayer are following suit.

A major analysis of How Artificial Intelligence Is Being Used by the Pharma Industry in Drug Development and Clinical Trials

• AI is being used to reduce the cost and length of clinical trials, with improved design and patient recruitment

• Symbolic learning means you teach a machine symbol that humans can understand, such as things, people, and actions

• The data-based approach, known as machine learning (ML), involves giving a lot of data to a program. The program then decides by itself what is essential for making a decision and what is not

• Within the AI industry, seven key technology categories have been identified: ML, data science, conversational platforms, computer vision, AI chips, smart robots, and context-aware computing

• The pharmaceutical industry has a reputation as being risk-averse to embracing new technologies and spent many years in “watch and wait” mode regarding AI

• The entire process of developing a drug from preclinical research to marketing can take 12–18 years and often costs between $2.0–3.0B, with only about 10% of candidates successfully completing clinical trials and gaining regulatory approval

Access the report to understand how artificial intelligence is being applied and its impacts on Drug Development and Clinical Trials.